arm_compute v18.08
diff --git a/documentation/annotated.xhtml b/documentation/annotated.xhtml
index 4d1cba4..50d313d 100644
--- a/documentation/annotated.xhtml
+++ b/documentation/annotated.xhtml
@@ -40,7 +40,7 @@
<tr style="height: 56px;">
<td style="padding-left: 0.5em;">
<div id="projectname">Compute Library
-  <span id="projectnumber">18.05</span>
+  <span id="projectnumber">18.08</span>
</div>
</td>
</tr>
@@ -156,77 +156,91 @@
<tr id="row_0_2_1_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_activation_layer.xhtml" target="_self">ActivationLayer</a></td><td class="desc">Activation Layer </td></tr>
<tr id="row_0_2_1_1_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_batch_normalization_layer.xhtml" target="_self">BatchNormalizationLayer</a></td><td class="desc">Batchnormalization Layer </td></tr>
<tr id="row_0_2_1_2_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_branch_layer.xhtml" target="_self">BranchLayer</a></td><td class="desc">Branch Layer </td></tr>
-<tr id="row_0_2_1_3_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_convolution_layer.xhtml" target="_self">ConvolutionLayer</a></td><td class="desc">Convolution Layer </td></tr>
-<tr id="row_0_2_1_4_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_depthwise_convolution_layer.xhtml" target="_self">DepthwiseConvolutionLayer</a></td><td class="desc">Depthwise Convolution Layer </td></tr>
-<tr id="row_0_2_1_5_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_flatten_layer.xhtml" target="_self">FlattenLayer</a></td><td class="desc">Flatten Layer </td></tr>
-<tr id="row_0_2_1_6_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_fully_connected_layer.xhtml" target="_self">FullyConnectedLayer</a></td><td class="desc">Fully Connected Layer </td></tr>
-<tr id="row_0_2_1_7_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_i_layer.xhtml" target="_self">ILayer</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_i_layer.xhtml" title="ILayer interface. ">ILayer</a> interface </td></tr>
-<tr id="row_0_2_1_8_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_input_layer.xhtml" target="_self">InputLayer</a></td><td class="desc">Input Layer </td></tr>
-<tr id="row_0_2_1_9_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_i_stream.xhtml" target="_self">IStream</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_stream.xhtml" title="Stream frontend class to construct simple graphs in a stream fashion. ">Stream</a> interface </td></tr>
-<tr id="row_0_2_1_10_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_normalization_layer.xhtml" target="_self">NormalizationLayer</a></td><td class="desc">Normalization Layer </td></tr>
-<tr id="row_0_2_1_11_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_output_layer.xhtml" target="_self">OutputLayer</a></td><td class="desc">Output Layer </td></tr>
-<tr id="row_0_2_1_12_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_pooling_layer.xhtml" target="_self">PoolingLayer</a></td><td class="desc">Pooling Layer </td></tr>
-<tr id="row_0_2_1_13_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_reshape_layer.xhtml" target="_self">ReshapeLayer</a></td><td class="desc">Reshape Layer </td></tr>
-<tr id="row_0_2_1_14_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_scale_layer.xhtml" target="_self">ScaleLayer</a></td><td class="desc">Scale Layer </td></tr>
-<tr id="row_0_2_1_15_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_softmax_layer.xhtml" target="_self">SoftmaxLayer</a></td><td class="desc">Softmax Layer </td></tr>
-<tr id="row_0_2_1_16_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_stream.xhtml" target="_self">Stream</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_stream.xhtml" title="Stream frontend class to construct simple graphs in a stream fashion. ">Stream</a> frontend class to construct simple graphs in a stream fashion </td></tr>
-<tr id="row_0_2_1_17_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1frontend_1_1_stream_hints.xhtml" target="_self">StreamHints</a></td><td class="desc">Hints that can be passed to the stream to expose parameterization </td></tr>
-<tr id="row_0_2_1_18_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_sub_stream.xhtml" target="_self">SubStream</a></td><td class="desc">Sub stream class </td></tr>
+<tr id="row_0_2_1_3_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_channel_shuffle_layer.xhtml" target="_self">ChannelShuffleLayer</a></td><td class="desc">Channel Shuffle Layer </td></tr>
+<tr id="row_0_2_1_4_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_convolution_layer.xhtml" target="_self">ConvolutionLayer</a></td><td class="desc">Convolution Layer </td></tr>
+<tr id="row_0_2_1_5_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_deconvolution_layer.xhtml" target="_self">DeconvolutionLayer</a></td><td class="desc">Deconvolution Layer </td></tr>
+<tr id="row_0_2_1_6_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_depthwise_convolution_layer.xhtml" target="_self">DepthwiseConvolutionLayer</a></td><td class="desc">Depthwise Convolution Layer </td></tr>
+<tr id="row_0_2_1_7_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_dummy_layer.xhtml" target="_self">DummyLayer</a></td><td class="desc">Dummy Layer </td></tr>
+<tr id="row_0_2_1_8_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_flatten_layer.xhtml" target="_self">FlattenLayer</a></td><td class="desc">Flatten Layer </td></tr>
+<tr id="row_0_2_1_9_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_fully_connected_layer.xhtml" target="_self">FullyConnectedLayer</a></td><td class="desc">Fully Connected Layer </td></tr>
+<tr id="row_0_2_1_10_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_i_layer.xhtml" target="_self">ILayer</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_i_layer.xhtml" title="ILayer interface. ">ILayer</a> interface </td></tr>
+<tr id="row_0_2_1_11_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_input_layer.xhtml" target="_self">InputLayer</a></td><td class="desc">Input Layer </td></tr>
+<tr id="row_0_2_1_12_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_i_stream.xhtml" target="_self">IStream</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_stream.xhtml" title="Stream frontend class to construct simple graphs in a stream fashion. ">Stream</a> interface </td></tr>
+<tr id="row_0_2_1_13_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_normalization_layer.xhtml" target="_self">NormalizationLayer</a></td><td class="desc">Normalization Layer </td></tr>
+<tr id="row_0_2_1_14_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_output_layer.xhtml" target="_self">OutputLayer</a></td><td class="desc">Output Layer </td></tr>
+<tr id="row_0_2_1_15_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_permute_layer.xhtml" target="_self">PermuteLayer</a></td><td class="desc">Permute Layer </td></tr>
+<tr id="row_0_2_1_16_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_pooling_layer.xhtml" target="_self">PoolingLayer</a></td><td class="desc">Pooling Layer </td></tr>
+<tr id="row_0_2_1_17_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_reshape_layer.xhtml" target="_self">ReshapeLayer</a></td><td class="desc">Reshape Layer </td></tr>
+<tr id="row_0_2_1_18_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_resize_layer.xhtml" target="_self">ResizeLayer</a></td><td class="desc">Resize Layer </td></tr>
+<tr id="row_0_2_1_19_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_scale_layer.xhtml" target="_self">ScaleLayer</a></td><td class="desc">Scale Layer </td></tr>
+<tr id="row_0_2_1_20_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_softmax_layer.xhtml" target="_self">SoftmaxLayer</a></td><td class="desc">Softmax Layer </td></tr>
+<tr id="row_0_2_1_21_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_stream.xhtml" target="_self">Stream</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_stream.xhtml" title="Stream frontend class to construct simple graphs in a stream fashion. ">Stream</a> frontend class to construct simple graphs in a stream fashion </td></tr>
+<tr id="row_0_2_1_22_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1frontend_1_1_stream_hints.xhtml" target="_self">StreamHints</a></td><td class="desc">Hints that can be passed to the stream to expose parameterization </td></tr>
+<tr id="row_0_2_1_23_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1frontend_1_1_sub_stream.xhtml" target="_self">SubStream</a></td><td class="desc">Sub stream class </td></tr>
<tr id="row_0_2_2_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_activation_layer_node.xhtml" target="_self">ActivationLayerNode</a></td><td class="desc">Activation Layer node </td></tr>
<tr id="row_0_2_3_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_batch_normalization_layer_node.xhtml" target="_self">BatchNormalizationLayerNode</a></td><td class="desc">Batch Normalization Layer node </td></tr>
-<tr id="row_0_2_4_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_const_node.xhtml" target="_self">ConstNode</a></td><td class="desc">Const node </td></tr>
-<tr id="row_0_2_5_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_convolution_layer_node.xhtml" target="_self">ConvolutionLayerNode</a></td><td class="desc">Convolution Layer node </td></tr>
-<tr id="row_0_2_6_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_default_node_visitor.xhtml" target="_self">DefaultNodeVisitor</a></td><td class="desc">Default visitor implementation </td></tr>
-<tr id="row_0_2_7_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_depth_concatenate_layer_node.xhtml" target="_self">DepthConcatenateLayerNode</a></td><td class="desc">Depth Concatenation Layer node </td></tr>
-<tr id="row_0_2_8_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_depth_concat_sub_tensor_mutator.xhtml" target="_self">DepthConcatSubTensorMutator</a></td><td class="desc">Mutation pass to optimize depth concatenation operations by using sub-tensors </td></tr>
-<tr id="row_0_2_9_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml" target="_self">DepthwiseConvolutionLayerNode</a></td><td class="desc">Depthwise Convolution Layer node </td></tr>
-<tr id="row_0_2_10_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_dot_graph_printer.xhtml" target="_self">DotGraphPrinter</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> printer interface </td></tr>
-<tr id="row_0_2_11_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_dot_graph_visitor.xhtml" target="_self">DotGraphVisitor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> printer visitor </td></tr>
-<tr id="row_0_2_12_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_edge.xhtml" target="_self">Edge</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> <a class="el" href="classarm__compute_1_1graph_1_1_edge.xhtml" title="Graph Edge. ">Edge</a> </td></tr>
-<tr id="row_0_2_13_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_eltwise_layer_node.xhtml" target="_self">EltwiseLayerNode</a></td><td class="desc">Eltwise Layer node </td></tr>
-<tr id="row_0_2_14_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_execution_task.xhtml" target="_self">ExecutionTask</a></td><td class="desc">Execution task </td></tr>
-<tr id="row_0_2_15_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_execution_workload.xhtml" target="_self">ExecutionWorkload</a></td><td class="desc">Execution workload </td></tr>
-<tr id="row_0_2_16_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_flatten_layer_node.xhtml" target="_self">FlattenLayerNode</a></td><td class="desc">Flatten Layer node </td></tr>
-<tr id="row_0_2_17_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_fully_connected_layer_node.xhtml" target="_self">FullyConnectedLayerNode</a></td><td class="desc">Fully Connected Layer node </td></tr>
-<tr id="row_0_2_18_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" target="_self">Graph</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> class </td></tr>
-<tr id="row_0_2_19_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph_builder.xhtml" target="_self">GraphBuilder</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> builder class </td></tr>
-<tr id="row_0_2_20_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_graph_config.xhtml" target="_self">GraphConfig</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> configuration structure Device target types </td></tr>
-<tr id="row_0_2_21_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph_context.xhtml" target="_self">GraphContext</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> context </td></tr>
-<tr id="row_0_2_22_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph_manager.xhtml" target="_self">GraphManager</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> manager class </td></tr>
-<tr id="row_0_2_23_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_graph_mutator.xhtml" target="_self">IGraphMutator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> mutator interface </td></tr>
-<tr id="row_0_2_24_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_graph_printer.xhtml" target="_self">IGraphPrinter</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> printer interface </td></tr>
-<tr id="row_0_2_25_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_node.xhtml" target="_self">INode</a></td><td class="desc">Node interface </td></tr>
-<tr id="row_0_2_26_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_node_visitor.xhtml" target="_self">INodeVisitor</a></td><td class="desc">Node visitor interface </td></tr>
-<tr id="row_0_2_27_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_in_place_operation_mutator.xhtml" target="_self">InPlaceOperationMutator</a></td><td class="desc">Mutation pass to optimize operations that can be performed in-place </td></tr>
-<tr id="row_0_2_28_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_input_node.xhtml" target="_self">InputNode</a></td><td class="desc">Input Layer node </td></tr>
-<tr id="row_0_2_29_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_tensor_accessor.xhtml" target="_self">ITensorAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" title="Tensor object. ">Tensor</a> accessor interface </td></tr>
-<tr id="row_0_2_30_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_tensor_handle.xhtml" target="_self">ITensorHandle</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" title="Tensor object. ">Tensor</a> handle interface object </td></tr>
-<tr id="row_0_2_31_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_memory_manager_context.xhtml" target="_self">MemoryManagerContext</a></td><td class="desc">Contains structs required for memory management </td></tr>
-<tr id="row_0_2_32_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_node_fusion_mutator.xhtml" target="_self">NodeFusionMutator</a></td><td class="desc">Mutation pass to fuss nodes </td></tr>
-<tr id="row_0_2_33_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_node_idx_pair.xhtml" target="_self">NodeIdxPair</a></td><td class="desc">NodeID-index struct </td></tr>
-<tr id="row_0_2_34_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_node_params.xhtml" target="_self">NodeParams</a></td><td class="desc">Common node parameters </td></tr>
-<tr id="row_0_2_35_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_normalization_layer_node.xhtml" target="_self">NormalizationLayerNode</a></td><td class="desc">Normalization Layer node </td></tr>
-<tr id="row_0_2_36_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_output_node.xhtml" target="_self">OutputNode</a></td><td class="desc">Output Layer node </td></tr>
-<tr id="row_0_2_37_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_pass_manager.xhtml" target="_self">PassManager</a></td><td class="desc">Pass manager </td></tr>
-<tr id="row_0_2_38_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_pooling_layer_node.xhtml" target="_self">PoolingLayerNode</a></td><td class="desc">Pooling Layer node </td></tr>
-<tr id="row_0_2_39_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_reshape_layer_node.xhtml" target="_self">ReshapeLayerNode</a></td><td class="desc">Reshape Layer node </td></tr>
-<tr id="row_0_2_40_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_softmax_layer_node.xhtml" target="_self">SoftmaxLayerNode</a></td><td class="desc">Softmax Layer node </td></tr>
-<tr id="row_0_2_41_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_split_layer_node.xhtml" target="_self">SplitLayerNode</a></td><td class="desc">Split Layer node </td></tr>
-<tr id="row_0_2_42_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_split_layer_sub_tensor_mutator.xhtml" target="_self">SplitLayerSubTensorMutator</a></td><td class="desc">Mutation pass to optimize split operations by using sub-tensors </td></tr>
-<tr id="row_0_2_43_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_task_executor.xhtml" target="_self">TaskExecutor</a></td><td class="desc">Task executor </td></tr>
-<tr id="row_0_2_44_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" target="_self">Tensor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" title="Tensor object. ">Tensor</a> object </td></tr>
-<tr id="row_0_2_45_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_tensor_descriptor.xhtml" target="_self">TensorDescriptor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" title="Tensor object. ">Tensor</a> metadata class </td></tr>
+<tr id="row_0_2_4_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_channel_shuffle_layer_node.xhtml" target="_self">ChannelShuffleLayerNode</a></td><td class="desc">Channel Shuffle Layer node </td></tr>
+<tr id="row_0_2_5_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_concatenate_layer_node.xhtml" target="_self">ConcatenateLayerNode</a></td><td class="desc">Concatenation Layer node </td></tr>
+<tr id="row_0_2_6_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_const_node.xhtml" target="_self">ConstNode</a></td><td class="desc">Const node </td></tr>
+<tr id="row_0_2_7_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_convolution_layer_node.xhtml" target="_self">ConvolutionLayerNode</a></td><td class="desc">Convolution Layer node </td></tr>
+<tr id="row_0_2_8_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_deconvolution_layer_node.xhtml" target="_self">DeconvolutionLayerNode</a></td><td class="desc">Deconvolution Layer node </td></tr>
+<tr id="row_0_2_9_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_default_node_visitor.xhtml" target="_self">DefaultNodeVisitor</a></td><td class="desc">Default visitor implementation </td></tr>
+<tr id="row_0_2_10_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_depth_concat_sub_tensor_mutator.xhtml" target="_self">DepthConcatSubTensorMutator</a></td><td class="desc">Mutation pass to optimize depth concatenation operations by using sub-tensors </td></tr>
+<tr id="row_0_2_11_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml" target="_self">DepthwiseConvolutionLayerNode</a></td><td class="desc">Depthwise Convolution Layer node </td></tr>
+<tr id="row_0_2_12_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_dot_graph_printer.xhtml" target="_self">DotGraphPrinter</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> printer interface </td></tr>
+<tr id="row_0_2_13_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_dot_graph_visitor.xhtml" target="_self">DotGraphVisitor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> printer visitor </td></tr>
+<tr id="row_0_2_14_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_dummy_node.xhtml" target="_self">DummyNode</a></td><td class="desc">Dummy Layer node </td></tr>
+<tr id="row_0_2_15_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_edge.xhtml" target="_self">Edge</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> <a class="el" href="classarm__compute_1_1graph_1_1_edge.xhtml" title="Graph Edge. ">Edge</a> </td></tr>
+<tr id="row_0_2_16_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_eltwise_layer_node.xhtml" target="_self">EltwiseLayerNode</a></td><td class="desc">Eltwise Layer node </td></tr>
+<tr id="row_0_2_17_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_execution_task.xhtml" target="_self">ExecutionTask</a></td><td class="desc">Execution task </td></tr>
+<tr id="row_0_2_18_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_execution_workload.xhtml" target="_self">ExecutionWorkload</a></td><td class="desc">Execution workload </td></tr>
+<tr id="row_0_2_19_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_flatten_layer_node.xhtml" target="_self">FlattenLayerNode</a></td><td class="desc">Flatten Layer node </td></tr>
+<tr id="row_0_2_20_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_fully_connected_layer_node.xhtml" target="_self">FullyConnectedLayerNode</a></td><td class="desc">Fully Connected Layer node </td></tr>
+<tr id="row_0_2_21_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" target="_self">Graph</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> class </td></tr>
+<tr id="row_0_2_22_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph_builder.xhtml" target="_self">GraphBuilder</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> builder class </td></tr>
+<tr id="row_0_2_23_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_graph_config.xhtml" target="_self">GraphConfig</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> configuration structure Device target types </td></tr>
+<tr id="row_0_2_24_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph_context.xhtml" target="_self">GraphContext</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> context </td></tr>
+<tr id="row_0_2_25_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph_manager.xhtml" target="_self">GraphManager</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> manager class </td></tr>
+<tr id="row_0_2_26_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_grouped_convolution_mutator.xhtml" target="_self">GroupedConvolutionMutator</a></td><td class="desc">Mutation pass to implement/optimize grouped convolutions </td></tr>
+<tr id="row_0_2_27_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_graph_mutator.xhtml" target="_self">IGraphMutator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> mutator interface </td></tr>
+<tr id="row_0_2_28_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_graph_printer.xhtml" target="_self">IGraphPrinter</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> printer interface </td></tr>
+<tr id="row_0_2_29_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_node.xhtml" target="_self">INode</a></td><td class="desc">Node interface </td></tr>
+<tr id="row_0_2_30_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_node_visitor.xhtml" target="_self">INodeVisitor</a></td><td class="desc">Node visitor interface </td></tr>
+<tr id="row_0_2_31_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_in_place_operation_mutator.xhtml" target="_self">InPlaceOperationMutator</a></td><td class="desc">Mutation pass to optimize operations that can be performed in-place </td></tr>
+<tr id="row_0_2_32_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_input_node.xhtml" target="_self">InputNode</a></td><td class="desc">Input Layer node </td></tr>
+<tr id="row_0_2_33_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_tensor_accessor.xhtml" target="_self">ITensorAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" title="Tensor object. ">Tensor</a> accessor interface </td></tr>
+<tr id="row_0_2_34_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_i_tensor_handle.xhtml" target="_self">ITensorHandle</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" title="Tensor object. ">Tensor</a> handle interface object </td></tr>
+<tr id="row_0_2_35_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_memory_manager_context.xhtml" target="_self">MemoryManagerContext</a></td><td class="desc">Contains structs required for memory management </td></tr>
+<tr id="row_0_2_36_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_node_execution_method_mutator.xhtml" target="_self">NodeExecutionMethodMutator</a></td><td class="desc">Mutation pass to fall-back to default execution method </td></tr>
+<tr id="row_0_2_37_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_node_fusion_mutator.xhtml" target="_self">NodeFusionMutator</a></td><td class="desc">Mutation pass to fuss nodes </td></tr>
+<tr id="row_0_2_38_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_node_idx_pair.xhtml" target="_self">NodeIdxPair</a></td><td class="desc">NodeID-index struct </td></tr>
+<tr id="row_0_2_39_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_node_params.xhtml" target="_self">NodeParams</a></td><td class="desc">Common node parameters </td></tr>
+<tr id="row_0_2_40_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_normalization_layer_node.xhtml" target="_self">NormalizationLayerNode</a></td><td class="desc">Normalization Layer node </td></tr>
+<tr id="row_0_2_41_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_output_node.xhtml" target="_self">OutputNode</a></td><td class="desc">Output Layer node </td></tr>
+<tr id="row_0_2_42_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_pass_manager.xhtml" target="_self">PassManager</a></td><td class="desc">Pass manager </td></tr>
+<tr id="row_0_2_43_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_permute_layer_node.xhtml" target="_self">PermuteLayerNode</a></td><td class="desc">Permute Layer node </td></tr>
+<tr id="row_0_2_44_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_pooling_layer_node.xhtml" target="_self">PoolingLayerNode</a></td><td class="desc">Pooling Layer node </td></tr>
+<tr id="row_0_2_45_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_reshape_layer_node.xhtml" target="_self">ReshapeLayerNode</a></td><td class="desc">Reshape Layer node </td></tr>
+<tr id="row_0_2_46_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_resize_layer_node.xhtml" target="_self">ResizeLayerNode</a></td><td class="desc">Resize Layer node </td></tr>
+<tr id="row_0_2_47_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_softmax_layer_node.xhtml" target="_self">SoftmaxLayerNode</a></td><td class="desc">Softmax Layer node </td></tr>
+<tr id="row_0_2_48_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_split_layer_node.xhtml" target="_self">SplitLayerNode</a></td><td class="desc">Split Layer node </td></tr>
+<tr id="row_0_2_49_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_split_layer_sub_tensor_mutator.xhtml" target="_self">SplitLayerSubTensorMutator</a></td><td class="desc">Mutation pass to optimize split operations by using sub-tensors </td></tr>
+<tr id="row_0_2_50_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_task_executor.xhtml" target="_self">TaskExecutor</a></td><td class="desc">Task executor </td></tr>
+<tr id="row_0_2_51_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" target="_self">Tensor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" title="Tensor object. ">Tensor</a> object </td></tr>
+<tr id="row_0_2_52_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_tensor_descriptor.xhtml" target="_self">TensorDescriptor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" title="Tensor object. ">Tensor</a> metadata class </td></tr>
<tr id="row_0_3_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_3_" class="arrow" onclick="toggleFolder('0_3_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1graph__utils.xhtml" target="_self">graph_utils</a></td><td class="desc"></td></tr>
<tr id="row_0_3_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_caffe_preproccessor.xhtml" target="_self">CaffePreproccessor</a></td><td class="desc">Caffe preproccessor </td></tr>
<tr id="row_0_3_1_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_dummy_accessor.xhtml" target="_self">DummyAccessor</a></td><td class="desc">Dummy accessor class </td></tr>
-<tr id="row_0_3_2_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_i_preprocessor.xhtml" target="_self">IPreprocessor</a></td><td class="desc">Preprocessor interface </td></tr>
-<tr id="row_0_3_3_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_num_py_accessor.xhtml" target="_self">NumPyAccessor</a></td><td class="desc">NumPy accessor class </td></tr>
-<tr id="row_0_3_4_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml" target="_self">NumPyBinLoader</a></td><td class="desc">Numpy Binary loader class </td></tr>
-<tr id="row_0_3_5_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_p_p_m_accessor.xhtml" target="_self">PPMAccessor</a></td><td class="desc">PPM accessor class </td></tr>
+<tr id="row_0_3_2_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_image_accessor.xhtml" target="_self">ImageAccessor</a></td><td class="desc"><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> accessor class </td></tr>
+<tr id="row_0_3_3_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_i_preprocessor.xhtml" target="_self">IPreprocessor</a></td><td class="desc">Preprocessor interface </td></tr>
+<tr id="row_0_3_4_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_num_py_accessor.xhtml" target="_self">NumPyAccessor</a></td><td class="desc">NumPy accessor class </td></tr>
+<tr id="row_0_3_5_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml" target="_self">NumPyBinLoader</a></td><td class="desc">Numpy Binary loader class </td></tr>
<tr id="row_0_3_6_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml" target="_self">PPMWriter</a></td><td class="desc">PPM writer class </td></tr>
<tr id="row_0_3_7_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml" target="_self">RandomAccessor</a></td><td class="desc">Random accessor class </td></tr>
<tr id="row_0_3_8_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_t_f_preproccessor.xhtml" target="_self">TFPreproccessor</a></td><td class="desc">TF preproccessor </td></tr>
<tr id="row_0_3_9_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_top_n_predictions_accessor.xhtml" target="_self">TopNPredictionsAccessor</a></td><td class="desc">Result accessor class </td></tr>
+<tr id="row_0_3_10_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_validation_input_accessor.xhtml" target="_self">ValidationInputAccessor</a></td><td class="desc">Input Accessor used for network validation </td></tr>
+<tr id="row_0_3_11_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph__utils_1_1_validation_output_accessor.xhtml" target="_self">ValidationOutputAccessor</a></td><td class="desc">Output Accessor used for network validation </td></tr>
<tr id="row_0_4_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_4_" class="arrow" onclick="toggleFolder('0_4_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1io.xhtml" target="_self">io</a></td><td class="desc"></td></tr>
<tr id="row_0_4_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1io_1_1_file_handler.xhtml" target="_self">FileHandler</a></td><td class="desc">File Handling interface </td></tr>
<tr id="row_0_5_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_5_" class="arrow" onclick="toggleFolder('0_5_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1logging.xhtml" target="_self">logging</a></td><td class="desc"></td></tr>
@@ -255,22 +269,8 @@
<tr id="row_0_9_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_9_" class="arrow" onclick="toggleFolder('0_9_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test.xhtml" target="_self">test</a></td><td class="desc"></td></tr>
<tr id="row_0_9_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_0_" class="arrow" onclick="toggleFolder('0_9_0_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1benchmark.xhtml" target="_self">benchmark</a></td><td class="desc"></td></tr>
<tr id="row_0_9_0_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_0_9_0_0_" class="arrow" onclick="toggleFolder('0_9_0_0_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1benchmark_1_1_c_l_suite.xhtml" target="_self">CLSuite</a></td><td class="desc"></td></tr>
-<tr id="row_0_9_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_1_" class="arrow" onclick="toggleFolder('0_9_1_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1convolution__3d.xhtml" target="_self">convolution_3d</a></td><td class="desc"></td></tr>
-<tr id="row_0_9_2_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_2_" class="arrow" onclick="toggleFolder('0_9_2_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic.xhtml" target="_self">fixed_point_arithmetic</a></td><td class="desc"></td></tr>
-<tr id="row_0_9_2_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_0_9_2_0_" class="arrow" onclick="toggleFolder('0_9_2_0_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml" target="_self">detail</a></td><td class="desc"></td></tr>
-<tr id="row_0_9_2_0_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_1_1constant__expr.xhtml" target="_self">constant_expr</a></td><td class="desc">Constant expressions </td></tr>
-<tr id="row_0_9_2_0_1_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_1_1functions.xhtml" target="_self">functions</a></td><td class="desc">Functions </td></tr>
-<tr id="row_0_9_2_1_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_0_9_2_1_" class="arrow" onclick="toggleFolder('0_9_2_1_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits.xhtml" target="_self">traits</a></td><td class="desc">Fixed point traits </td></tr>
-<tr id="row_0_9_2_1_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote.xhtml" target="_self">promote</a></td><td class="desc">Promote a type </td></tr>
-<tr id="row_0_9_2_1_1_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01float_01_4.xhtml" target="_self">promote< float ></a></td><td class="desc">Promote float to float </td></tr>
-<tr id="row_0_9_2_1_2_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01half_01_4.xhtml" target="_self">promote< half ></a></td><td class="desc">Promote half to half </td></tr>
-<tr id="row_0_9_2_1_3_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01int16__t_01_4.xhtml" target="_self">promote< int16_t ></a></td><td class="desc">Promote int16_t to int32_t </td></tr>
-<tr id="row_0_9_2_1_4_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01int32__t_01_4.xhtml" target="_self">promote< int32_t ></a></td><td class="desc">Promote int32_t to int64_t </td></tr>
-<tr id="row_0_9_2_1_5_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01int8__t_01_4.xhtml" target="_self">promote< int8_t ></a></td><td class="desc">Promote int8_t to int16_t </td></tr>
-<tr id="row_0_9_2_1_6_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01uint16__t_01_4.xhtml" target="_self">promote< uint16_t ></a></td><td class="desc">Promote uint16_t to uint32_t </td></tr>
-<tr id="row_0_9_2_1_7_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01uint32__t_01_4.xhtml" target="_self">promote< uint32_t ></a></td><td class="desc">Promote uint32_t to uint64_t </td></tr>
-<tr id="row_0_9_2_1_8_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01uint8__t_01_4.xhtml" target="_self">promote< uint8_t ></a></td><td class="desc">Promote uint8_t to uint16_t </td></tr>
-<tr id="row_0_9_2_2_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1fixed__point__arithmetic_1_1fixed__point.xhtml" target="_self">fixed_point</a></td><td class="desc">Arbitrary fixed-point arithmetic class </td></tr>
+<tr id="row_0_9_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_1_" class="arrow" onclick="toggleFolder('0_9_1_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1colorconvert__helper.xhtml" target="_self">colorconvert_helper</a></td><td class="desc"></td></tr>
+<tr id="row_0_9_2_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_2_" class="arrow" onclick="toggleFolder('0_9_2_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1convolution__3d.xhtml" target="_self">convolution_3d</a></td><td class="desc"></td></tr>
<tr id="row_0_9_3_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_3_" class="arrow" onclick="toggleFolder('0_9_3_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml" target="_self">framework</a></td><td class="desc"></td></tr>
<tr id="row_0_9_3_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_0_9_3_0_" class="arrow" onclick="toggleFolder('0_9_3_0_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml" target="_self">dataset</a></td><td class="desc"></td></tr>
<tr id="row_0_9_3_0_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span id="arr_0_9_3_0_0_" class="arrow" onclick="toggleFolder('0_9_3_0_0_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_cartesian_product_dataset.xhtml" target="_self">CartesianProductDataset</a></td><td class="desc">Implementation of a dataset representing all combinations of values of the input datasets </td></tr>
@@ -294,92 +294,81 @@
<tr id="row_0_9_3_1_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_0_9_3_1_" class="arrow" onclick="toggleFolder('0_9_3_1_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1detail.xhtml" target="_self">detail</a></td><td class="desc"></td></tr>
<tr id="row_0_9_3_1_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1detail_1_1_test_case_registrar.xhtml" target="_self">TestCaseRegistrar</a></td><td class="desc">Helper class to statically register a test case </td></tr>
<tr id="row_0_9_3_1_1_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1detail_1_1_test_suite_registrar.xhtml" target="_self">TestSuiteRegistrar</a></td><td class="desc">Helper class to statically begin and end a test suite </td></tr>
-<tr id="row_0_9_3_2_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_command_line_parser.xhtml" target="_self">CommandLineParser</a></td><td class="desc">Class to parse command line arguments </td></tr>
-<tr id="row_0_9_3_3_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_common_options.xhtml" target="_self">CommonOptions</a></td><td class="desc">Common command line options used to configure the framework </td></tr>
-<tr id="row_0_9_3_4_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase</a></td><td class="desc">Data test case class </td></tr>
-<tr id="row_0_9_3_5_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case_factory.xhtml" target="_self">DataTestCaseFactory</a></td><td class="desc">Implementation of a test case factory to create data test cases </td></tr>
-<tr id="row_0_9_3_6_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_enum_list_option.xhtml" target="_self">EnumListOption</a></td><td class="desc">Implementation of an option that accepts any number of values from a fixed set </td></tr>
-<tr id="row_0_9_3_7_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_enum_option.xhtml" target="_self">EnumOption</a></td><td class="desc">Implementation of a simple option that accepts a value from a fixed set </td></tr>
-<tr id="row_0_9_3_8_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_file_not_found.xhtml" target="_self">FileNotFound</a></td><td class="desc">Error class for when some external assets are missing </td></tr>
-<tr id="row_0_9_3_9_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_fixture.xhtml" target="_self">Fixture</a></td><td class="desc">Abstract fixture class </td></tr>
-<tr id="row_0_9_3_10_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_framework.xhtml" target="_self">Framework</a></td><td class="desc">Main framework class </td></tr>
-<tr id="row_0_9_3_11_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instrument.xhtml" target="_self">Instrument</a></td><td class="desc">Interface for classes that can be used to measure performance </td></tr>
-<tr id="row_0_9_3_12_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instruments_stats.xhtml" target="_self">InstrumentsStats</a></td><td class="desc">Generate common statistics for a set of measurements </td></tr>
-<tr id="row_0_9_3_13_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_j_s_o_n_printer.xhtml" target="_self">JSONPrinter</a></td><td class="desc">Implementation of a <a class="el" href="classarm__compute_1_1test_1_1framework_1_1_printer.xhtml">Printer</a> that produces JSON output </td></tr>
-<tr id="row_0_9_3_14_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_list_option.xhtml" target="_self">ListOption</a></td><td class="desc">Implementation of an option that accepts any number of values </td></tr>
-<tr id="row_0_9_3_15_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_mali_counter.xhtml" target="_self">MaliCounter</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instrument.xhtml" title="Interface for classes that can be used to measure performance. ">Instrument</a> implementation for mali hw counters </td></tr>
-<tr id="row_0_9_3_16_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_0_9_3_16_" class="arrow" onclick="toggleFolder('0_9_3_16_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_measurement.xhtml" target="_self">Measurement</a></td><td class="desc">Generic measurement that stores values as either double or long long int </td></tr>
-<tr id="row_0_9_3_16_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_measurement_1_1_value.xhtml" target="_self">Value</a></td><td class="desc"><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_measurement.xhtml" title="Generic measurement that stores values as either double or long long int. ">Measurement</a> value </td></tr>
-<tr id="row_0_9_3_17_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_open_c_l_memory_usage.xhtml" target="_self">OpenCLMemoryUsage</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instrument.xhtml" title="Interface for classes that can be used to measure performance. ">Instrument</a> collecting memory usage information for OpenCL </td></tr>
-<tr id="row_0_9_3_18_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_open_c_l_timer.xhtml" target="_self">OpenCLTimer</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instrument.xhtml" title="Interface for classes that can be used to measure performance. ">Instrument</a> creating measurements based on the information returned by clGetEventProfilingInfo for each OpenCL kernel executed </td></tr>
-<tr id="row_0_9_3_19_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_option.xhtml" target="_self">Option</a></td><td class="desc">Abstract base class for a command line option </td></tr>
-<tr id="row_0_9_3_20_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_p_m_u.xhtml" target="_self">PMU</a></td><td class="desc">Class provides access to CPU hardware counters </td></tr>
-<tr id="row_0_9_3_21_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_p_m_u_counter.xhtml" target="_self">PMUCounter</a></td><td class="desc">Implementation of an instrument to count CPU cycles </td></tr>
-<tr id="row_0_9_3_22_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_pretty_printer.xhtml" target="_self">PrettyPrinter</a></td><td class="desc">Implementation of a <a class="el" href="classarm__compute_1_1test_1_1framework_1_1_printer.xhtml">Printer</a> that produces human readable output </td></tr>
-<tr id="row_0_9_3_23_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_printer.xhtml" target="_self">Printer</a></td><td class="desc">Abstract printer class used by the <a class="el" href="classarm__compute_1_1test_1_1framework_1_1_framework.xhtml">Framework</a> to present output </td></tr>
-<tr id="row_0_9_3_24_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_profiler.xhtml" target="_self">Profiler</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_profiler.xhtml" title="Profiler class to collect benchmark numbers. ">Profiler</a> class to collect benchmark numbers </td></tr>
-<tr id="row_0_9_3_25_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_0_9_3_25_" class="arrow" onclick="toggleFolder('0_9_3_25_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_scheduler_timer.xhtml" target="_self">SchedulerTimer</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instrument.xhtml" title="Interface for classes that can be used to measure performance. ">Instrument</a> creating measurements based on the information returned by clGetEventProfilingInfo for each OpenCL kernel executed </td></tr>
-<tr id="row_0_9_3_25_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_scheduler_timer_1_1kernel__info.xhtml" target="_self">kernel_info</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> information </td></tr>
-<tr id="row_0_9_3_26_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_simple_option.xhtml" target="_self">SimpleOption</a></td><td class="desc">Implementation of an option that accepts a single value </td></tr>
-<tr id="row_0_9_3_27_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_simple_test_case_factory.xhtml" target="_self">SimpleTestCaseFactory</a></td><td class="desc">Implementation of a test case factory to create non-data test cases </td></tr>
-<tr id="row_0_9_3_28_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_case.xhtml" target="_self">TestCase</a></td><td class="desc">Abstract test case class </td></tr>
-<tr id="row_0_9_3_29_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_case_factory.xhtml" target="_self">TestCaseFactory</a></td><td class="desc">Abstract factory class to create test cases </td></tr>
-<tr id="row_0_9_3_30_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_error.xhtml" target="_self">TestError</a></td><td class="desc">Error class for failures during test execution </td></tr>
-<tr id="row_0_9_3_31_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_filter.xhtml" target="_self">TestFilter</a></td><td class="desc">Test filter class </td></tr>
-<tr id="row_0_9_3_32_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_test_info.xhtml" target="_self">TestInfo</a></td><td class="desc">Information about a test case </td></tr>
-<tr id="row_0_9_3_33_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_test_result.xhtml" target="_self">TestResult</a></td><td class="desc">Class to store results of a test </td></tr>
-<tr id="row_0_9_3_34_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_toggle_option.xhtml" target="_self">ToggleOption</a></td><td class="desc">Implementation of an option that can be either true or false </td></tr>
-<tr id="row_0_9_3_35_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_wall_clock_timer.xhtml" target="_self">WallClockTimer</a></td><td class="desc">Implementation of an instrument to measure elapsed wall-clock time in milliseconds </td></tr>
-<tr id="row_0_9_4_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_4_" class="arrow" onclick="toggleFolder('0_9_4_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1networks.xhtml" target="_self">networks</a></td><td class="desc"></td></tr>
-<tr id="row_0_9_4_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_alex_net_network.xhtml" target="_self">AlexNetNetwork</a></td><td class="desc">AlexNet model object </td></tr>
-<tr id="row_0_9_4_1_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_le_net5_network.xhtml" target="_self">LeNet5Network</a></td><td class="desc">Lenet5 model object </td></tr>
-<tr id="row_0_9_4_2_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_network.xhtml" target="_self">MobileNetNetwork</a></td><td class="desc">MobileNet model object </td></tr>
-<tr id="row_0_9_4_3_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml" target="_self">MobileNetV1Network</a></td><td class="desc">MobileNet model object </td></tr>
-<tr id="row_0_9_5_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_5_" class="arrow" onclick="toggleFolder('0_9_5_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1traits.xhtml" target="_self">traits</a></td><td class="desc"></td></tr>
-<tr id="row_0_9_5_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote.xhtml" target="_self">promote</a></td><td class="desc">Promote a type </td></tr>
-<tr id="row_0_9_5_1_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01float_01_4.xhtml" target="_self">promote< float ></a></td><td class="desc">Promote float to float </td></tr>
-<tr id="row_0_9_5_2_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01half_01_4.xhtml" target="_self">promote< half ></a></td><td class="desc">Promote half to half </td></tr>
-<tr id="row_0_9_5_3_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01int16__t_01_4.xhtml" target="_self">promote< int16_t ></a></td><td class="desc">Promote int16_t to int32_t </td></tr>
-<tr id="row_0_9_5_4_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01int32__t_01_4.xhtml" target="_self">promote< int32_t ></a></td><td class="desc">Promote int32_t to int64_t </td></tr>
-<tr id="row_0_9_5_5_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01int8__t_01_4.xhtml" target="_self">promote< int8_t ></a></td><td class="desc">Promote int8_t to int16_t </td></tr>
-<tr id="row_0_9_5_6_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint16__t_01_4.xhtml" target="_self">promote< uint16_t ></a></td><td class="desc">Promote uint16_t to uint32_t </td></tr>
-<tr id="row_0_9_5_7_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint32__t_01_4.xhtml" target="_self">promote< uint32_t ></a></td><td class="desc">Promote uint32_t to uint64_t </td></tr>
-<tr id="row_0_9_5_8_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint8__t_01_4.xhtml" target="_self">promote< uint8_t ></a></td><td class="desc">Promote uint8_t to uint16_t </td></tr>
-<tr id="row_0_9_6_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_6_" class="arrow" onclick="toggleFolder('0_9_6_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml" target="_self">validation</a></td><td class="desc"></td></tr>
-<tr id="row_0_9_6_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_absolute_tolerance.xhtml" target="_self">AbsoluteTolerance</a></td><td class="desc">Class reprensenting an absolute tolerance value </td></tr>
-<tr id="row_0_9_6_1_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare.xhtml" target="_self">compare</a></td><td class="desc"></td></tr>
-<tr id="row_0_9_6_2_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare_3_01_absolute_tolerance_3_01_u_01_4_01_4.xhtml" target="_self">compare< AbsoluteTolerance< U > ></a></td><td class="desc">Compare values with an absolute tolerance </td></tr>
-<tr id="row_0_9_6_3_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare_3_01_relative_tolerance_3_01_u_01_4_01_4.xhtml" target="_self">compare< RelativeTolerance< U > ></a></td><td class="desc">Compare values with a relative tolerance </td></tr>
-<tr id="row_0_9_6_4_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare__base.xhtml" target="_self">compare_base</a></td><td class="desc"></td></tr>
-<tr id="row_0_9_6_5_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1_harris_corners_parameters.xhtml" target="_self">HarrisCornersParameters</a></td><td class="desc">Parameters of Harris Corners algorithm </td></tr>
-<tr id="row_0_9_6_6_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1is__floating__point.xhtml" target="_self">is_floating_point</a></td><td class="desc"></td></tr>
-<tr id="row_0_9_6_7_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1is__floating__point_3_01half_01_4.xhtml" target="_self">is_floating_point< half ></a></td><td class="desc"></td></tr>
-<tr id="row_0_9_6_8_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_relative_tolerance.xhtml" target="_self">RelativeTolerance</a></td><td class="desc">Class reprensenting a relative tolerance value </td></tr>
-<tr id="row_0_9_7_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" target="_self">Accessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> objects </td></tr>
-<tr id="row_0_9_8_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_array_accessor.xhtml" target="_self">ArrayAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_array_accessor.xhtml" title="ArrayAccessor implementation for Array objects. ">ArrayAccessor</a> implementation for <a class="el" href="classarm__compute_1_1_array.xhtml">Array</a> objects </td></tr>
-<tr id="row_0_9_9_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_assets_library.xhtml" target="_self">AssetsLibrary</a></td><td class="desc">Factory class to create and fill tensors </td></tr>
-<tr id="row_0_9_10_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml" target="_self">CLAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> objects </td></tr>
-<tr id="row_0_9_11_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_array_accessor.xhtml" target="_self">CLArrayAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_array.xhtml">CLArray</a> objects </td></tr>
-<tr id="row_0_9_12_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_h_o_g_accessor.xhtml" target="_self">CLHOGAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_h_o_g.xhtml">CLHOG</a> objects </td></tr>
-<tr id="row_0_9_13_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_lut_accessor.xhtml" target="_self">CLLutAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_lut.xhtml">CLLut</a> objects </td></tr>
-<tr id="row_0_9_14_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_synthetize_function.xhtml" target="_self">CLSynthetizeFunction</a></td><td class="desc">This template synthetizes an <a class="el" href="classarm__compute_1_1_i_c_l_simple_function.xhtml" title="Basic interface for functions which have a single OpenCL kernel. ">ICLSimpleFunction</a> which runs the given kernel K </td></tr>
-<tr id="row_0_9_15_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_synthetize_function_with_zero_constant_border.xhtml" target="_self">CLSynthetizeFunctionWithZeroConstantBorder</a></td><td class="desc">As above but this also setups a Zero border on the input tensor of the specified bordersize </td></tr>
-<tr id="row_0_9_16_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1common__promoted__signed__type.xhtml" target="_self">common_promoted_signed_type</a></td><td class="desc">Find the signed promoted common type </td></tr>
-<tr id="row_0_9_17_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1common__promoted__unsigned__type.xhtml" target="_self">common_promoted_unsigned_type</a></td><td class="desc">Find the unsigned promoted common type </td></tr>
-<tr id="row_0_9_18_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_g_c_accessor.xhtml" target="_self">GCAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_g_c_tensor.xhtml">GCTensor</a> objects </td></tr>
-<tr id="row_0_9_19_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_h_o_g_accessor.xhtml" target="_self">HOGAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_h_o_g.xhtml">HOG</a> objects </td></tr>
-<tr id="row_0_9_20_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_i_accessor.xhtml" target="_self">IAccessor</a></td><td class="desc">Common interface to provide information and access to tensor like structures </td></tr>
-<tr id="row_0_9_21_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_i_array_accessor.xhtml" target="_self">IArrayAccessor</a></td><td class="desc">Common interface to provide information and access to array like structures </td></tr>
-<tr id="row_0_9_22_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_i_h_o_g_accessor.xhtml" target="_self">IHOGAccessor</a></td><td class="desc">Common interface to access <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> structure </td></tr>
-<tr id="row_0_9_23_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_i_lut_accessor.xhtml" target="_self">ILutAccessor</a></td><td class="desc">Common interface to provide information and access to <a class="el" href="classarm__compute_1_1_lut.xhtml" title="Basic implementation of the LUT interface. ">Lut</a> like structures </td></tr>
-<tr id="row_0_9_24_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_lut_accessor.xhtml" target="_self">LutAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_lut.xhtml">Lut</a> objects </td></tr>
-<tr id="row_0_9_25_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_n_e_synthetize_function.xhtml" target="_self">NESynthetizeFunction</a></td><td class="desc">This template synthetizes an <a class="el" href="classarm__compute_1_1_i_n_e_simple_function.xhtml" title="Basic interface for functions which have a single NEON kernel. ">INESimpleFunction</a> which runs the given kernel K </td></tr>
-<tr id="row_0_9_26_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_n_e_synthetize_function_with_zero_constant_border.xhtml" target="_self">NESynthetizeFunctionWithZeroConstantBorder</a></td><td class="desc">As above but this also setups a Zero border on the input tensor of the specified bordersize </td></tr>
-<tr id="row_0_9_27_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_padding_calculator.xhtml" target="_self">PaddingCalculator</a></td><td class="desc">Calculate required padding </td></tr>
-<tr id="row_0_9_28_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_raw_lut_accessor.xhtml" target="_self">RawLutAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for std::map-lut objects </td></tr>
-<tr id="row_0_9_29_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml" target="_self">RawTensor</a></td><td class="desc">Subclass of <a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" title="Simple tensor object that stores elements in a consecutive chunk of memory. ">SimpleTensor</a> using uint8_t as value type </td></tr>
-<tr id="row_0_9_30_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" target="_self">SimpleTensor</a></td><td class="desc">Simple tensor object that stores elements in a consecutive chunk of memory </td></tr>
-<tr id="row_0_9_31_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_tensor_cache.xhtml" target="_self">TensorCache</a></td><td class="desc">Stores <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> categorised by the image they are created from including name, format and channel </td></tr>
+<tr id="row_0_9_3_2_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_common_options.xhtml" target="_self">CommonOptions</a></td><td class="desc">Common command line options used to configure the framework </td></tr>
+<tr id="row_0_9_3_3_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase</a></td><td class="desc">Data test case class </td></tr>
+<tr id="row_0_9_3_4_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case_factory.xhtml" target="_self">DataTestCaseFactory</a></td><td class="desc">Implementation of a test case factory to create data test cases </td></tr>
+<tr id="row_0_9_3_5_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_file_not_found.xhtml" target="_self">FileNotFound</a></td><td class="desc">Error class for when some external assets are missing </td></tr>
+<tr id="row_0_9_3_6_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_fixture.xhtml" target="_self">Fixture</a></td><td class="desc">Abstract fixture class </td></tr>
+<tr id="row_0_9_3_7_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_framework.xhtml" target="_self">Framework</a></td><td class="desc">Main framework class </td></tr>
+<tr id="row_0_9_3_8_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instrument.xhtml" target="_self">Instrument</a></td><td class="desc">Interface for classes that can be used to measure performance </td></tr>
+<tr id="row_0_9_3_9_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instruments_stats.xhtml" target="_self">InstrumentsStats</a></td><td class="desc">Generate common statistics for a set of measurements </td></tr>
+<tr id="row_0_9_3_10_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_j_s_o_n_printer.xhtml" target="_self">JSONPrinter</a></td><td class="desc">Implementation of a <a class="el" href="classarm__compute_1_1test_1_1framework_1_1_printer.xhtml">Printer</a> that produces JSON output </td></tr>
+<tr id="row_0_9_3_11_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_mali_counter.xhtml" target="_self">MaliCounter</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instrument.xhtml" title="Interface for classes that can be used to measure performance. ">Instrument</a> implementation for mali hw counters </td></tr>
+<tr id="row_0_9_3_12_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_0_9_3_12_" class="arrow" onclick="toggleFolder('0_9_3_12_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_measurement.xhtml" target="_self">Measurement</a></td><td class="desc">Generic measurement that stores values as either double or long long int </td></tr>
+<tr id="row_0_9_3_12_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_measurement_1_1_value.xhtml" target="_self">Value</a></td><td class="desc"><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_measurement.xhtml" title="Generic measurement that stores values as either double or long long int. ">Measurement</a> value </td></tr>
+<tr id="row_0_9_3_13_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_open_c_l_memory_usage.xhtml" target="_self">OpenCLMemoryUsage</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instrument.xhtml" title="Interface for classes that can be used to measure performance. ">Instrument</a> collecting memory usage information for OpenCL </td></tr>
+<tr id="row_0_9_3_14_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_open_c_l_timer.xhtml" target="_self">OpenCLTimer</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instrument.xhtml" title="Interface for classes that can be used to measure performance. ">Instrument</a> creating measurements based on the information returned by clGetEventProfilingInfo for each OpenCL kernel executed </td></tr>
+<tr id="row_0_9_3_15_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_p_m_u.xhtml" target="_self">PMU</a></td><td class="desc">Class provides access to CPU hardware counters </td></tr>
+<tr id="row_0_9_3_16_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_p_m_u_counter.xhtml" target="_self">PMUCounter</a></td><td class="desc">Implementation of an instrument to count CPU cycles </td></tr>
+<tr id="row_0_9_3_17_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_pretty_printer.xhtml" target="_self">PrettyPrinter</a></td><td class="desc">Implementation of a <a class="el" href="classarm__compute_1_1test_1_1framework_1_1_printer.xhtml">Printer</a> that produces human readable output </td></tr>
+<tr id="row_0_9_3_18_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_printer.xhtml" target="_self">Printer</a></td><td class="desc">Abstract printer class used by the <a class="el" href="classarm__compute_1_1test_1_1framework_1_1_framework.xhtml">Framework</a> to present output </td></tr>
+<tr id="row_0_9_3_19_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_profiler.xhtml" target="_self">Profiler</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_profiler.xhtml" title="Profiler class to collect benchmark numbers. ">Profiler</a> class to collect benchmark numbers </td></tr>
+<tr id="row_0_9_3_20_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_0_9_3_20_" class="arrow" onclick="toggleFolder('0_9_3_20_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_scheduler_timer.xhtml" target="_self">SchedulerTimer</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_instrument.xhtml" title="Interface for classes that can be used to measure performance. ">Instrument</a> creating measurements based on the information returned by clGetEventProfilingInfo for each OpenCL kernel executed </td></tr>
+<tr id="row_0_9_3_20_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_scheduler_timer_1_1kernel__info.xhtml" target="_self">kernel_info</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> information </td></tr>
+<tr id="row_0_9_3_21_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_simple_test_case_factory.xhtml" target="_self">SimpleTestCaseFactory</a></td><td class="desc">Implementation of a test case factory to create non-data test cases </td></tr>
+<tr id="row_0_9_3_22_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_case.xhtml" target="_self">TestCase</a></td><td class="desc">Abstract test case class </td></tr>
+<tr id="row_0_9_3_23_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_case_factory.xhtml" target="_self">TestCaseFactory</a></td><td class="desc">Abstract factory class to create test cases </td></tr>
+<tr id="row_0_9_3_24_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_error.xhtml" target="_self">TestError</a></td><td class="desc">Error class for failures during test execution </td></tr>
+<tr id="row_0_9_3_25_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_filter.xhtml" target="_self">TestFilter</a></td><td class="desc">Test filter class </td></tr>
+<tr id="row_0_9_3_26_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_test_info.xhtml" target="_self">TestInfo</a></td><td class="desc">Information about a test case </td></tr>
+<tr id="row_0_9_3_27_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_test_result.xhtml" target="_self">TestResult</a></td><td class="desc">Class to store results of a test </td></tr>
+<tr id="row_0_9_3_28_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_wall_clock_timer.xhtml" target="_self">WallClockTimer</a></td><td class="desc">Implementation of an instrument to measure elapsed wall-clock time in milliseconds </td></tr>
+<tr id="row_0_9_4_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_4_" class="arrow" onclick="toggleFolder('0_9_4_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1traits.xhtml" target="_self">traits</a></td><td class="desc"></td></tr>
+<tr id="row_0_9_4_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote.xhtml" target="_self">promote</a></td><td class="desc">Promote a type </td></tr>
+<tr id="row_0_9_4_1_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01float_01_4.xhtml" target="_self">promote< float ></a></td><td class="desc">Promote float to float </td></tr>
+<tr id="row_0_9_4_2_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01half_01_4.xhtml" target="_self">promote< half ></a></td><td class="desc">Promote half to half </td></tr>
+<tr id="row_0_9_4_3_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01int16__t_01_4.xhtml" target="_self">promote< int16_t ></a></td><td class="desc">Promote int16_t to int32_t </td></tr>
+<tr id="row_0_9_4_4_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01int32__t_01_4.xhtml" target="_self">promote< int32_t ></a></td><td class="desc">Promote int32_t to int64_t </td></tr>
+<tr id="row_0_9_4_5_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01int8__t_01_4.xhtml" target="_self">promote< int8_t ></a></td><td class="desc">Promote int8_t to int16_t </td></tr>
+<tr id="row_0_9_4_6_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint16__t_01_4.xhtml" target="_self">promote< uint16_t ></a></td><td class="desc">Promote uint16_t to uint32_t </td></tr>
+<tr id="row_0_9_4_7_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint32__t_01_4.xhtml" target="_self">promote< uint32_t ></a></td><td class="desc">Promote uint32_t to uint64_t </td></tr>
+<tr id="row_0_9_4_8_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint8__t_01_4.xhtml" target="_self">promote< uint8_t ></a></td><td class="desc">Promote uint8_t to uint16_t </td></tr>
+<tr id="row_0_9_5_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_9_5_" class="arrow" onclick="toggleFolder('0_9_5_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml" target="_self">validation</a></td><td class="desc"></td></tr>
+<tr id="row_0_9_5_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_absolute_tolerance.xhtml" target="_self">AbsoluteTolerance</a></td><td class="desc">Class reprensenting an absolute tolerance value </td></tr>
+<tr id="row_0_9_5_1_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1_canny_edge_parameters.xhtml" target="_self">CannyEdgeParameters</a></td><td class="desc">Parameters of Canny edge algorithm </td></tr>
+<tr id="row_0_9_5_2_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare.xhtml" target="_self">compare</a></td><td class="desc"></td></tr>
+<tr id="row_0_9_5_3_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare_3_01_absolute_tolerance_3_01_u_01_4_01_4.xhtml" target="_self">compare< AbsoluteTolerance< U > ></a></td><td class="desc">Compare values with an absolute tolerance </td></tr>
+<tr id="row_0_9_5_4_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare_3_01_relative_tolerance_3_01_u_01_4_01_4.xhtml" target="_self">compare< RelativeTolerance< U > ></a></td><td class="desc">Compare values with a relative tolerance </td></tr>
+<tr id="row_0_9_5_5_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare__base.xhtml" target="_self">compare_base</a></td><td class="desc"></td></tr>
+<tr id="row_0_9_5_6_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1_harris_corners_parameters.xhtml" target="_self">HarrisCornersParameters</a></td><td class="desc">Parameters of Harris Corners algorithm </td></tr>
+<tr id="row_0_9_5_7_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1is__floating__point.xhtml" target="_self">is_floating_point</a></td><td class="desc"></td></tr>
+<tr id="row_0_9_5_8_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1is__floating__point_3_01half_01_4.xhtml" target="_self">is_floating_point< half ></a></td><td class="desc"></td></tr>
+<tr id="row_0_9_5_9_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_relative_tolerance.xhtml" target="_self">RelativeTolerance</a></td><td class="desc">Class reprensenting a relative tolerance value </td></tr>
+<tr id="row_0_9_6_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" target="_self">Accessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> objects </td></tr>
+<tr id="row_0_9_7_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_array_accessor.xhtml" target="_self">ArrayAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_array_accessor.xhtml" title="ArrayAccessor implementation for Array objects. ">ArrayAccessor</a> implementation for <a class="el" href="classarm__compute_1_1_array.xhtml">Array</a> objects </td></tr>
+<tr id="row_0_9_8_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_assets_library.xhtml" target="_self">AssetsLibrary</a></td><td class="desc">Factory class to create and fill tensors </td></tr>
+<tr id="row_0_9_9_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml" target="_self">CLAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> objects </td></tr>
+<tr id="row_0_9_10_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_array_accessor.xhtml" target="_self">CLArrayAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_array.xhtml">CLArray</a> objects </td></tr>
+<tr id="row_0_9_11_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_h_o_g_accessor.xhtml" target="_self">CLHOGAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_h_o_g.xhtml">CLHOG</a> objects </td></tr>
+<tr id="row_0_9_12_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_lut_accessor.xhtml" target="_self">CLLutAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_lut.xhtml">CLLut</a> objects </td></tr>
+<tr id="row_0_9_13_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_synthetize_function.xhtml" target="_self">CLSynthetizeFunction</a></td><td class="desc">This template synthetizes an <a class="el" href="classarm__compute_1_1_i_c_l_simple_function.xhtml" title="Basic interface for functions which have a single OpenCL kernel. ">ICLSimpleFunction</a> which runs the given kernel K </td></tr>
+<tr id="row_0_9_14_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_synthetize_function_with_zero_constant_border.xhtml" target="_self">CLSynthetizeFunctionWithZeroConstantBorder</a></td><td class="desc">As above but this also setups a Zero border on the input tensor of the specified bordersize </td></tr>
+<tr id="row_0_9_15_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1common__promoted__signed__type.xhtml" target="_self">common_promoted_signed_type</a></td><td class="desc">Find the signed promoted common type </td></tr>
+<tr id="row_0_9_16_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1common__promoted__unsigned__type.xhtml" target="_self">common_promoted_unsigned_type</a></td><td class="desc">Find the unsigned promoted common type </td></tr>
+<tr id="row_0_9_17_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_g_c_accessor.xhtml" target="_self">GCAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_g_c_tensor.xhtml">GCTensor</a> objects </td></tr>
+<tr id="row_0_9_18_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_h_o_g_accessor.xhtml" target="_self">HOGAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_h_o_g.xhtml">HOG</a> objects </td></tr>
+<tr id="row_0_9_19_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_i_accessor.xhtml" target="_self">IAccessor</a></td><td class="desc">Common interface to provide information and access to tensor like structures </td></tr>
+<tr id="row_0_9_20_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_i_array_accessor.xhtml" target="_self">IArrayAccessor</a></td><td class="desc">Common interface to provide information and access to array like structures </td></tr>
+<tr id="row_0_9_21_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_i_h_o_g_accessor.xhtml" target="_self">IHOGAccessor</a></td><td class="desc">Common interface to access <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> structure </td></tr>
+<tr id="row_0_9_22_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_i_lut_accessor.xhtml" target="_self">ILutAccessor</a></td><td class="desc">Common interface to provide information and access to <a class="el" href="classarm__compute_1_1_lut.xhtml" title="Basic implementation of the LUT interface. ">Lut</a> like structures </td></tr>
+<tr id="row_0_9_23_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_lut_accessor.xhtml" target="_self">LutAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_lut.xhtml">Lut</a> objects </td></tr>
+<tr id="row_0_9_24_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_n_e_synthetize_function.xhtml" target="_self">NESynthetizeFunction</a></td><td class="desc">This template synthetizes an <a class="el" href="classarm__compute_1_1_i_n_e_simple_function.xhtml" title="Basic interface for functions which have a single NEON kernel. ">INESimpleFunction</a> which runs the given kernel K </td></tr>
+<tr id="row_0_9_25_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_n_e_synthetize_function_with_zero_constant_border.xhtml" target="_self">NESynthetizeFunctionWithZeroConstantBorder</a></td><td class="desc">As above but this also setups a Zero border on the input tensor of the specified bordersize </td></tr>
+<tr id="row_0_9_26_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_padding_calculator.xhtml" target="_self">PaddingCalculator</a></td><td class="desc">Calculate required padding </td></tr>
+<tr id="row_0_9_27_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_raw_lut_accessor.xhtml" target="_self">RawLutAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for std::map-lut objects </td></tr>
+<tr id="row_0_9_28_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml" target="_self">RawTensor</a></td><td class="desc">Subclass of <a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" title="Simple tensor object that stores elements in a consecutive chunk of memory. ">SimpleTensor</a> using uint8_t as value type </td></tr>
+<tr id="row_0_9_29_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" target="_self">SimpleTensor</a></td><td class="desc">Simple tensor object that stores elements in a consecutive chunk of memory </td></tr>
+<tr id="row_0_9_30_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_tensor_cache.xhtml" target="_self">TensorCache</a></td><td class="desc">Stores <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> categorised by the image they are created from including name, format and channel </td></tr>
<tr id="row_0_10_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_10_" class="arrow" onclick="toggleFolder('0_10_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1traits.xhtml" target="_self">traits</a></td><td class="desc"></td></tr>
<tr id="row_0_10_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1traits_1_1is__contained.xhtml" target="_self">is_contained</a></td><td class="desc">Check if a type T is contained in a tuple Tuple of types </td></tr>
<tr id="row_0_10_1_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1traits_1_1is__contained_3_01_t_00_01std_1_1tuple_3_01_t_00_01_ts_8_8_8_01_4_01_4.xhtml" target="_self">is_contained< T, std::tuple< T, Ts... > ></a></td><td class="desc"></td></tr>
@@ -387,6 +376,8 @@
<tr id="row_0_10_3_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1traits_1_1is__contained_3_01_t_00_01std_1_1tuple_3_4_01_4.xhtml" target="_self">is_contained< T, std::tuple<> ></a></td><td class="desc"></td></tr>
<tr id="row_0_11_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_11_" class="arrow" onclick="toggleFolder('0_11_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1tuners.xhtml" target="_self">tuners</a></td><td class="desc"></td></tr>
<tr id="row_0_11_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1tuners_1_1_bifrost_tuner.xhtml" target="_self">BifrostTuner</a></td><td class="desc">Bifrost based OpenCL tuner implementation </td></tr>
+<tr id="row_0_11_1_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1tuners_1_1_midgard_tuner.xhtml" target="_self">MidgardTuner</a></td><td class="desc">Midgard based OpenCL tuner implementation </td></tr>
+<tr id="row_0_11_2_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1tuners_1_1_tuner_factory.xhtml" target="_self">TunerFactory</a></td><td class="desc">Tuner factory class </td></tr>
<tr id="row_0_12_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_12_" class="arrow" onclick="toggleFolder('0_12_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1utility.xhtml" target="_self">utility</a></td><td class="desc"></td></tr>
<tr id="row_0_13_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_13_" class="arrow" onclick="toggleFolder('0_13_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1utils.xhtml" target="_self">utils</a></td><td class="desc"></td></tr>
<tr id="row_0_13_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_13_0_" class="arrow" onclick="toggleFolder('0_13_0_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1utils_1_1iterable.xhtml" target="_self">iterable</a></td><td class="desc"></td></tr>
@@ -395,9 +386,24 @@
<tr id="row_0_13_1_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_0_13_1_0_" class="arrow" onclick="toggleFolder('0_13_1_0_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1utils_1_1signal_1_1detail.xhtml" target="_self">detail</a></td><td class="desc"></td></tr>
<tr id="row_0_13_1_0_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1signal_1_1detail_1_1_signal_impl.xhtml" target="_self">SignalImpl</a></td><td class="desc">Base signal class </td></tr>
<tr id="row_0_13_1_0_1_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1signal_1_1detail_1_1_signal_impl_3_01_return_type_07_args_8_8_8_08_4.xhtml" target="_self">SignalImpl< ReturnType(Args...)></a></td><td class="desc">Signal class function specialization </td></tr>
-<tr id="row_0_13_2_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_example.xhtml" target="_self">Example</a></td><td class="desc">Abstract <a class="el" href="classarm__compute_1_1utils_1_1_example.xhtml" title="Abstract Example class. ">Example</a> class </td></tr>
-<tr id="row_0_13_3_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_n_p_y_loader.xhtml" target="_self">NPYLoader</a></td><td class="desc">Numpy data loader </td></tr>
-<tr id="row_0_13_4_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml" target="_self">PPMLoader</a></td><td class="desc">Class to load the content of a PPM file into an <a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> </td></tr>
+<tr id="row_0_13_2_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_command_line_parser.xhtml" target="_self">CommandLineParser</a></td><td class="desc">Class to parse command line arguments </td></tr>
+<tr id="row_0_13_3_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_common_graph_options.xhtml" target="_self">CommonGraphOptions</a></td><td class="desc">Common command line options used to configure the graph examples </td></tr>
+<tr id="row_0_13_4_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1utils_1_1_common_graph_params.xhtml" target="_self">CommonGraphParams</a></td><td class="desc">Structure holding all the common graph parameters </td></tr>
+<tr id="row_0_13_5_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_enum_list_option.xhtml" target="_self">EnumListOption</a></td><td class="desc">Implementation of an option that accepts any number of values from a fixed set </td></tr>
+<tr id="row_0_13_6_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_enum_option.xhtml" target="_self">EnumOption</a></td><td class="desc">Implementation of a simple option that accepts a value from a fixed set </td></tr>
+<tr id="row_0_13_7_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_example.xhtml" target="_self">Example</a></td><td class="desc">Abstract <a class="el" href="classarm__compute_1_1utils_1_1_example.xhtml" title="Abstract Example class. ">Example</a> class </td></tr>
+<tr id="row_0_13_8_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_file_image_feeder.xhtml" target="_self">FileImageFeeder</a></td><td class="desc">File <a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> feeder concrete implementation </td></tr>
+<tr id="row_0_13_9_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_i_image_data_feeder.xhtml" target="_self">IImageDataFeeder</a></td><td class="desc"><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> feeder interface </td></tr>
+<tr id="row_0_13_10_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_i_image_loader.xhtml" target="_self">IImageLoader</a></td><td class="desc"><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> loader interface </td></tr>
+<tr id="row_0_13_11_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_image_loader_factory.xhtml" target="_self">ImageLoaderFactory</a></td><td class="desc">Factory for generating appropriate image loader </td></tr>
+<tr id="row_0_13_12_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_j_p_e_g_loader.xhtml" target="_self">JPEGLoader</a></td><td class="desc">Class to load the content of a JPEG file into an <a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> </td></tr>
+<tr id="row_0_13_13_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_list_option.xhtml" target="_self">ListOption</a></td><td class="desc">Implementation of an option that accepts any number of values </td></tr>
+<tr id="row_0_13_14_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_memory_image_feeder.xhtml" target="_self">MemoryImageFeeder</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> <a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> feeder concrete implementation </td></tr>
+<tr id="row_0_13_15_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_n_p_y_loader.xhtml" target="_self">NPYLoader</a></td><td class="desc">Numpy data loader </td></tr>
+<tr id="row_0_13_16_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_option.xhtml" target="_self">Option</a></td><td class="desc">Abstract base class for a command line option </td></tr>
+<tr id="row_0_13_17_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml" target="_self">PPMLoader</a></td><td class="desc">PPM <a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> loader concrete implementation </td></tr>
+<tr id="row_0_13_18_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_simple_option.xhtml" target="_self">SimpleOption</a></td><td class="desc">Implementation of an option that accepts a single value </td></tr>
+<tr id="row_0_13_19_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1_toggle_option.xhtml" target="_self">ToggleOption</a></td><td class="desc">Implementation of an option that can be either true or false </td></tr>
<tr id="row_0_14_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_14_" class="arrow" onclick="toggleFolder('0_14_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1wrapper.xhtml" target="_self">wrapper</a></td><td class="desc"></td></tr>
<tr id="row_0_14_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_0_14_0_" class="arrow" onclick="toggleFolder('0_14_0_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacearm__compute_1_1wrapper_1_1traits.xhtml" target="_self">traits</a></td><td class="desc"></td></tr>
<tr id="row_0_14_0_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1wrapper_1_1traits_1_1neon__vector.xhtml" target="_self">neon_vector</a></td><td class="desc">Create the appropriate NEON vector given its type and size </td></tr>
@@ -412,643 +418,659 @@
<tr id="row_0_21_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml" target="_self">ActivationLayerInfo</a></td><td class="desc">Activation Layer Information class </td></tr>
<tr id="row_0_22_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_allocator.xhtml" target="_self">Allocator</a></td><td class="desc">Default malloc allocator implementation </td></tr>
<tr id="row_0_23_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_array.xhtml" target="_self">Array</a></td><td class="desc">Basic implementation of the <a class="el" href="classarm__compute_1_1_i_array.xhtml" title="Array of type T. ">IArray</a> interface which allocates a static number of T values </td></tr>
-<tr id="row_0_24_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_assembly_kernel_glue.xhtml" target="_self">AssemblyKernelGlue</a></td><td class="desc">Assembly kernel glue </td></tr>
-<tr id="row_0_25_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_blob_lifetime_manager.xhtml" target="_self">BlobLifetimeManager</a></td><td class="desc">Concrete class that tracks the lifetime of registered tensors and calculates the systems memory requirements in terms of blobs </td></tr>
-<tr id="row_0_26_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_blob_memory_pool.xhtml" target="_self">BlobMemoryPool</a></td><td class="desc">Blob memory pool </td></tr>
-<tr id="row_0_27_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_border_size.xhtml" target="_self">BorderSize</a></td><td class="desc">Container for 2D border size </td></tr>
-<tr id="row_0_28_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_absolute_difference.xhtml" target="_self">CLAbsoluteDifference</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_absolute_difference_kernel.xhtml">CLAbsoluteDifferenceKernel</a> </td></tr>
-<tr id="row_0_29_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_absolute_difference_kernel.xhtml" target="_self">CLAbsoluteDifferenceKernel</a></td><td class="desc">Interface for the absolute difference kernel </td></tr>
-<tr id="row_0_30_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate.xhtml" target="_self">CLAccumulate</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml">CLAccumulateKernel</a> </td></tr>
-<tr id="row_0_31_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml" target="_self">CLAccumulateKernel</a></td><td class="desc">Interface for the accumulate kernel </td></tr>
-<tr id="row_0_32_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_squared.xhtml" target="_self">CLAccumulateSquared</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_accumulate_squared_kernel.xhtml">CLAccumulateSquaredKernel</a> </td></tr>
-<tr id="row_0_33_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_squared_kernel.xhtml" target="_self">CLAccumulateSquaredKernel</a></td><td class="desc">Interface for the accumulate squared kernel </td></tr>
-<tr id="row_0_34_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_weighted.xhtml" target="_self">CLAccumulateWeighted</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml">CLAccumulateWeightedKernel</a> </td></tr>
-<tr id="row_0_35_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml" target="_self">CLAccumulateWeightedKernel</a></td><td class="desc">Interface for the accumulate weighted kernel </td></tr>
-<tr id="row_0_36_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_activation_layer.xhtml" target="_self">CLActivationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_activation_layer_kernel.xhtml">CLActivationLayerKernel</a> </td></tr>
-<tr id="row_0_37_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_activation_layer_kernel.xhtml" target="_self">CLActivationLayerKernel</a></td><td class="desc">Interface for the activation layer kernel </td></tr>
-<tr id="row_0_38_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_addition.xhtml" target="_self">CLArithmeticAddition</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_arithmetic_addition_kernel.xhtml">CLArithmeticAdditionKernel</a> </td></tr>
-<tr id="row_0_39_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_addition_kernel.xhtml" target="_self">CLArithmeticAdditionKernel</a></td><td class="desc">Interface for the arithmetic addition kernel </td></tr>
-<tr id="row_0_40_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_subtraction.xhtml" target="_self">CLArithmeticSubtraction</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_arithmetic_subtraction_kernel.xhtml">CLArithmeticSubtractionKernel</a> </td></tr>
-<tr id="row_0_41_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_subtraction_kernel.xhtml" target="_self">CLArithmeticSubtractionKernel</a></td><td class="desc">Interface for the arithmetic subtraction kernel </td></tr>
-<tr id="row_0_42_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_array.xhtml" target="_self">CLArray</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_c_l_array.xhtml" title="CLArray implementation. ">CLArray</a> implementation </td></tr>
-<tr id="row_0_43_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml" target="_self">CLBatchNormalizationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_normalization_layer_kernel.xhtml">CLNormalizationLayerKernel</a> and simulate a batch normalization layer </td></tr>
-<tr id="row_0_44_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer_kernel.xhtml" target="_self">CLBatchNormalizationLayerKernel</a></td><td class="desc">Interface for the BatchNormalization layer kernel </td></tr>
-<tr id="row_0_45_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_and.xhtml" target="_self">CLBitwiseAnd</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_and_kernel.xhtml">CLBitwiseAndKernel</a> </td></tr>
-<tr id="row_0_46_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_and_kernel.xhtml" target="_self">CLBitwiseAndKernel</a></td><td class="desc">Interface for the bitwise AND operation kernel </td></tr>
-<tr id="row_0_47_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_not.xhtml" target="_self">CLBitwiseNot</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_not_kernel.xhtml">CLBitwiseNotKernel</a> </td></tr>
-<tr id="row_0_48_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_not_kernel.xhtml" target="_self">CLBitwiseNotKernel</a></td><td class="desc">Interface for the bitwise NOT operation kernel </td></tr>
-<tr id="row_0_49_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_or.xhtml" target="_self">CLBitwiseOr</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_or_kernel.xhtml">CLBitwiseOrKernel</a> </td></tr>
-<tr id="row_0_50_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_or_kernel.xhtml" target="_self">CLBitwiseOrKernel</a></td><td class="desc">Interface for the bitwise OR operation kernel </td></tr>
-<tr id="row_0_51_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_xor.xhtml" target="_self">CLBitwiseXor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_xor_kernel.xhtml">CLBitwiseXorKernel</a> </td></tr>
-<tr id="row_0_52_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_xor_kernel.xhtml" target="_self">CLBitwiseXorKernel</a></td><td class="desc">Interface for the bitwise XOR operation kernel </td></tr>
-<tr id="row_0_53_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_box3x3.xhtml" target="_self">CLBox3x3</a></td><td class="desc">Basic function to execute box filter 3x3 </td></tr>
-<tr id="row_0_54_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_box3x3_kernel.xhtml" target="_self">CLBox3x3Kernel</a></td><td class="desc">Interface for the box 3x3 filter kernel </td></tr>
-<tr id="row_0_55_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_buffer_allocator.xhtml" target="_self">CLBufferAllocator</a></td><td class="desc">Default OpenCL cl buffer allocator implementation </td></tr>
-<tr id="row_0_56_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_buffer_memory_region.xhtml" target="_self">CLBufferMemoryRegion</a></td><td class="desc">OpenCL buffer memory region implementation </td></tr>
-<tr id="row_0_57_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_build_options.xhtml" target="_self">CLBuildOptions</a></td><td class="desc">Build options </td></tr>
-<tr id="row_0_58_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml" target="_self">CLCannyEdge</a></td><td class="desc">Basic function to execute canny edge on OpenCL </td></tr>
-<tr id="row_0_59_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_combine.xhtml" target="_self">CLChannelCombine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_channel_combine_kernel.xhtml">CLChannelCombineKernel</a> to perform channel combination </td></tr>
-<tr id="row_0_60_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_combine_kernel.xhtml" target="_self">CLChannelCombineKernel</a></td><td class="desc">Interface for the channel combine kernel </td></tr>
-<tr id="row_0_61_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_extract.xhtml" target="_self">CLChannelExtract</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_channel_extract_kernel.xhtml">CLChannelExtractKernel</a> to perform channel extraction </td></tr>
-<tr id="row_0_62_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_extract_kernel.xhtml" target="_self">CLChannelExtractKernel</a></td><td class="desc">Interface for the channel extract kernel </td></tr>
-<tr id="row_0_63_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_shuffle_layer.xhtml" target="_self">CLChannelShuffleLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_channel_shuffle_layer_kernel.xhtml">CLChannelShuffleLayerKernel</a> </td></tr>
-<tr id="row_0_64_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_shuffle_layer_kernel.xhtml" target="_self">CLChannelShuffleLayerKernel</a></td><td class="desc">Interface for the channel shuffle kernel </td></tr>
-<tr id="row_0_65_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_coarse_s_v_m_memory_region.xhtml" target="_self">CLCoarseSVMMemoryRegion</a></td><td class="desc">OpenCL coarse-grain SVM memory region implementation </td></tr>
-<tr id="row_0_66_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_coefficient_table.xhtml" target="_self">CLCoefficientTable</a></td><td class="desc">Structure for storing Spatial Gradient Matrix and the minimum eigenvalue for each keypoint </td></tr>
-<tr id="row_0_67_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_col2_im_kernel.xhtml" target="_self">CLCol2ImKernel</a></td><td class="desc">Interface for the col2im reshaping kernel </td></tr>
-<tr id="row_0_68_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_color_convert.xhtml" target="_self">CLColorConvert</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_color_convert_kernel.xhtml">CLColorConvertKernel</a> </td></tr>
-<tr id="row_0_69_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_color_convert_kernel.xhtml" target="_self">CLColorConvertKernel</a></td><td class="desc">Interface for the color convert kernel </td></tr>
-<tr id="row_0_70_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convert_fully_connected_weights.xhtml" target="_self">CLConvertFullyConnectedWeights</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_convert_fully_connected_weights_kernel.xhtml">CLConvertFullyConnectedWeightsKernel</a> </td></tr>
-<tr id="row_0_71_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convert_fully_connected_weights_kernel.xhtml" target="_self">CLConvertFullyConnectedWeightsKernel</a></td><td class="desc">Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa </td></tr>
-<tr id="row_0_72_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution3x3.xhtml" target="_self">CLConvolution3x3</a></td><td class="desc">Basic function to execute convolution of size 3x3 </td></tr>
-<tr id="row_0_73_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_kernel.xhtml" target="_self">CLConvolutionKernel</a></td><td class="desc">Interface for the kernel to run an arbitrary size convolution on a tensor </td></tr>
-<tr id="row_0_74_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml" target="_self">CLConvolutionLayer</a></td><td class="desc">Basic function to compute the convolution layer </td></tr>
-<tr id="row_0_75_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_layer_reshape_weights.xhtml" target="_self">CLConvolutionLayerReshapeWeights</a></td><td class="desc">Function to reshape and transpose the weights </td></tr>
-<tr id="row_0_76_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_rectangle.xhtml" target="_self">CLConvolutionRectangle</a></td><td class="desc">Basic function to execute non-square convolution </td></tr>
-<tr id="row_0_77_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_rectangle_kernel.xhtml" target="_self">CLConvolutionRectangleKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the running convolution on a rectangle matrix </td></tr>
-<tr id="row_0_78_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_square.xhtml" target="_self">CLConvolutionSquare</a></td><td class="desc">Basic function to execute square convolution.Currently it supports 5x5, 7x7, 9x9 </td></tr>
-<tr id="row_0_79_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_copy.xhtml" target="_self">CLCopy</a></td><td class="desc"></td></tr>
-<tr id="row_0_80_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_copy_kernel.xhtml" target="_self">CLCopyKernel</a></td><td class="desc">OpenCL kernel to perform a copy between two tensors </td></tr>
-<tr id="row_0_81_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_copy_to_array_kernel.xhtml" target="_self">CLCopyToArrayKernel</a></td><td class="desc">CL kernel to copy keypoints information to ICLKeyPointArray and counts the number of key points </td></tr>
-<tr id="row_0_82_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_deconvolution_layer.xhtml" target="_self">CLDeconvolutionLayer</a></td><td class="desc">Function to run the deconvolution layer </td></tr>
-<tr id="row_0_83_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_deconvolution_layer_upsample.xhtml" target="_self">CLDeconvolutionLayerUpsample</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_deconvolution_layer_upsample_kernel.xhtml">CLDeconvolutionLayerUpsampleKernel</a> </td></tr>
-<tr id="row_0_84_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_deconvolution_layer_upsample_kernel.xhtml" target="_self">CLDeconvolutionLayerUpsampleKernel</a></td><td class="desc">Interface for the Deconvolution layer kernel on OpenCL </td></tr>
-<tr id="row_0_85_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depth_concatenate_layer.xhtml" target="_self">CLDepthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
-<tr id="row_0_86_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depth_concatenate_layer_kernel.xhtml" target="_self">CLDepthConcatenateLayerKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
-<tr id="row_0_87_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depth_convert_layer.xhtml" target="_self">CLDepthConvertLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_depth_convert_layer_kernel.xhtml">CLDepthConvertLayerKernel</a> </td></tr>
-<tr id="row_0_88_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depth_convert_layer_kernel.xhtml" target="_self">CLDepthConvertLayerKernel</a></td><td class="desc">Interface for the depth conversion kernel </td></tr>
-<tr id="row_0_89_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer.xhtml" target="_self">CLDepthwiseConvolutionLayer</a></td><td class="desc">Basic function to execute a generic depthwise convolution </td></tr>
-<tr id="row_0_90_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml" target="_self">CLDepthwiseConvolutionLayer3x3</a></td><td class="desc">Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC) </td></tr>
-<tr id="row_0_91_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_c_h_w_kernel.xhtml" target="_self">CLDepthwiseConvolutionLayer3x3NCHWKernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor when the data layout is NCHW </td></tr>
-<tr id="row_0_92_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_h_w_c_kernel.xhtml" target="_self">CLDepthwiseConvolutionLayer3x3NHWCKernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor when the data layout is NHWC </td></tr>
-<tr id="row_0_93_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_im2_col_kernel.xhtml" target="_self">CLDepthwiseIm2ColKernel</a></td><td class="desc">Interface for the depthwise im2col reshape kernel </td></tr>
-<tr id="row_0_94_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_separable_convolution_layer.xhtml" target="_self">CLDepthwiseSeparableConvolutionLayer</a></td><td class="desc">Basic function to execute depthwise convolution </td></tr>
-<tr id="row_0_95_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_vector_to_tensor_kernel.xhtml" target="_self">CLDepthwiseVectorToTensorKernel</a></td><td class="desc">Interface for the depthwise vector to tensor kernel </td></tr>
-<tr id="row_0_96_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_weights_reshape_kernel.xhtml" target="_self">CLDepthwiseWeightsReshapeKernel</a></td><td class="desc">Interface for the depthwise weights reshape kernel </td></tr>
-<tr id="row_0_97_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dequantization_layer.xhtml" target="_self">CLDequantizationLayer</a></td><td class="desc">Basic function to simulate a dequantization layer </td></tr>
-<tr id="row_0_98_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml" target="_self">CLDequantizationLayerKernel</a></td><td class="desc">Interface for the dequantization layer kernel </td></tr>
-<tr id="row_0_99_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_derivative.xhtml" target="_self">CLDerivative</a></td><td class="desc">Basic function to execute first order derivative operator </td></tr>
-<tr id="row_0_100_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_derivative_kernel.xhtml" target="_self">CLDerivativeKernel</a></td><td class="desc">Interface for the derivative kernel </td></tr>
-<tr id="row_0_101_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_device_options.xhtml" target="_self">CLDeviceOptions</a></td><td class="desc">OpenCL device options </td></tr>
-<tr id="row_0_102_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dilate.xhtml" target="_self">CLDilate</a></td><td class="desc">Basic function to execute dilate </td></tr>
-<tr id="row_0_103_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dilate_kernel.xhtml" target="_self">CLDilateKernel</a></td><td class="desc">Interface for the dilate kernel </td></tr>
-<tr id="row_0_104_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml" target="_self">CLDirectConvolutionLayer</a></td><td class="desc">Basic function to execute direct convolution function: </td></tr>
-<tr id="row_0_105_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml" target="_self">CLDirectConvolutionLayerKernel</a></td><td class="desc">Interface for the direct convolution kernel </td></tr>
-<tr id="row_0_106_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer_output_stage_kernel.xhtml" target="_self">CLDirectConvolutionLayerOutputStageKernel</a></td><td class="desc">OpenCL kernel to accumulate the biases, if provided, or downscale in case of quantized input </td></tr>
-<tr id="row_0_107_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_distribution1_d.xhtml" target="_self">CLDistribution1D</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_c_l_distribution1_d.xhtml" title="CLDistribution1D object class. ">CLDistribution1D</a> object class </td></tr>
-<tr id="row_0_108_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel.xhtml" target="_self">CLEdgeNonMaxSuppressionKernel</a></td><td class="desc">OpenCL kernel to perform Non-Maxima suppression for Canny Edge </td></tr>
-<tr id="row_0_109_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_edge_trace_kernel.xhtml" target="_self">CLEdgeTraceKernel</a></td><td class="desc">OpenCL kernel to perform Edge tracing </td></tr>
-<tr id="row_0_110_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_equalize_histogram.xhtml" target="_self">CLEqualizeHistogram</a></td><td class="desc">Basic function to execute histogram equalization </td></tr>
-<tr id="row_0_111_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_erode.xhtml" target="_self">CLErode</a></td><td class="desc">Basic function to execute erode </td></tr>
-<tr id="row_0_112_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_erode_kernel.xhtml" target="_self">CLErodeKernel</a></td><td class="desc">Interface for the erode kernel </td></tr>
-<tr id="row_0_113_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fast_corners.xhtml" target="_self">CLFastCorners</a></td><td class="desc">Basic function to execute fast corners </td></tr>
-<tr id="row_0_114_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fast_corners_kernel.xhtml" target="_self">CLFastCornersKernel</a></td><td class="desc">CL kernel to perform fast corners </td></tr>
-<tr id="row_0_115_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fill_border.xhtml" target="_self">CLFillBorder</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml">CLFillBorderKernel</a> </td></tr>
-<tr id="row_0_116_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml" target="_self">CLFillBorderKernel</a></td><td class="desc">Interface for filling the border of a kernel </td></tr>
-<tr id="row_0_117_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fine_s_v_m_memory_region.xhtml" target="_self">CLFineSVMMemoryRegion</a></td><td class="desc">OpenCL fine-grain SVM memory region implementation </td></tr>
-<tr id="row_0_118_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_flatten_layer.xhtml" target="_self">CLFlattenLayer</a></td><td class="desc">Basic function to execute flatten </td></tr>
-<tr id="row_0_119_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_floor.xhtml" target="_self">CLFloor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_floor_kernel.xhtml">CLFloorKernel</a> </td></tr>
-<tr id="row_0_120_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_floor_kernel.xhtml" target="_self">CLFloorKernel</a></td><td class="desc">OpenCL kernel to perform a floor operation </td></tr>
-<tr id="row_0_121_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer.xhtml" target="_self">CLFullyConnectedLayer</a></td><td class="desc">Basic function to compute a Fully Connected layer on OpenCL </td></tr>
-<tr id="row_0_122_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer_reshape_weights.xhtml" target="_self">CLFullyConnectedLayerReshapeWeights</a></td><td class="desc">Basic function to reshape the weights of Fully Connected layer with OpenCL </td></tr>
-<tr id="row_0_123_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian3x3.xhtml" target="_self">CLGaussian3x3</a></td><td class="desc">Basic function to execute gaussian filter 3x3 </td></tr>
-<tr id="row_0_124_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian3x3_kernel.xhtml" target="_self">CLGaussian3x3Kernel</a></td><td class="desc">Interface for the Gaussian 3x3 filter kernel </td></tr>
-<tr id="row_0_125_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian5x5.xhtml" target="_self">CLGaussian5x5</a></td><td class="desc">Basic function to execute gaussian filter 5x5 </td></tr>
-<tr id="row_0_126_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian5x5_hor_kernel.xhtml" target="_self">CLGaussian5x5HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 5x5 Gaussian filter on a tensor </td></tr>
-<tr id="row_0_127_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian5x5_vert_kernel.xhtml" target="_self">CLGaussian5x5VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 5x5 Gaussian filter on a tensor </td></tr>
-<tr id="row_0_128_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid.xhtml" target="_self">CLGaussianPyramid</a></td><td class="desc">Common interface for all Gaussian pyramid functions </td></tr>
-<tr id="row_0_129_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_half.xhtml" target="_self">CLGaussianPyramidHalf</a></td><td class="desc">Basic function to execute gaussian pyramid with HALF scale factor </td></tr>
-<tr id="row_0_130_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_hor_kernel.xhtml" target="_self">CLGaussianPyramidHorKernel</a></td><td class="desc">OpenCL kernel to perform a Gaussian filter and half scaling across width (horizontal pass) </td></tr>
-<tr id="row_0_131_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_orb.xhtml" target="_self">CLGaussianPyramidOrb</a></td><td class="desc">Basic function to execute gaussian pyramid with ORB scale factor </td></tr>
-<tr id="row_0_132_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_vert_kernel.xhtml" target="_self">CLGaussianPyramidVertKernel</a></td><td class="desc">OpenCL kernel to perform a Gaussian filter and half scaling across height (vertical pass) </td></tr>
-<tr id="row_0_133_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m.xhtml" target="_self">CLGEMM</a></td><td class="desc">Basic function to execute GEMM on OpenCL </td></tr>
-<tr id="row_0_134_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_convolution_layer.xhtml" target="_self">CLGEMMConvolutionLayer</a></td><td class="desc">Basic function to compute the convolution layer </td></tr>
-<tr id="row_0_135_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4.xhtml" target="_self">CLGEMMInterleave4x4</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4_kernel.xhtml" title="OpenCL kernel which interleaves the elements of a matrix A in chunk of 4x4. ">CLGEMMInterleave4x4Kernel</a> </td></tr>
-<tr id="row_0_136_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4_kernel.xhtml" target="_self">CLGEMMInterleave4x4Kernel</a></td><td class="desc">OpenCL kernel which interleaves the elements of a matrix A in chunk of 4x4 </td></tr>
-<tr id="row_0_137_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_a_reduction_kernel.xhtml" target="_self">CLGEMMLowpMatrixAReductionKernel</a></td><td class="desc">OpenCL kernel used to compute the row-vectors of sums of all the entries in each row of Matrix A </td></tr>
-<tr id="row_0_138_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_b_reduction_kernel.xhtml" target="_self">CLGEMMLowpMatrixBReductionKernel</a></td><td class="desc">OpenCL kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B </td></tr>
-<tr id="row_0_139_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core.xhtml" target="_self">CLGEMMLowpMatrixMultiplyCore</a></td><td class="desc">Basic function to execute GEMMLowpMatrixMultiplyCore on OpenCL </td></tr>
-<tr id="row_0_140_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml" target="_self">CLGEMMLowpMatrixMultiplyKernel</a></td><td class="desc">OpenCL kernel to multiply matrices </td></tr>
-<tr id="row_0_141_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_offset_contribution_kernel.xhtml" target="_self">CLGEMMLowpOffsetContributionKernel</a></td><td class="desc">OpenCL kernel used to add the offset contribution after <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml">CLGEMMLowpMatrixMultiplyKernel</a> </td></tr>
-<tr id="row_0_142_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" target="_self">CLGEMMLowpQuantizeDownInt32ToUint8Scale</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" title="Basic function to execute CLGEMMLowpQuantizeDownInt32ToUint8Scale on OpenCL. ">CLGEMMLowpQuantizeDownInt32ToUint8Scale</a> on OpenCL </td></tr>
-<tr id="row_0_143_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" target="_self">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" title="Basic function to execute CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint on OpenCL. ">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a> on OpenCL </td></tr>
-<tr id="row_0_144_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point_kernel.xhtml" target="_self">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel</a></td><td class="desc">OpenCL kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 </td></tr>
-<tr id="row_0_145_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_kernel.xhtml" target="_self">CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel</a></td><td class="desc">OpenCL kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 </td></tr>
-<tr id="row_0_146_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_accumulate_biases_kernel.xhtml" target="_self">CLGEMMMatrixAccumulateBiasesKernel</a></td><td class="desc">Interface to add a bias to each row of the input tensor </td></tr>
-<tr id="row_0_147_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_addition_kernel.xhtml" target="_self">CLGEMMMatrixAdditionKernel</a></td><td class="desc">OpenCL kernel to perform the in-place matrix addition between 2 matrices, taking into account that the second matrix might be weighted by a scalar value beta </td></tr>
-<tr id="row_0_148_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_multiply_kernel.xhtml" target="_self">CLGEMMMatrixMultiplyKernel</a></td><td class="desc">OpenCL kernel to multiply two input matrices "A" and "B" </td></tr>
-<tr id="row_0_149_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_vector_multiply_kernel.xhtml" target="_self">CLGEMMMatrixVectorMultiplyKernel</a></td><td class="desc">Interface for the GEMM matrix vector multiply kernel </td></tr>
-<tr id="row_0_150_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_transpose1x_w.xhtml" target="_self">CLGEMMTranspose1xW</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_transpose1x_w_kernel.xhtml" title="OpenCL kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / e...">CLGEMMTranspose1xWKernel</a> </td></tr>
-<tr id="row_0_151_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_transpose1x_w_kernel.xhtml" target="_self">CLGEMMTranspose1xWKernel</a></td><td class="desc">OpenCL kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / element size of the tensor) </td></tr>
-<tr id="row_0_152_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gradient_kernel.xhtml" target="_self">CLGradientKernel</a></td><td class="desc">OpenCL kernel to perform Gradient computation </td></tr>
-<tr id="row_0_153_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_harris_corners.xhtml" target="_self">CLHarrisCorners</a></td><td class="desc">Basic function to execute harris corners detection </td></tr>
-<tr id="row_0_154_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_harris_score_kernel.xhtml" target="_self">CLHarrisScoreKernel</a></td><td class="desc">Interface for the harris score kernel </td></tr>
-<tr id="row_0_155_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_histogram.xhtml" target="_self">CLHistogram</a></td><td class="desc">Basic function to execute histogram </td></tr>
-<tr id="row_0_156_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_histogram_border_kernel.xhtml" target="_self">CLHistogramBorderKernel</a></td><td class="desc">Interface to run the histogram kernel to handle the leftover part of image </td></tr>
-<tr id="row_0_157_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_histogram_kernel.xhtml" target="_self">CLHistogramKernel</a></td><td class="desc">Interface to run the histogram kernel </td></tr>
-<tr id="row_0_158_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g.xhtml" target="_self">CLHOG</a></td><td class="desc">OpenCL implementation of <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-object </td></tr>
-<tr id="row_0_159_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_block_normalization_kernel.xhtml" target="_self">CLHOGBlockNormalizationKernel</a></td><td class="desc">OpenCL kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> block normalization </td></tr>
-<tr id="row_0_160_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_descriptor.xhtml" target="_self">CLHOGDescriptor</a></td><td class="desc">Basic function to calculate <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> descriptor </td></tr>
-<tr id="row_0_161_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_detector.xhtml" target="_self">CLHOGDetector</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector based on linear SVM </td></tr>
-<tr id="row_0_162_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_detector_kernel.xhtml" target="_self">CLHOGDetectorKernel</a></td><td class="desc">OpenCL kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector kernel using linear SVM </td></tr>
-<tr id="row_0_163_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_gradient.xhtml" target="_self">CLHOGGradient</a></td><td class="desc">Basic function to calculate the gradient for <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
-<tr id="row_0_164_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml" target="_self">CLHOGMultiDetection</a></td><td class="desc">Basic function to detect multiple objects (or the same object at different scales) on the same input image using <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
-<tr id="row_0_165_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_orientation_binning_kernel.xhtml" target="_self">CLHOGOrientationBinningKernel</a></td><td class="desc">OpenCL kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> Orientation Binning </td></tr>
-<tr id="row_0_166_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_im2_col_kernel.xhtml" target="_self">CLIm2ColKernel</a></td><td class="desc">Interface for the im2col reshape kernel </td></tr>
-<tr id="row_0_167_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_integral_image.xhtml" target="_self">CLIntegralImage</a></td><td class="desc">Basic function to execute integral image </td></tr>
-<tr id="row_0_168_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_integral_image_hor_kernel.xhtml" target="_self">CLIntegralImageHorKernel</a></td><td class="desc">Interface to run the horizontal pass of the integral image kernel </td></tr>
-<tr id="row_0_169_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_integral_image_vert_kernel.xhtml" target="_self">CLIntegralImageVertKernel</a></td><td class="desc">Interface to run the vertical pass of the integral image kernel </td></tr>
-<tr id="row_0_170_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml" target="_self">CLKernelLibrary</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml" title="CLKernelLibrary class. ">CLKernelLibrary</a> class </td></tr>
-<tr id="row_0_171_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l2_normalize_layer.xhtml" target="_self">CLL2NormalizeLayer</a></td><td class="desc">Basic function to perform a L2 normalization on a given axis </td></tr>
-<tr id="row_0_172_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l2_normalize_layer_kernel.xhtml" target="_self">CLL2NormalizeLayerKernel</a></td><td class="desc">Interface for performing a L2 normalize on a given axis given the square sum of it in this axis </td></tr>
-<tr id="row_0_173_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_laplacian_pyramid.xhtml" target="_self">CLLaplacianPyramid</a></td><td class="desc">Basic function to execute laplacian pyramid </td></tr>
-<tr id="row_0_174_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_laplacian_reconstruct.xhtml" target="_self">CLLaplacianReconstruct</a></td><td class="desc">Basic function to execute laplacian reconstruction </td></tr>
-<tr id="row_0_175_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_l_k_internal_keypoint.xhtml" target="_self">CLLKInternalKeypoint</a></td><td class="desc">Internal keypoint structure for Lucas-Kanade Optical Flow </td></tr>
-<tr id="row_0_176_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_finalize_kernel.xhtml" target="_self">CLLKTrackerFinalizeKernel</a></td><td class="desc">Interface to run the finalize step of LKTracker, where it truncates the coordinates stored in new_points array </td></tr>
-<tr id="row_0_177_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_init_kernel.xhtml" target="_self">CLLKTrackerInitKernel</a></td><td class="desc">Interface to run the initialization step of LKTracker </td></tr>
-<tr id="row_0_178_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_stage0_kernel.xhtml" target="_self">CLLKTrackerStage0Kernel</a></td><td class="desc">Interface to run the first stage of LKTracker, where A11, A12, A22, min_eig, ival, ixval and iyval are computed </td></tr>
-<tr id="row_0_179_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_stage1_kernel.xhtml" target="_self">CLLKTrackerStage1Kernel</a></td><td class="desc">Interface to run the second stage of LKTracker, where the motion vectors of the given points are computed </td></tr>
-<tr id="row_0_180_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_locally_connected_layer.xhtml" target="_self">CLLocallyConnectedLayer</a></td><td class="desc">Basic function to compute the locally connected layer </td></tr>
-<tr id="row_0_181_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_locally_connected_matrix_multiply_kernel.xhtml" target="_self">CLLocallyConnectedMatrixMultiplyKernel</a></td><td class="desc">OpenCL kernel to multiply each row of first tensor with low 2 dimensions of second tensor </td></tr>
-<tr id="row_0_182_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_max_kernel.xhtml" target="_self">CLLogits1DMaxKernel</a></td><td class="desc">Interface for the identifying the max value of 1D Logits </td></tr>
-<tr id="row_0_183_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_max_shift_exp_sum_kernel.xhtml" target="_self">CLLogits1DMaxShiftExpSumKernel</a></td><td class="desc">Interface for max, shifting, exponentiating and summing the logits </td></tr>
-<tr id="row_0_184_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_norm_kernel.xhtml" target="_self">CLLogits1DNormKernel</a></td><td class="desc">Interface for calculating the final step of the Softmax Layer where each logit value is multiplied by the inverse of the sum of the logits </td></tr>
-<tr id="row_0_185_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_shift_exp_sum_kernel.xhtml" target="_self">CLLogits1DShiftExpSumKernel</a></td><td class="desc">Interface for shifting, exponentiating and summing the logits </td></tr>
-<tr id="row_0_186_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_s_t_m_layer.xhtml" target="_self">CLLSTMLayer</a></td><td class="desc">This function performs a single time step in a Long Short-Term <a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> (LSTM) layer </td></tr>
-<tr id="row_0_187_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_lut.xhtml" target="_self">CLLut</a></td><td class="desc">Basic implementation of the OpenCL lut interface </td></tr>
-<tr id="row_0_188_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_lut_allocator.xhtml" target="_self">CLLutAllocator</a></td><td class="desc">Basic implementation of a CL memory LUT allocator </td></tr>
-<tr id="row_0_189_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_magnitude.xhtml" target="_self">CLMagnitude</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml">CLMagnitudePhaseKernel</a> </td></tr>
-<tr id="row_0_190_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml" target="_self">CLMagnitudePhaseKernel</a></td><td class="desc">Template interface for the kernel to compute magnitude and phase </td></tr>
-<tr id="row_0_191_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_mean_std_dev.xhtml" target="_self">CLMeanStdDev</a></td><td class="desc">Basic function to execute mean and standard deviation by calling <a class="el" href="classarm__compute_1_1_c_l_mean_std_dev_kernel.xhtml">CLMeanStdDevKernel</a> </td></tr>
-<tr id="row_0_192_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_mean_std_dev_kernel.xhtml" target="_self">CLMeanStdDevKernel</a></td><td class="desc">Interface for the kernel to calculate mean and standard deviation of input image pixels </td></tr>
-<tr id="row_0_193_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_median3x3.xhtml" target="_self">CLMedian3x3</a></td><td class="desc">Basic function to execute median filter </td></tr>
-<tr id="row_0_194_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_median3x3_kernel.xhtml" target="_self">CLMedian3x3Kernel</a></td><td class="desc">Interface for the median 3x3 filter kernel </td></tr>
-<tr id="row_0_195_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_memory.xhtml" target="_self">CLMemory</a></td><td class="desc">OpenCL implementation of memory object </td></tr>
-<tr id="row_0_196_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_kernel.xhtml" target="_self">CLMinMaxKernel</a></td><td class="desc">Interface for the kernel to perform min max search on an image </td></tr>
-<tr id="row_0_197_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_layer_kernel.xhtml" target="_self">CLMinMaxLayerKernel</a></td><td class="desc">Interface for the kernel to perform min max search on a 3D tensor </td></tr>
-<tr id="row_0_198_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_location.xhtml" target="_self">CLMinMaxLocation</a></td><td class="desc">Basic function to execute min and max location </td></tr>
-<tr id="row_0_199_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_location_kernel.xhtml" target="_self">CLMinMaxLocationKernel</a></td><td class="desc">Interface for the kernel to find min max locations of an image </td></tr>
-<tr id="row_0_200_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_multi_h_o_g.xhtml" target="_self">CLMultiHOG</a></td><td class="desc">Basic implementation of the CL multi <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-objects </td></tr>
-<tr id="row_0_201_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_multi_image.xhtml" target="_self">CLMultiImage</a></td><td class="desc">Basic implementation of the CL multi-planar image interface </td></tr>
-<tr id="row_0_202_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_linear_filter.xhtml" target="_self">CLNonLinearFilter</a></td><td class="desc">Basic function to execute non linear filter </td></tr>
-<tr id="row_0_203_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_linear_filter_kernel.xhtml" target="_self">CLNonLinearFilterKernel</a></td><td class="desc">Interface for the kernel to apply a non-linear filter </td></tr>
-<tr id="row_0_204_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_maxima_suppression3x3.xhtml" target="_self">CLNonMaximaSuppression3x3</a></td><td class="desc">Basic function to execute non-maxima suppression over a 3x3 window </td></tr>
-<tr id="row_0_205_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_maxima_suppression3x3_kernel.xhtml" target="_self">CLNonMaximaSuppression3x3Kernel</a></td><td class="desc">Interface to perform Non-Maxima suppression over a 3x3 window using OpenCL </td></tr>
-<tr id="row_0_206_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_normalization_layer.xhtml" target="_self">CLNormalizationLayer</a></td><td class="desc">Basic function to compute a normalization layer </td></tr>
-<tr id="row_0_207_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_normalization_layer_kernel.xhtml" target="_self">CLNormalizationLayerKernel</a></td><td class="desc">Interface for the normalization layer kernel </td></tr>
-<tr id="row_0_208_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_old_value.xhtml" target="_self">CLOldValue</a></td><td class="desc">Structure for storing ival, ixval and iyval for each point inside the window </td></tr>
-<tr id="row_0_209_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_optical_flow.xhtml" target="_self">CLOpticalFlow</a></td><td class="desc">Basic function to execute optical flow </td></tr>
-<tr id="row_0_210_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_permute.xhtml" target="_self">CLPermute</a></td><td class="desc">Basic function to execute an <a class="el" href="classarm__compute_1_1_c_l_permute_kernel.xhtml">CLPermuteKernel</a> </td></tr>
-<tr id="row_0_211_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_permute_kernel.xhtml" target="_self">CLPermuteKernel</a></td><td class="desc">OpenCL kernel to perform tensor permutation </td></tr>
-<tr id="row_0_212_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_phase.xhtml" target="_self">CLPhase</a></td><td class="desc">Basic function to execute an <a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml">CLMagnitudePhaseKernel</a> </td></tr>
-<tr id="row_0_213_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication.xhtml" target="_self">CLPixelWiseMultiplication</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication_kernel.xhtml">CLPixelWiseMultiplicationKernel</a> </td></tr>
-<tr id="row_0_214_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication_kernel.xhtml" target="_self">CLPixelWiseMultiplicationKernel</a></td><td class="desc">Interface for the pixelwise multiplication kernel </td></tr>
-<tr id="row_0_215_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pooling_layer.xhtml" target="_self">CLPoolingLayer</a></td><td class="desc">Basic function to simulate a pooling layer with the specified pooling operation </td></tr>
-<tr id="row_0_216_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pooling_layer_kernel.xhtml" target="_self">CLPoolingLayerKernel</a></td><td class="desc">Interface for the pooling layer kernel </td></tr>
-<tr id="row_0_217_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pyramid.xhtml" target="_self">CLPyramid</a></td><td class="desc">Basic implementation of the OpenCL pyramid interface </td></tr>
-<tr id="row_0_218_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_quantization_layer.xhtml" target="_self">CLQuantizationLayer</a></td><td class="desc">Basic function to simulate a quantization layer </td></tr>
-<tr id="row_0_219_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_quantization_layer_kernel.xhtml" target="_self">CLQuantizationLayerKernel</a></td><td class="desc">Interface for the quantization layer kernel </td></tr>
-<tr id="row_0_220_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reduction_operation.xhtml" target="_self">CLReductionOperation</a></td><td class="desc">Perform reduction operation </td></tr>
-<tr id="row_0_221_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reduction_operation_kernel.xhtml" target="_self">CLReductionOperationKernel</a></td><td class="desc">Interface for the reduction operation kernel </td></tr>
-<tr id="row_0_222_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_remap.xhtml" target="_self">CLRemap</a></td><td class="desc">Basic function to execute remap </td></tr>
-<tr id="row_0_223_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_remap_kernel.xhtml" target="_self">CLRemapKernel</a></td><td class="desc">OpenCL kernel to perform a remap on a tensor </td></tr>
-<tr id="row_0_224_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reshape_layer.xhtml" target="_self">CLReshapeLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml">CLReshapeLayerKernel</a> </td></tr>
-<tr id="row_0_225_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml" target="_self">CLReshapeLayerKernel</a></td><td class="desc">Interface for the kernel to perform tensor reshaping </td></tr>
-<tr id="row_0_226_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_r_n_n_layer.xhtml" target="_self">CLRNNLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_r_n_n_layer.xhtml">CLRNNLayer</a> </td></tr>
-<tr id="row_0_227_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer.xhtml" target="_self">CLROIPoolingLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer_kernel.xhtml">CLROIPoolingLayerKernel</a> </td></tr>
-<tr id="row_0_228_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer_kernel.xhtml" target="_self">CLROIPoolingLayerKernel</a></td><td class="desc">Interface for the <a class="el" href="structarm__compute_1_1_r_o_i.xhtml" title="Region of interest. ">ROI</a> pooling layer kernel </td></tr>
-<tr id="row_0_229_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scale.xhtml" target="_self">CLScale</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_scale_kernel.xhtml">CLScaleKernel</a> </td></tr>
-<tr id="row_0_230_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scale_kernel.xhtml" target="_self">CLScaleKernel</a></td><td class="desc">Interface for the scale kernel </td></tr>
-<tr id="row_0_231_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scharr3x3.xhtml" target="_self">CLScharr3x3</a></td><td class="desc">Basic function to execute scharr 3x3 filter </td></tr>
-<tr id="row_0_232_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scharr3x3_kernel.xhtml" target="_self">CLScharr3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Scharr filter on a tensor </td></tr>
-<tr id="row_0_233_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" target="_self">CLScheduler</a></td><td class="desc">Provides global access to a CL context and command queue </td></tr>
-<tr id="row_0_234_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_separable_convolution_hor_kernel.xhtml" target="_self">CLSeparableConvolutionHorKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the Horizontal pass of a Separable Convolution </td></tr>
-<tr id="row_0_235_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_separable_convolution_vert_kernel.xhtml" target="_self">CLSeparableConvolutionVertKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the Vertical pass of a Separable Convolution </td></tr>
-<tr id="row_0_236_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel3x3.xhtml" target="_self">CLSobel3x3</a></td><td class="desc">Basic function to execute sobel 3x3 filter </td></tr>
-<tr id="row_0_237_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel3x3_kernel.xhtml" target="_self">CLSobel3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Sobel filter on a tensor </td></tr>
-<tr id="row_0_238_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel5x5.xhtml" target="_self">CLSobel5x5</a></td><td class="desc">Basic function to execute sobel 5x5 filter </td></tr>
-<tr id="row_0_239_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel5x5_hor_kernel.xhtml" target="_self">CLSobel5x5HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 5x5 Sobel filter on a tensor </td></tr>
-<tr id="row_0_240_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel5x5_vert_kernel.xhtml" target="_self">CLSobel5x5VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 5x5 Sobel filter on a tensor </td></tr>
-<tr id="row_0_241_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel7x7.xhtml" target="_self">CLSobel7x7</a></td><td class="desc">Basic function to execute sobel 7x7 filter </td></tr>
-<tr id="row_0_242_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel7x7_hor_kernel.xhtml" target="_self">CLSobel7x7HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 7x7 Sobel filter on a tensor </td></tr>
-<tr id="row_0_243_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel7x7_vert_kernel.xhtml" target="_self">CLSobel7x7VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 7x7 Sobel filter on a tensor </td></tr>
-<tr id="row_0_244_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_softmax_layer.xhtml" target="_self">CLSoftmaxLayer</a></td><td class="desc">Basic function to compute a SoftmaxLayer </td></tr>
-<tr id="row_0_245_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sub_tensor.xhtml" target="_self">CLSubTensor</a></td><td class="desc">Basic implementation of the OpenCL sub-tensor interface </td></tr>
-<tr id="row_0_246_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_symbols.xhtml" target="_self">CLSymbols</a></td><td class="desc">Class for loading OpenCL symbols </td></tr>
-<tr id="row_0_247_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_table_lookup.xhtml" target="_self">CLTableLookup</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_table_lookup_kernel.xhtml">CLTableLookupKernel</a> </td></tr>
-<tr id="row_0_248_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_table_lookup_kernel.xhtml" target="_self">CLTableLookupKernel</a></td><td class="desc">Interface for the kernel to perform table lookup calculations </td></tr>
-<tr id="row_0_249_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml" target="_self">CLTensor</a></td><td class="desc">Basic implementation of the OpenCL tensor interface </td></tr>
-<tr id="row_0_250_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml" target="_self">CLTensorAllocator</a></td><td class="desc">Basic implementation of a CL memory tensor allocator </td></tr>
-<tr id="row_0_251_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_threshold.xhtml" target="_self">CLThreshold</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_threshold_kernel.xhtml">CLThresholdKernel</a> </td></tr>
-<tr id="row_0_252_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_threshold_kernel.xhtml" target="_self">CLThresholdKernel</a></td><td class="desc">Interface for the thresholding kernel </td></tr>
-<tr id="row_0_253_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_transpose.xhtml" target="_self">CLTranspose</a></td><td class="desc">Basic function to transpose a matrix on OpenCL </td></tr>
-<tr id="row_0_254_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_transpose_kernel.xhtml" target="_self">CLTransposeKernel</a></td><td class="desc">OpenCL kernel which transposes the elements of a matrix </td></tr>
-<tr id="row_0_255_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_tuner.xhtml" target="_self">CLTuner</a></td><td class="desc">Basic implementation of the OpenCL tuner interface </td></tr>
-<tr id="row_0_256_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_affine.xhtml" target="_self">CLWarpAffine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_warp_affine_kernel.xhtml">CLWarpAffineKernel</a> for AFFINE transformation </td></tr>
-<tr id="row_0_257_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_affine_kernel.xhtml" target="_self">CLWarpAffineKernel</a></td><td class="desc">Interface for the warp affine kernel </td></tr>
-<tr id="row_0_258_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_perspective.xhtml" target="_self">CLWarpPerspective</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_warp_perspective_kernel.xhtml">CLWarpPerspectiveKernel</a> for PERSPECTIVE transformation </td></tr>
-<tr id="row_0_259_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_perspective_kernel.xhtml" target="_self">CLWarpPerspectiveKernel</a></td><td class="desc">Interface for the warp perspective kernel </td></tr>
-<tr id="row_0_260_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_weights_reshape_kernel.xhtml" target="_self">CLWeightsReshapeKernel</a></td><td class="desc">OpenCL kernel to perform reshaping on the weights used by convolution and locally connected layer </td></tr>
-<tr id="row_0_261_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml" target="_self">CLWidthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along x axis </td></tr>
-<tr id="row_0_262_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer_kernel.xhtml" target="_self">CLWidthConcatenateLayerKernel</a></td><td class="desc">Interface for the width concatenate kernel </td></tr>
-<tr id="row_0_263_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_convolution_layer.xhtml" target="_self">CLWinogradConvolutionLayer</a></td><td class="desc">Basic function to execute Winograd-based convolution on OpenCL </td></tr>
-<tr id="row_0_264_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_filter_transform_kernel.xhtml" target="_self">CLWinogradFilterTransformKernel</a></td><td class="desc">Interface for the Winograd filter transform kernel </td></tr>
-<tr id="row_0_265_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_input_transform.xhtml" target="_self">CLWinogradInputTransform</a></td><td class="desc">Basic function to execute a <a class="el" href="classarm__compute_1_1_c_l_winograd_input_transform_kernel.xhtml">CLWinogradInputTransformKernel</a> </td></tr>
-<tr id="row_0_266_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_input_transform_kernel.xhtml" target="_self">CLWinogradInputTransformKernel</a></td><td class="desc">OpenCL kernel to perform Winograd input transform </td></tr>
-<tr id="row_0_267_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_output_transform_kernel.xhtml" target="_self">CLWinogradOutputTransformKernel</a></td><td class="desc">Interface for the Winograd output transform kernel </td></tr>
-<tr id="row_0_268_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_coordinates.xhtml" target="_self">Coordinates</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_coordinates.xhtml" title="Coordinates of an item. ">Coordinates</a> of an item </td></tr>
-<tr id="row_0_269_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_coordinates2_d.xhtml" target="_self">Coordinates2D</a></td><td class="desc">Coordinate type </td></tr>
-<tr id="row_0_270_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_coordinates3_d.xhtml" target="_self">Coordinates3D</a></td><td class="desc">Coordinate type </td></tr>
-<tr id="row_0_271_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_corner_candidates_kernel.xhtml" target="_self">CPPCornerCandidatesKernel</a></td><td class="desc">CPP kernel to perform corner candidates </td></tr>
-<tr id="row_0_272_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_detection_window_non_maxima_suppression_kernel.xhtml" target="_self">CPPDetectionWindowNonMaximaSuppressionKernel</a></td><td class="desc">CPP kernel to perform in-place computation of euclidean distance on IDetectionWindowArray </td></tr>
-<tr id="row_0_273_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_permute.xhtml" target="_self">CPPPermute</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_p_p_permute_kernel.xhtml">CPPPermuteKernel</a> </td></tr>
-<tr id="row_0_274_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_permute_kernel.xhtml" target="_self">CPPPermuteKernel</a></td><td class="desc">CPP kernel to perform tensor permutation </td></tr>
-<tr id="row_0_275_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml" target="_self">CPPScheduler</a></td><td class="desc">C++11 implementation of a pool of threads to automatically split a kernel's execution among several threads </td></tr>
-<tr id="row_0_276_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_sort_euclidean_distance_kernel.xhtml" target="_self">CPPSortEuclideanDistanceKernel</a></td><td class="desc">CPP kernel to perform sorting and euclidean distance </td></tr>
-<tr id="row_0_277_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_upsample.xhtml" target="_self">CPPUpsample</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_p_p_upsample.xhtml">CPPUpsample</a> </td></tr>
-<tr id="row_0_278_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_upsample_kernel.xhtml" target="_self">CPPUpsampleKernel</a></td><td class="desc">CPP kernel to perform tensor upsample </td></tr>
-<tr id="row_0_279_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_u_info.xhtml" target="_self">CPUInfo</a></td><td class="desc"></td></tr>
-<tr id="row_0_280_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_detection_window.xhtml" target="_self">DetectionWindow</a></td><td class="desc">Detection window used for the object detection </td></tr>
-<tr id="row_0_281_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_dimensions.xhtml" target="_self">Dimensions</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_dimensions.xhtml" title="Dimensions with dimensionality. ">Dimensions</a> with dimensionality </td></tr>
-<tr id="row_0_282_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_distribution1_d.xhtml" target="_self">Distribution1D</a></td><td class="desc">Basic implementation of the 1D distribution interface </td></tr>
-<tr id="row_0_283_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1enable__bitwise__ops.xhtml" target="_self">enable_bitwise_ops</a></td><td class="desc">Disable bitwise operations by default </td></tr>
-<tr id="row_0_284_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1enable__bitwise__ops_3_01arm__compute_1_1_g_p_u_target_01_4.xhtml" target="_self">enable_bitwise_ops< arm_compute::GPUTarget ></a></td><td class="desc">Enable bitwise operations on GPUTarget enumerations </td></tr>
-<tr id="row_0_285_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_absolute_difference.xhtml" target="_self">GCAbsoluteDifference</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_absolute_difference_kernel.xhtml">GCAbsoluteDifferenceKernel</a> </td></tr>
-<tr id="row_0_286_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_absolute_difference_kernel.xhtml" target="_self">GCAbsoluteDifferenceKernel</a></td><td class="desc">Interface for the absolute difference kernel </td></tr>
-<tr id="row_0_287_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_activation_layer.xhtml" target="_self">GCActivationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_activation_layer_kernel.xhtml">GCActivationLayerKernel</a> </td></tr>
-<tr id="row_0_288_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_activation_layer_kernel.xhtml" target="_self">GCActivationLayerKernel</a></td><td class="desc">Interface for the activation layer kernel </td></tr>
-<tr id="row_0_289_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_arithmetic_addition.xhtml" target="_self">GCArithmeticAddition</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_arithmetic_addition_kernel.xhtml">GCArithmeticAdditionKernel</a> </td></tr>
-<tr id="row_0_290_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_arithmetic_addition_kernel.xhtml" target="_self">GCArithmeticAdditionKernel</a></td><td class="desc">Interface for the arithmetic addition kernel </td></tr>
-<tr id="row_0_291_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_batch_normalization_layer.xhtml" target="_self">GCBatchNormalizationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_batch_normalization_layer_kernel.xhtml">GCBatchNormalizationLayerKernel</a> and simulate a batch normalization layer </td></tr>
-<tr id="row_0_292_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_batch_normalization_layer_kernel.xhtml" target="_self">GCBatchNormalizationLayerKernel</a></td><td class="desc">Interface for the BatchNormalization layer kernel </td></tr>
-<tr id="row_0_293_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_buffer_allocator.xhtml" target="_self">GCBufferAllocator</a></td><td class="desc">Default GLES buffer allocator implementation </td></tr>
-<tr id="row_0_294_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_col2_im_kernel.xhtml" target="_self">GCCol2ImKernel</a></td><td class="desc">Interface for the col2im reshaping kernel </td></tr>
-<tr id="row_0_295_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_convolution_layer.xhtml" target="_self">GCConvolutionLayer</a></td><td class="desc">Basic function to compute the convolution layer </td></tr>
-<tr id="row_0_296_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_convolution_layer_reshape_weights.xhtml" target="_self">GCConvolutionLayerReshapeWeights</a></td><td class="desc">Function to reshape and transpose the weights </td></tr>
-<tr id="row_0_297_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depth_concatenate_layer.xhtml" target="_self">GCDepthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
-<tr id="row_0_298_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depth_concatenate_layer_kernel.xhtml" target="_self">GCDepthConcatenateLayerKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
-<tr id="row_0_299_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depthwise_convolution_layer3x3.xhtml" target="_self">GCDepthwiseConvolutionLayer3x3</a></td><td class="desc">Basic function to execute a depthwise convolution for kernel size 3x3xC </td></tr>
-<tr id="row_0_300_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depthwise_convolution_layer3x3_kernel.xhtml" target="_self">GCDepthwiseConvolutionLayer3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor </td></tr>
-<tr id="row_0_301_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer.xhtml" target="_self">GCDirectConvolutionLayer</a></td><td class="desc">Basic function to execute direct convolution function </td></tr>
-<tr id="row_0_302_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer_kernel.xhtml" target="_self">GCDirectConvolutionLayerKernel</a></td><td class="desc">Interface for the direct convolution kernel </td></tr>
-<tr id="row_0_303_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_dropout_layer.xhtml" target="_self">GCDropoutLayer</a></td><td class="desc">Basic function to do dropout op </td></tr>
-<tr id="row_0_304_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_dropout_layer_kernel.xhtml" target="_self">GCDropoutLayerKernel</a></td><td class="desc">Interface for the dropout layer kernel </td></tr>
-<tr id="row_0_305_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fill_border.xhtml" target="_self">GCFillBorder</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml">GCFillBorderKernel</a> </td></tr>
-<tr id="row_0_306_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml" target="_self">GCFillBorderKernel</a></td><td class="desc">Interface for filling the border of a kernel </td></tr>
-<tr id="row_0_307_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer.xhtml" target="_self">GCFullyConnectedLayer</a></td><td class="desc">Basic function to compute a Fully Connected layer on OpenGL ES </td></tr>
-<tr id="row_0_308_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer_reshape_weights.xhtml" target="_self">GCFullyConnectedLayerReshapeWeights</a></td><td class="desc">Basic function to reshape the weights of Fully Connected layer with OpenGL ES </td></tr>
-<tr id="row_0_309_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m.xhtml" target="_self">GCGEMM</a></td><td class="desc">Basic function to execute GEMM on OpenGLES Compute </td></tr>
-<tr id="row_0_310_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_interleave4x4.xhtml" target="_self">GCGEMMInterleave4x4</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_interleave4x4_kernel.xhtml" title="OpenGL ES kernel which interleaves the elements of a matrix A in chunk of 4x4. ">GCGEMMInterleave4x4Kernel</a> </td></tr>
-<tr id="row_0_311_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_interleave4x4_kernel.xhtml" target="_self">GCGEMMInterleave4x4Kernel</a></td><td class="desc">OpenGL ES kernel which interleaves the elements of a matrix A in chunk of 4x4 </td></tr>
-<tr id="row_0_312_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_accumulate_biases_kernel.xhtml" target="_self">GCGEMMMatrixAccumulateBiasesKernel</a></td><td class="desc">Interface to add a bias to each row of the input tensor </td></tr>
-<tr id="row_0_313_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_addition_kernel.xhtml" target="_self">GCGEMMMatrixAdditionKernel</a></td><td class="desc">OpenGL ES kernel to perform the in-place matrix addition between 2 matrices, taking into account that the second matrix might be weighted by a scalar value beta </td></tr>
-<tr id="row_0_314_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_multiply_kernel.xhtml" target="_self">GCGEMMMatrixMultiplyKernel</a></td><td class="desc">GLES Compute kernel to multiply two input matrices "A" and "B" or to multiply a vector "A" by a matrix "B" </td></tr>
-<tr id="row_0_315_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_transpose1x_w.xhtml" target="_self">GCGEMMTranspose1xW</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_transpose1x_w_kernel.xhtml" title="OpenGLES kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 /...">GCGEMMTranspose1xWKernel</a> </td></tr>
-<tr id="row_0_316_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_transpose1x_w_kernel.xhtml" target="_self">GCGEMMTranspose1xWKernel</a></td><td class="desc">OpenGLES kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / element size of the tensor) </td></tr>
-<tr id="row_0_317_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_im2_col_kernel.xhtml" target="_self">GCIm2ColKernel</a></td><td class="desc">Interface for the im2col reshape kernel </td></tr>
-<tr id="row_0_318_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_kernel.xhtml" target="_self">GCKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_g_c_kernel.xhtml" title="GCKernel class. ">GCKernel</a> class </td></tr>
-<tr id="row_0_319_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_kernel_library.xhtml" target="_self">GCKernelLibrary</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_g_c_kernel_library.xhtml" title="GCKernelLibrary class. ">GCKernelLibrary</a> class </td></tr>
-<tr id="row_0_320_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_logits1_d_max_kernel.xhtml" target="_self">GCLogits1DMaxKernel</a></td><td class="desc">Interface for the identifying the max value of 1D Logits </td></tr>
-<tr id="row_0_321_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_logits1_d_norm_kernel.xhtml" target="_self">GCLogits1DNormKernel</a></td><td class="desc">Interface for calculating the final step of the Softmax Layer where each logit value is multiplied by the inverse of the sum of the logits </td></tr>
-<tr id="row_0_322_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_logits1_d_shift_exp_sum_kernel.xhtml" target="_self">GCLogits1DShiftExpSumKernel</a></td><td class="desc">Interface for shifting the logits values around the max value and exponentiating the result </td></tr>
-<tr id="row_0_323_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalization_layer.xhtml" target="_self">GCNormalizationLayer</a></td><td class="desc">Basic function to compute a normalization layer </td></tr>
-<tr id="row_0_324_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalization_layer_kernel.xhtml" target="_self">GCNormalizationLayerKernel</a></td><td class="desc">Interface for the normalization layer kernel </td></tr>
-<tr id="row_0_325_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer.xhtml" target="_self">GCNormalizePlanarYUVLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer_kernel.xhtml">GCNormalizePlanarYUVLayerKernel</a> </td></tr>
-<tr id="row_0_326_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer_kernel.xhtml" target="_self">GCNormalizePlanarYUVLayerKernel</a></td><td class="desc">Interface for the NormalizePlanarYUV layer kernel </td></tr>
-<tr id="row_0_327_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pixel_wise_multiplication.xhtml" target="_self">GCPixelWiseMultiplication</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_pixel_wise_multiplication_kernel.xhtml">GCPixelWiseMultiplicationKernel</a> </td></tr>
-<tr id="row_0_328_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pixel_wise_multiplication_kernel.xhtml" target="_self">GCPixelWiseMultiplicationKernel</a></td><td class="desc">Interface for the pixelwise multiplication kernel </td></tr>
-<tr id="row_0_329_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pooling_layer.xhtml" target="_self">GCPoolingLayer</a></td><td class="desc">Basic function to simulate a pooling layer with the specified pooling operation </td></tr>
-<tr id="row_0_330_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pooling_layer_kernel.xhtml" target="_self">GCPoolingLayerKernel</a></td><td class="desc">Interface for the pooling layer kernel </td></tr>
-<tr id="row_0_331_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_program.xhtml" target="_self">GCProgram</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_g_c_program.xhtml" title="GCProgram class. ">GCProgram</a> class </td></tr>
-<tr id="row_0_332_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_scale.xhtml" target="_self">GCScale</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_scale_kernel.xhtml">GCScaleKernel</a> </td></tr>
-<tr id="row_0_333_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_scale_kernel.xhtml" target="_self">GCScaleKernel</a></td><td class="desc">Interface for the scale kernel </td></tr>
-<tr id="row_0_334_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_scheduler.xhtml" target="_self">GCScheduler</a></td><td class="desc">Provides global access to a OpenGL ES context and command queue </td></tr>
-<tr id="row_0_335_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_softmax_layer.xhtml" target="_self">GCSoftmaxLayer</a></td><td class="desc">Basic function to compute a SoftmaxLayer </td></tr>
-<tr id="row_0_336_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_tensor.xhtml" target="_self">GCTensor</a></td><td class="desc">Interface for OpenGL ES tensor </td></tr>
-<tr id="row_0_337_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_tensor_allocator.xhtml" target="_self">GCTensorAllocator</a></td><td class="desc">Basic implementation of a GLES memory tensor allocator </td></tr>
-<tr id="row_0_338_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_tensor_shift.xhtml" target="_self">GCTensorShift</a></td><td class="desc">Basic function to execute shift function for tensor </td></tr>
-<tr id="row_0_339_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_tensor_shift_kernel.xhtml" target="_self">GCTensorShiftKernel</a></td><td class="desc">Interface for the kernel to shift valid data on a tensor </td></tr>
-<tr id="row_0_340_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_transpose.xhtml" target="_self">GCTranspose</a></td><td class="desc">Basic function to transpose a matrix on OpenGL ES </td></tr>
-<tr id="row_0_341_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_transpose_kernel.xhtml" target="_self">GCTransposeKernel</a></td><td class="desc">OpenGL ES kernel which transposes the elements of a matrix </td></tr>
-<tr id="row_0_342_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_weights_reshape_kernel.xhtml" target="_self">GCWeightsReshapeKernel</a></td><td class="desc">GLES Compute kernel to perform reshaping on the weights used by convolution and locally connected layer </td></tr>
-<tr id="row_0_343_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_e_m_m_info.xhtml" target="_self">GEMMInfo</a></td><td class="desc">GEMM information class </td></tr>
-<tr id="row_0_344_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml" target="_self">GEMMReshapeInfo</a></td><td class="desc">GEMM reshape information class </td></tr>
-<tr id="row_0_345_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_l_buffer_wrapper.xhtml" target="_self">GLBufferWrapper</a></td><td class="desc"></td></tr>
-<tr id="row_0_346_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_h_o_g.xhtml" target="_self">HOG</a></td><td class="desc">CPU implementation of <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-object </td></tr>
-<tr id="row_0_347_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_h_o_g_info.xhtml" target="_self">HOGInfo</a></td><td class="desc">Store the <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a>'s metadata </td></tr>
-<tr id="row_0_348_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_access_window.xhtml" target="_self">IAccessWindow</a></td><td class="desc">Interface describing methods to update access window and padding based on kernel parameters </td></tr>
-<tr id="row_0_349_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_allocator.xhtml" target="_self">IAllocator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_allocator.xhtml" title="Default malloc allocator implementation. ">Allocator</a> interface </td></tr>
-<tr id="row_0_350_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_array.xhtml" target="_self">IArray</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_array.xhtml" title="Basic implementation of the IArray interface which allocates a static number of T values...">Array</a> of type T </td></tr>
-<tr id="row_0_351_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml" target="_self">ICLArray</a></td><td class="desc">Interface for OpenCL <a class="el" href="classarm__compute_1_1_array.xhtml" title="Basic implementation of the IArray interface which allocates a static number of T values...">Array</a> </td></tr>
-<tr id="row_0_352_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_depthwise_convolution_layer3x3_kernel.xhtml" target="_self">ICLDepthwiseConvolutionLayer3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor </td></tr>
-<tr id="row_0_353_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_distribution1_d.xhtml" target="_self">ICLDistribution1D</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_i_c_l_distribution1_d.xhtml" title="ICLDistribution1D interface class. ">ICLDistribution1D</a> interface class </td></tr>
-<tr id="row_0_354_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_g_e_m_m_lowp_reduction_kernel.xhtml" target="_self">ICLGEMMLowpReductionKernel</a></td><td class="desc">Common interface for all OpenCL reduction kernels </td></tr>
-<tr id="row_0_355_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_h_o_g.xhtml" target="_self">ICLHOG</a></td><td class="desc">Interface for OpenCL <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-object </td></tr>
-<tr id="row_0_356_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml" target="_self">ICLKernel</a></td><td class="desc">Common interface for all the OpenCL kernels </td></tr>
-<tr id="row_0_357_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_lut.xhtml" target="_self">ICLLut</a></td><td class="desc">Interface for OpenCL LUT </td></tr>
-<tr id="row_0_358_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_memory_region.xhtml" target="_self">ICLMemoryRegion</a></td><td class="desc">OpenCL memory region interface </td></tr>
-<tr id="row_0_359_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml" target="_self">ICLMultiHOG</a></td><td class="desc">Interface for storing multiple <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-objects </td></tr>
-<tr id="row_0_360_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_multi_image.xhtml" target="_self">ICLMultiImage</a></td><td class="desc">Interface for OpenCL multi-planar images </td></tr>
-<tr id="row_0_361_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_simple2_d_kernel.xhtml" target="_self">ICLSimple2DKernel</a></td><td class="desc">Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output </td></tr>
-<tr id="row_0_362_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_simple3_d_kernel.xhtml" target="_self">ICLSimple3DKernel</a></td><td class="desc">Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output </td></tr>
-<tr id="row_0_363_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_simple_function.xhtml" target="_self">ICLSimpleFunction</a></td><td class="desc">Basic interface for functions which have a single OpenCL kernel </td></tr>
-<tr id="row_0_364_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_simple_kernel.xhtml" target="_self">ICLSimpleKernel</a></td><td class="desc">Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output </td></tr>
-<tr id="row_0_365_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_s_v_m_memory_region.xhtml" target="_self">ICLSVMMemoryRegion</a></td><td class="desc">OpenCL SVM memory region interface </td></tr>
-<tr id="row_0_366_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml" target="_self">ICLTensor</a></td><td class="desc">Interface for OpenCL tensor </td></tr>
-<tr id="row_0_367_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_tuner.xhtml" target="_self">ICLTuner</a></td><td class="desc">Basic interface for tuning the OpenCL kernels </td></tr>
-<tr id="row_0_368_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml" target="_self">ICPPKernel</a></td><td class="desc">Common interface for all kernels implemented in C++ </td></tr>
-<tr id="row_0_369_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_p_p_simple_function.xhtml" target="_self">ICPPSimpleFunction</a></td><td class="desc">Basic interface for functions which have a single CPP kernel </td></tr>
-<tr id="row_0_370_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_p_p_simple_kernel.xhtml" target="_self">ICPPSimpleKernel</a></td><td class="desc">Interface for simple C++ kernels having 1 tensor input and 1 tensor output </td></tr>
-<tr id="row_0_371_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_distribution.xhtml" target="_self">IDistribution</a></td><td class="desc">Interface for distribution objects </td></tr>
-<tr id="row_0_372_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_distribution1_d.xhtml" target="_self">IDistribution1D</a></td><td class="desc">1D Distribution interface </td></tr>
-<tr id="row_0_373_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_function.xhtml" target="_self">IFunction</a></td><td class="desc">Base class for all functions </td></tr>
-<tr id="row_0_374_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_kernel.xhtml" target="_self">IGCKernel</a></td><td class="desc">Common interface for all the GLES kernels </td></tr>
-<tr id="row_0_375_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_simple2_d_kernel.xhtml" target="_self">IGCSimple2DKernel</a></td><td class="desc">Interface for simple OpenGL ES kernels having 1 tensor input and 1 tensor output </td></tr>
-<tr id="row_0_376_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_simple3_d_kernel.xhtml" target="_self">IGCSimple3DKernel</a></td><td class="desc">Interface for simple GLES kernels having 1 tensor input and 1 tensor output </td></tr>
-<tr id="row_0_377_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_simple_function.xhtml" target="_self">IGCSimpleFunction</a></td><td class="desc">Basic interface for functions which have a single OpenGL ES kernel </td></tr>
-<tr id="row_0_378_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_simple_kernel.xhtml" target="_self">IGCSimpleKernel</a></td><td class="desc">Interface for simple OpenGL ES kernels having 1 tensor input and 1 tensor output </td></tr>
-<tr id="row_0_379_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml" target="_self">IGCTensor</a></td><td class="desc">Interface for GLES Compute tensor </td></tr>
-<tr id="row_0_380_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_h_o_g.xhtml" target="_self">IHOG</a></td><td class="desc">Interface for <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-object </td></tr>
-<tr id="row_0_381_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_kernel.xhtml" target="_self">IKernel</a></td><td class="desc">Common information for all the kernels </td></tr>
-<tr id="row_0_382_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_lifetime_manager.xhtml" target="_self">ILifetimeManager</a></td><td class="desc">Interface for managing the lifetime of objects </td></tr>
-<tr id="row_0_383_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_lut.xhtml" target="_self">ILut</a></td><td class="desc">Lookup Table object interface </td></tr>
-<tr id="row_0_384_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_lut_allocator.xhtml" target="_self">ILutAllocator</a></td><td class="desc">Basic interface to allocate LUTs' </td></tr>
-<tr id="row_0_385_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_memory_group.xhtml" target="_self">IMemoryGroup</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> group interface </td></tr>
-<tr id="row_0_386_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml" target="_self">IMemoryManager</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> manager interface to handle allocations of backing memory </td></tr>
-<tr id="row_0_387_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_memory_pool.xhtml" target="_self">IMemoryPool</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> Pool Inteface </td></tr>
-<tr id="row_0_388_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_memory_region.xhtml" target="_self">IMemoryRegion</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> region interface </td></tr>
-<tr id="row_0_389_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_multi_h_o_g.xhtml" target="_self">IMultiHOG</a></td><td class="desc">Interface for storing multiple <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-objects </td></tr>
-<tr id="row_0_390_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_multi_image.xhtml" target="_self">IMultiImage</a></td><td class="desc">Interface for multi-planar images </td></tr>
-<tr id="row_0_391_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_g_e_m_m_lowp_reduction_kernel.xhtml" target="_self">INEGEMMLowpReductionKernel</a></td><td class="desc">Common interface for all NEON reduction kernels </td></tr>
-<tr id="row_0_392_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_harris_score_kernel.xhtml" target="_self">INEHarrisScoreKernel</a></td><td class="desc">Common interface for all Harris Score kernels </td></tr>
-<tr id="row_0_393_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_simple_function.xhtml" target="_self">INESimpleFunction</a></td><td class="desc">Basic interface for functions which have a single NEON kernel </td></tr>
-<tr id="row_0_394_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_warp_kernel.xhtml" target="_self">INEWarpKernel</a></td><td class="desc">Common interface for warp affine and warp perspective </td></tr>
-<tr id="row_0_395_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml" target="_self">INEWinogradLayerBatchedGEMMKernel</a></td><td class="desc">Interface for the NEON kernel to perform Winograd </td></tr>
-<tr id="row_0_396_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_input_kernel.xhtml" target="_self">INEWinogradLayerTransformInputKernel</a></td><td class="desc">Interface for the NEON kernel to perform Winograd input transform </td></tr>
-<tr id="row_0_397_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_output_kernel.xhtml" target="_self">INEWinogradLayerTransformOutputKernel</a></td><td class="desc">Interface for the NEON kernel to perform Winograd output transform </td></tr>
-<tr id="row_0_398_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel.xhtml" target="_self">INEWinogradLayerTransformWeightsKernel</a></td><td class="desc">Interface for the NEON kernel to perform Winograd weights transform </td></tr>
-<tr id="row_0_399_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_internal_key_point.xhtml" target="_self">InternalKeyPoint</a></td><td class="desc">Internal keypoint class for Lucas-Kanade Optical Flow </td></tr>
-<tr id="row_0_400_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_i_o_format_info.xhtml" target="_self">IOFormatInfo</a></td><td class="desc">IO formatting information class </td></tr>
-<tr id="row_0_401_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_pool_manager.xhtml" target="_self">IPoolManager</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> pool manager interface </td></tr>
-<tr id="row_0_402_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_pyramid.xhtml" target="_self">IPyramid</a></td><td class="desc">Interface for pyramid data-object </td></tr>
-<tr id="row_0_403_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_scheduler.xhtml" target="_self">IScheduler</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_scheduler.xhtml" title="Configurable scheduler which supports multiple multithreading APIs and choosing between different sch...">Scheduler</a> interface to run kernels </td></tr>
-<tr id="row_0_404_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_simple_lifetime_manager.xhtml" target="_self">ISimpleLifetimeManager</a></td><td class="desc">Abstract class of the simple lifetime manager interface </td></tr>
-<tr id="row_0_405_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_tensor.xhtml" target="_self">ITensor</a></td><td class="desc">Interface for NEON tensor </td></tr>
-<tr id="row_0_406_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_tensor_allocator.xhtml" target="_self">ITensorAllocator</a></td><td class="desc">Interface to allocate tensors </td></tr>
-<tr id="row_0_407_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml" target="_self">ITensorInfo</a></td><td class="desc">Store the tensor's metadata </td></tr>
-<tr id="row_0_408_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_iterator.xhtml" target="_self">Iterator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> updated by <a class="el" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a> for each window element </td></tr>
-<tr id="row_0_409_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_kernel.xhtml" target="_self">Kernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> class </td></tr>
-<tr id="row_0_410_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_key_point.xhtml" target="_self">KeyPoint</a></td><td class="desc"><a class="el" href="struct_keypoint.xhtml">Keypoint</a> type </td></tr>
-<tr id="row_0_411_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_l_s_t_m_params.xhtml" target="_self">LSTMParams</a></td><td class="desc"></td></tr>
-<tr id="row_0_412_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_lut.xhtml" target="_self">Lut</a></td><td class="desc">Basic implementation of the LUT interface </td></tr>
-<tr id="row_0_413_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_lut_allocator.xhtml" target="_self">LutAllocator</a></td><td class="desc">Basic implementation of a CPU memory LUT allocator </td></tr>
-<tr id="row_0_414_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_memory.xhtml" target="_self">Memory</a></td><td class="desc">CPU implementation of memory object </td></tr>
-<tr id="row_0_415_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_memory_group_base.xhtml" target="_self">MemoryGroupBase</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> group </td></tr>
-<tr id="row_0_416_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_memory_manager_on_demand.xhtml" target="_self">MemoryManagerOnDemand</a></td><td class="desc">On-demand memory manager </td></tr>
-<tr id="row_0_417_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_memory_region.xhtml" target="_self">MemoryRegion</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> region CPU implementation </td></tr>
-<tr id="row_0_418_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_min_max_location_values.xhtml" target="_self">MinMaxLocationValues</a></td><td class="desc">Min and max values and locations </td></tr>
-<tr id="row_0_419_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_multi_h_o_g.xhtml" target="_self">MultiHOG</a></td><td class="desc">CPU implementation of multi <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-object </td></tr>
-<tr id="row_0_420_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_multi_image.xhtml" target="_self">MultiImage</a></td><td class="desc">Basic implementation of the multi-planar image interface </td></tr>
-<tr id="row_0_421_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_multi_image_info.xhtml" target="_self">MultiImageInfo</a></td><td class="desc">Store the multi-planar image's metadata </td></tr>
-<tr id="row_0_422_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_absolute_difference.xhtml" target="_self">NEAbsoluteDifference</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_absolute_difference_kernel.xhtml">NEAbsoluteDifferenceKernel</a> </td></tr>
-<tr id="row_0_423_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_absolute_difference_kernel.xhtml" target="_self">NEAbsoluteDifferenceKernel</a></td><td class="desc">Interface for the absolute difference kernel </td></tr>
-<tr id="row_0_424_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate.xhtml" target="_self">NEAccumulate</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_accumulate_kernel.xhtml">NEAccumulateKernel</a> </td></tr>
-<tr id="row_0_425_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_kernel.xhtml" target="_self">NEAccumulateKernel</a></td><td class="desc">Interface for the accumulate kernel </td></tr>
-<tr id="row_0_426_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_squared.xhtml" target="_self">NEAccumulateSquared</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_accumulate_squared_kernel.xhtml">NEAccumulateSquaredKernel</a> </td></tr>
-<tr id="row_0_427_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_squared_kernel.xhtml" target="_self">NEAccumulateSquaredKernel</a></td><td class="desc">Interface for the accumulate squared kernel </td></tr>
-<tr id="row_0_428_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_weighted.xhtml" target="_self">NEAccumulateWeighted</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_accumulate_weighted_kernel.xhtml">NEAccumulateWeightedKernel</a> </td></tr>
-<tr id="row_0_429_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_weighted_kernel.xhtml" target="_self">NEAccumulateWeightedKernel</a></td><td class="desc">Interface for the accumulate weighted kernel </td></tr>
-<tr id="row_0_430_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_activation_layer.xhtml" target="_self">NEActivationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_activation_layer_kernel.xhtml">NEActivationLayerKernel</a> </td></tr>
-<tr id="row_0_431_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_activation_layer_kernel.xhtml" target="_self">NEActivationLayerKernel</a></td><td class="desc">Interface for the activation layer kernel </td></tr>
-<tr id="row_0_432_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_addition.xhtml" target="_self">NEArithmeticAddition</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_arithmetic_addition_kernel.xhtml">NEArithmeticAdditionKernel</a> </td></tr>
-<tr id="row_0_433_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_addition_kernel.xhtml" target="_self">NEArithmeticAdditionKernel</a></td><td class="desc">Interface for the kernel to perform addition between two tensors </td></tr>
-<tr id="row_0_434_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_subtraction.xhtml" target="_self">NEArithmeticSubtraction</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_arithmetic_subtraction_kernel.xhtml">NEArithmeticSubtractionKernel</a> </td></tr>
-<tr id="row_0_435_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_subtraction_kernel.xhtml" target="_self">NEArithmeticSubtractionKernel</a></td><td class="desc">Interface for the kernel to perform subtraction between two tensors </td></tr>
-<tr id="row_0_436_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_batch_normalization_layer.xhtml" target="_self">NEBatchNormalizationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_normalization_layer_kernel.xhtml">NENormalizationLayerKernel</a> and simulate a batch normalization layer </td></tr>
-<tr id="row_0_437_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_batch_normalization_layer_kernel.xhtml" target="_self">NEBatchNormalizationLayerKernel</a></td><td class="desc">Interface for the batch normalization layer kernel </td></tr>
-<tr id="row_0_438_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_and.xhtml" target="_self">NEBitwiseAnd</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_and_kernel.xhtml">NEBitwiseAndKernel</a> </td></tr>
-<tr id="row_0_439_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_and_kernel.xhtml" target="_self">NEBitwiseAndKernel</a></td><td class="desc">Interface for the kernel to perform bitwise AND between XY-planes of two tensors </td></tr>
-<tr id="row_0_440_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_not.xhtml" target="_self">NEBitwiseNot</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_not_kernel.xhtml">NEBitwiseNotKernel</a> </td></tr>
-<tr id="row_0_441_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_not_kernel.xhtml" target="_self">NEBitwiseNotKernel</a></td><td class="desc">Interface for the kernel to perform bitwise NOT operation </td></tr>
-<tr id="row_0_442_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_or.xhtml" target="_self">NEBitwiseOr</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_or_kernel.xhtml">NEBitwiseOrKernel</a> </td></tr>
-<tr id="row_0_443_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_or_kernel.xhtml" target="_self">NEBitwiseOrKernel</a></td><td class="desc">Interface for the kernel to perform bitwise inclusive OR between two tensors </td></tr>
-<tr id="row_0_444_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_xor.xhtml" target="_self">NEBitwiseXor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_xor_kernel.xhtml">NEBitwiseXorKernel</a> </td></tr>
-<tr id="row_0_445_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_xor_kernel.xhtml" target="_self">NEBitwiseXorKernel</a></td><td class="desc">Interface for the kernel to perform bitwise exclusive OR (XOR) between two tensors </td></tr>
-<tr id="row_0_446_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_box3x3.xhtml" target="_self">NEBox3x3</a></td><td class="desc">Basic function to execute box filter 3x3 </td></tr>
-<tr id="row_0_447_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_box3x3_kernel.xhtml" target="_self">NEBox3x3Kernel</a></td><td class="desc">NEON kernel to perform a Box 3x3 filter </td></tr>
-<tr id="row_0_448_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml" target="_self">NECannyEdge</a></td><td class="desc">Basic function to execute canny edge on NEON </td></tr>
-<tr id="row_0_449_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_combine.xhtml" target="_self">NEChannelCombine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_channel_combine_kernel.xhtml">NEChannelCombineKernel</a> to perform channel combination </td></tr>
-<tr id="row_0_450_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_combine_kernel.xhtml" target="_self">NEChannelCombineKernel</a></td><td class="desc">Interface for the channel combine kernel </td></tr>
-<tr id="row_0_451_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_extract.xhtml" target="_self">NEChannelExtract</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_channel_extract_kernel.xhtml">NEChannelExtractKernel</a> to perform channel extraction </td></tr>
-<tr id="row_0_452_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_extract_kernel.xhtml" target="_self">NEChannelExtractKernel</a></td><td class="desc">Interface for the channel extract kernel </td></tr>
-<tr id="row_0_453_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_col2_im.xhtml" target="_self">NECol2Im</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_col2_im.xhtml">NECol2Im</a> </td></tr>
-<tr id="row_0_454_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_col2_im_kernel.xhtml" target="_self">NECol2ImKernel</a></td><td class="desc">NEON kernel to perform col2im reshaping </td></tr>
-<tr id="row_0_455_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_color_convert.xhtml" target="_self">NEColorConvert</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_color_convert_kernel.xhtml">NEColorConvertKernel</a> to perform color conversion </td></tr>
-<tr id="row_0_456_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_color_convert_kernel.xhtml" target="_self">NEColorConvertKernel</a></td><td class="desc">Interface for the color convert kernel </td></tr>
-<tr id="row_0_457_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convert_fully_connected_weights.xhtml" target="_self">NEConvertFullyConnectedWeights</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_convert_fully_connected_weights_kernel.xhtml">NEConvertFullyConnectedWeightsKernel</a> </td></tr>
-<tr id="row_0_458_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convert_fully_connected_weights_kernel.xhtml" target="_self">NEConvertFullyConnectedWeightsKernel</a></td><td class="desc">Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa </td></tr>
-<tr id="row_0_459_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution3x3.xhtml" target="_self">NEConvolution3x3</a></td><td class="desc">Basic function to execute convolution of size 3x3 </td></tr>
-<tr id="row_0_460_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_kernel.xhtml" target="_self">NEConvolutionKernel</a></td><td class="desc">Interface for the kernel to run an arbitrary size convolution on a tensor </td></tr>
-<tr id="row_0_461_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml" target="_self">NEConvolutionLayer</a></td><td class="desc">Basic function to simulate a convolution layer </td></tr>
-<tr id="row_0_462_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_layer_reshape_weights.xhtml" target="_self">NEConvolutionLayerReshapeWeights</a></td><td class="desc">Function to reshape and perform 1xW transposition on the weights </td></tr>
-<tr id="row_0_463_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_rectangle.xhtml" target="_self">NEConvolutionRectangle</a></td><td class="desc">Basic function to execute non-square convolution </td></tr>
-<tr id="row_0_464_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_rectangle_kernel.xhtml" target="_self">NEConvolutionRectangleKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the running convolution on a rectangle matrix </td></tr>
-<tr id="row_0_465_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_square.xhtml" target="_self">NEConvolutionSquare</a></td><td class="desc">Basic function to execute convolution of size 5x5, 7x7, 9x9 </td></tr>
-<tr id="row_0_466_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_cumulative_distribution_kernel.xhtml" target="_self">NECumulativeDistributionKernel</a></td><td class="desc">Interface for the cumulative distribution (cummulative summmation) calculation kernel </td></tr>
-<tr id="row_0_467_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_deconvolution_layer.xhtml" target="_self">NEDeconvolutionLayer</a></td><td class="desc">Function to run the deconvolution layer </td></tr>
-<tr id="row_0_468_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_concatenate_layer.xhtml" target="_self">NEDepthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
-<tr id="row_0_469_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_concatenate_layer_kernel.xhtml" target="_self">NEDepthConcatenateLayerKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
-<tr id="row_0_470_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_convert_layer.xhtml" target="_self">NEDepthConvertLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_depth_convert_layer_kernel.xhtml">NEDepthConvertLayerKernel</a> </td></tr>
-<tr id="row_0_471_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_convert_layer_kernel.xhtml" target="_self">NEDepthConvertLayerKernel</a></td><td class="desc">Depth conversion kernel </td></tr>
-<tr id="row_0_472_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml" target="_self">NEDepthwiseConvolutionLayer</a></td><td class="desc">Basic function to execute a generic depthwise convolution </td></tr>
-<tr id="row_0_473_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3.xhtml" target="_self">NEDepthwiseConvolutionLayer3x3</a></td><td class="desc">Basic function to execute a depthwise convolution for kernel size 3x3xC </td></tr>
-<tr id="row_0_474_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml" target="_self">NEDepthwiseConvolutionLayer3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor </td></tr>
-<tr id="row_0_475_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_im2_col_kernel.xhtml" target="_self">NEDepthwiseIm2ColKernel</a></td><td class="desc">Interface for the depthwise im2col reshape kernel </td></tr>
-<tr id="row_0_476_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_separable_convolution_layer.xhtml" target="_self">NEDepthwiseSeparableConvolutionLayer</a></td><td class="desc">Basic function to execute depthwise convolution </td></tr>
-<tr id="row_0_477_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_vector_to_tensor_kernel.xhtml" target="_self">NEDepthwiseVectorToTensorKernel</a></td><td class="desc">Interface for the depthwise vector to tensor kernel </td></tr>
-<tr id="row_0_478_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_weights_reshape_kernel.xhtml" target="_self">NEDepthwiseWeightsReshapeKernel</a></td><td class="desc">Interface for the depthwise weights reshape kernel </td></tr>
-<tr id="row_0_479_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dequantization_layer.xhtml" target="_self">NEDequantizationLayer</a></td><td class="desc">Basic function to simulate a dequantization layer </td></tr>
-<tr id="row_0_480_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dequantization_layer_kernel.xhtml" target="_self">NEDequantizationLayerKernel</a></td><td class="desc">Interface for the dequantization layer kernel </td></tr>
-<tr id="row_0_481_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_derivative.xhtml" target="_self">NEDerivative</a></td><td class="desc">Basic function to execute first order derivative operator </td></tr>
-<tr id="row_0_482_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_derivative_kernel.xhtml" target="_self">NEDerivativeKernel</a></td><td class="desc">Interface for the kernel to run the derivative along the X/Y directions on a tensor </td></tr>
-<tr id="row_0_483_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dilate.xhtml" target="_self">NEDilate</a></td><td class="desc">Basic function to execute dilate </td></tr>
-<tr id="row_0_484_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dilate_kernel.xhtml" target="_self">NEDilateKernel</a></td><td class="desc">Interface for the kernel to perform boolean image dilatation </td></tr>
-<tr id="row_0_485_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer.xhtml" target="_self">NEDirectConvolutionLayer</a></td><td class="desc">Function to run the direct convolution </td></tr>
-<tr id="row_0_486_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml" target="_self">NEDirectConvolutionLayerKernel</a></td><td class="desc">NEON interface for Direct Convolution Layer kernel </td></tr>
-<tr id="row_0_487_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_output_stage_kernel.xhtml" target="_self">NEDirectConvolutionLayerOutputStageKernel</a></td><td class="desc">NEON kernel to accumulate the biases, if provided, or downscale in case of quantized input </td></tr>
-<tr id="row_0_488_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_edge_non_max_suppression_kernel.xhtml" target="_self">NEEdgeNonMaxSuppressionKernel</a></td><td class="desc">NEON kernel to perform Non-Maxima suppression for Canny Edge </td></tr>
-<tr id="row_0_489_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_edge_trace_kernel.xhtml" target="_self">NEEdgeTraceKernel</a></td><td class="desc">NEON kernel to perform Edge tracing </td></tr>
-<tr id="row_0_490_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_equalize_histogram.xhtml" target="_self">NEEqualizeHistogram</a></td><td class="desc">Basic function to execute histogram equalization </td></tr>
-<tr id="row_0_491_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_erode.xhtml" target="_self">NEErode</a></td><td class="desc">Basic function to execute erode </td></tr>
-<tr id="row_0_492_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_erode_kernel.xhtml" target="_self">NEErodeKernel</a></td><td class="desc">Interface for the kernel to perform boolean image erosion </td></tr>
-<tr id="row_0_493_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fast_corners.xhtml" target="_self">NEFastCorners</a></td><td class="desc">Basic function to execute fast corners </td></tr>
-<tr id="row_0_494_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fast_corners_kernel.xhtml" target="_self">NEFastCornersKernel</a></td><td class="desc">NEON kernel to perform fast corners </td></tr>
-<tr id="row_0_495_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_array_kernel.xhtml" target="_self">NEFillArrayKernel</a></td><td class="desc">This kernel adds all texels greater than or equal to the threshold value to the keypoint array </td></tr>
-<tr id="row_0_496_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_border.xhtml" target="_self">NEFillBorder</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml">NEFillBorderKernel</a> </td></tr>
-<tr id="row_0_497_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml" target="_self">NEFillBorderKernel</a></td><td class="desc">Interface for the kernel to fill borders </td></tr>
-<tr id="row_0_498_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_inner_border_kernel.xhtml" target="_self">NEFillInnerBorderKernel</a></td><td class="desc">Interface for the kernel to fill the interior borders </td></tr>
-<tr id="row_0_499_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_flatten_layer.xhtml" target="_self">NEFlattenLayer</a></td><td class="desc">Basic function to execute flatten </td></tr>
-<tr id="row_0_500_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_floor.xhtml" target="_self">NEFloor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_floor_kernel.xhtml">NEFloorKernel</a> </td></tr>
-<tr id="row_0_501_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_floor_kernel.xhtml" target="_self">NEFloorKernel</a></td><td class="desc">NEON kernel to perform a floor operation </td></tr>
-<tr id="row_0_502_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer.xhtml" target="_self">NEFullyConnectedLayer</a></td><td class="desc">Basic function to compute a Fully Connected layer on NEON </td></tr>
-<tr id="row_0_503_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer_reshape_weights.xhtml" target="_self">NEFullyConnectedLayerReshapeWeights</a></td><td class="desc">Basic function to reshape the weights of Fully Connected layer with NEON </td></tr>
-<tr id="row_0_504_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian3x3.xhtml" target="_self">NEGaussian3x3</a></td><td class="desc">Basic function to execute gaussian filter 3x3 </td></tr>
-<tr id="row_0_505_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian3x3_kernel.xhtml" target="_self">NEGaussian3x3Kernel</a></td><td class="desc">NEON kernel to perform a Gaussian 3x3 filter </td></tr>
-<tr id="row_0_506_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian5x5.xhtml" target="_self">NEGaussian5x5</a></td><td class="desc">Basic function to execute gaussian filter 5x5 </td></tr>
-<tr id="row_0_507_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian5x5_hor_kernel.xhtml" target="_self">NEGaussian5x5HorKernel</a></td><td class="desc">NEON kernel to perform a Gaussian 5x5 filter (horizontal pass) </td></tr>
-<tr id="row_0_508_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian5x5_vert_kernel.xhtml" target="_self">NEGaussian5x5VertKernel</a></td><td class="desc">NEON kernel to perform a Gaussian 5x5 filter (vertical pass) </td></tr>
-<tr id="row_0_509_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid.xhtml" target="_self">NEGaussianPyramid</a></td><td class="desc">Common interface for all Gaussian pyramid functions </td></tr>
-<tr id="row_0_510_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_half.xhtml" target="_self">NEGaussianPyramidHalf</a></td><td class="desc">Basic function to execute gaussian pyramid with HALF scale factor </td></tr>
-<tr id="row_0_511_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_hor_kernel.xhtml" target="_self">NEGaussianPyramidHorKernel</a></td><td class="desc">NEON kernel to perform a GaussianPyramid (horizontal pass) </td></tr>
-<tr id="row_0_512_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_orb.xhtml" target="_self">NEGaussianPyramidOrb</a></td><td class="desc">Basic function to execute gaussian pyramid with ORB scale factor </td></tr>
-<tr id="row_0_513_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_vert_kernel.xhtml" target="_self">NEGaussianPyramidVertKernel</a></td><td class="desc">NEON kernel to perform a GaussianPyramid (vertical pass) </td></tr>
-<tr id="row_0_514_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m.xhtml" target="_self">NEGEMM</a></td><td class="desc">Basic function to execute GEMM on NEON </td></tr>
-<tr id="row_0_515_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_assembly_base_kernel.xhtml" target="_self">NEGEMMAssemblyBaseKernel</a></td><td class="desc">Base class for GEMM NEON kernels implemented in Assembly </td></tr>
-<tr id="row_0_516_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_convolution_layer.xhtml" target="_self">NEGEMMConvolutionLayer</a></td><td class="desc">Basic function to simulate a convolution layer </td></tr>
-<tr id="row_0_517_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_interleave4x4.xhtml" target="_self">NEGEMMInterleave4x4</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_interleave4x4_kernel.xhtml" title="NEON kernel to interleave the elements of a matrix. ">NEGEMMInterleave4x4Kernel</a> </td></tr>
-<tr id="row_0_518_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_interleave4x4_kernel.xhtml" target="_self">NEGEMMInterleave4x4Kernel</a></td><td class="desc">NEON kernel to interleave the elements of a matrix </td></tr>
-<tr id="row_0_519_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_assembly_matrix_multiply_core.xhtml" target="_self">NEGEMMLowpAssemblyMatrixMultiplyCore</a></td><td class="desc">Basic function to execute matrix multiply assembly kernels </td></tr>
-<tr id="row_0_520_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_a_reduction_kernel.xhtml" target="_self">NEGEMMLowpMatrixAReductionKernel</a></td><td class="desc">NEON kernel used to compute the row-vectors of sums of all the entries in each row of Matrix A </td></tr>
-<tr id="row_0_521_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_b_reduction_kernel.xhtml" target="_self">NEGEMMLowpMatrixBReductionKernel</a></td><td class="desc">NEON kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B </td></tr>
-<tr id="row_0_522_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_multiply_core.xhtml" target="_self">NEGEMMLowpMatrixMultiplyCore</a></td><td class="desc">Basic function to execute GEMMLowpMatrixMultiplyCore on NEON </td></tr>
-<tr id="row_0_523_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_multiply_kernel.xhtml" target="_self">NEGEMMLowpMatrixMultiplyKernel</a></td><td class="desc">NEON kernel to multiply matrices </td></tr>
-<tr id="row_0_524_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_offset_contribution_kernel.xhtml" target="_self">NEGEMMLowpOffsetContributionKernel</a></td><td class="desc">NEON kernel used to add the offset contribution after <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_multiply_kernel.xhtml">NEGEMMLowpMatrixMultiplyKernel</a> </td></tr>
-<tr id="row_0_525_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8Scale</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" title="Basic function to execute NEGEMMLowpQuantizeDownInt32ToUint8Scale on NEON. ">NEGEMMLowpQuantizeDownInt32ToUint8Scale</a> on NEON </td></tr>
-<tr id="row_0_526_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" title="Basic function to execute NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint on NEON. ">NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a> on NEON </td></tr>
-<tr id="row_0_527_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point_kernel.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel</a></td><td class="desc">NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 </td></tr>
-<tr id="row_0_528_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_kernel.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel</a></td><td class="desc">NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 </td></tr>
-<tr id="row_0_529_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_accumulate_biases_kernel.xhtml" target="_self">NEGEMMMatrixAccumulateBiasesKernel</a></td><td class="desc">NEON kernel to add a bias to each row of the input tensor </td></tr>
-<tr id="row_0_530_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_addition_kernel.xhtml" target="_self">NEGEMMMatrixAdditionKernel</a></td><td class="desc">NEON kernel to perform the in-place matrix addition between 2 matrices taking into account that the second matrix might be weighted by a scalar value beta: </td></tr>
-<tr id="row_0_531_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_multiply_kernel.xhtml" target="_self">NEGEMMMatrixMultiplyKernel</a></td><td class="desc">NEON kernel to multiply two input matrices "A" and "B" </td></tr>
-<tr id="row_0_532_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_vector_multiply_kernel.xhtml" target="_self">NEGEMMMatrixVectorMultiplyKernel</a></td><td class="desc">Interface for the GEMM matrix vector multiply kernel </td></tr>
-<tr id="row_0_533_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_transpose1x_w.xhtml" target="_self">NEGEMMTranspose1xW</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_transpose1x_w_kernel.xhtml" title="NEON kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / ele...">NEGEMMTranspose1xWKernel</a> </td></tr>
-<tr id="row_0_534_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_transpose1x_w_kernel.xhtml" target="_self">NEGEMMTranspose1xWKernel</a></td><td class="desc">NEON kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / element size of the tensor) </td></tr>
-<tr id="row_0_535_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gradient_kernel.xhtml" target="_self">NEGradientKernel</a></td><td class="desc">Computes magnitude and quantised phase from inputs gradients </td></tr>
-<tr id="row_0_536_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_harris_corners.xhtml" target="_self">NEHarrisCorners</a></td><td class="desc">Basic function to execute harris corners detection </td></tr>
-<tr id="row_0_537_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_harris_score_kernel.xhtml" target="_self">NEHarrisScoreKernel</a></td><td class="desc">Template NEON kernel to perform Harris Score </td></tr>
-<tr id="row_0_538_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_histogram.xhtml" target="_self">NEHistogram</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_histogram_kernel.xhtml">NEHistogramKernel</a> </td></tr>
-<tr id="row_0_539_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_histogram_kernel.xhtml" target="_self">NEHistogramKernel</a></td><td class="desc">Interface for the histogram kernel </td></tr>
-<tr id="row_0_540_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_block_normalization_kernel.xhtml" target="_self">NEHOGBlockNormalizationKernel</a></td><td class="desc">NEON kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> block normalization </td></tr>
-<tr id="row_0_541_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_descriptor.xhtml" target="_self">NEHOGDescriptor</a></td><td class="desc">Basic function to calculate <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> descriptor </td></tr>
-<tr id="row_0_542_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_detector.xhtml" target="_self">NEHOGDetector</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector based on linear SVM </td></tr>
-<tr id="row_0_543_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_detector_kernel.xhtml" target="_self">NEHOGDetectorKernel</a></td><td class="desc">NEON kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector kernel using linear SVM </td></tr>
-<tr id="row_0_544_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_gradient.xhtml" target="_self">NEHOGGradient</a></td><td class="desc">Basic function to calculate the gradient for <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
-<tr id="row_0_545_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_multi_detection.xhtml" target="_self">NEHOGMultiDetection</a></td><td class="desc">Basic function to detect multiple objects (or the same object at different scales) on the same input image using <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
-<tr id="row_0_546_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_orientation_binning_kernel.xhtml" target="_self">NEHOGOrientationBinningKernel</a></td><td class="desc">NEON kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> Orientation Binning </td></tr>
-<tr id="row_0_547_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_im2_col.xhtml" target="_self">NEIm2Col</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_im2_col_kernel.xhtml">NEIm2ColKernel</a> </td></tr>
-<tr id="row_0_548_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_im2_col_kernel.xhtml" target="_self">NEIm2ColKernel</a></td><td class="desc">Interface for the im2col reshape kernel </td></tr>
-<tr id="row_0_549_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_integral_image.xhtml" target="_self">NEIntegralImage</a></td><td class="desc">Basic function to run a <a class="el" href="classarm__compute_1_1_n_e_integral_image_kernel.xhtml">NEIntegralImageKernel</a> </td></tr>
-<tr id="row_0_550_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_integral_image_kernel.xhtml" target="_self">NEIntegralImageKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> to perform an image integral on an image </td></tr>
-<tr id="row_0_551_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_l2_normalize_layer.xhtml" target="_self">NEL2NormalizeLayer</a></td><td class="desc">Basic function to perform a L2 normalization on a given axis </td></tr>
-<tr id="row_0_552_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_l2_normalize_layer_kernel.xhtml" target="_self">NEL2NormalizeLayerKernel</a></td><td class="desc">Interface for performing a L2 normalize on a given axis given the square sum of it in this axis </td></tr>
-<tr id="row_0_553_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_laplacian_pyramid.xhtml" target="_self">NELaplacianPyramid</a></td><td class="desc">Basic function to execute laplacian pyramid </td></tr>
-<tr id="row_0_554_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_laplacian_reconstruct.xhtml" target="_self">NELaplacianReconstruct</a></td><td class="desc">Basic function to execute laplacian reconstruction </td></tr>
-<tr id="row_0_555_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_n_e_l_k_internal_keypoint.xhtml" target="_self">NELKInternalKeypoint</a></td><td class="desc">Internal keypoint class for Lucas-Kanade Optical Flow </td></tr>
-<tr id="row_0_556_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_l_k_tracker_kernel.xhtml" target="_self">NELKTrackerKernel</a></td><td class="desc">Interface for the Lucas-Kanade tracker kernel </td></tr>
-<tr id="row_0_557_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_locally_connected_layer.xhtml" target="_self">NELocallyConnectedLayer</a></td><td class="desc">Basic function to compute the locally connected layer </td></tr>
-<tr id="row_0_558_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_locally_connected_matrix_multiply_kernel.xhtml" target="_self">NELocallyConnectedMatrixMultiplyKernel</a></td><td class="desc">NEON kernel to multiply each row of first tensor with low 2 dimensions of second tensor </td></tr>
-<tr id="row_0_559_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_logits1_d_max_kernel.xhtml" target="_self">NELogits1DMaxKernel</a></td><td class="desc">Interface for the identifying the max value of 1D Logits </td></tr>
-<tr id="row_0_560_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_logits1_d_softmax_kernel.xhtml" target="_self">NELogits1DSoftmaxKernel</a></td><td class="desc">Interface for softmax computation for QASYMM8 with pre-computed max </td></tr>
-<tr id="row_0_561_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_magnitude.xhtml" target="_self">NEMagnitude</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_kernel.xhtml" title="Template interface for the kernel to compute magnitude and phase. ">NEMagnitudePhaseKernel</a> </td></tr>
-<tr id="row_0_562_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_kernel.xhtml" target="_self">NEMagnitudePhaseKernel</a></td><td class="desc">Template interface for the kernel to compute magnitude and phase </td></tr>
-<tr id="row_0_563_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_mean_std_dev.xhtml" target="_self">NEMeanStdDev</a></td><td class="desc">Basic function to execute mean and std deviation </td></tr>
-<tr id="row_0_564_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_mean_std_dev_kernel.xhtml" target="_self">NEMeanStdDevKernel</a></td><td class="desc">Interface for the kernel to calculate mean and standard deviation of input image pixels </td></tr>
-<tr id="row_0_565_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_median3x3.xhtml" target="_self">NEMedian3x3</a></td><td class="desc">Basic function to execute median filter </td></tr>
-<tr id="row_0_566_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_median3x3_kernel.xhtml" target="_self">NEMedian3x3Kernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> to perform a median filter on a tensor </td></tr>
-<tr id="row_0_567_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_kernel.xhtml" target="_self">NEMinMaxKernel</a></td><td class="desc">Interface for the kernel to perform min max search on an image </td></tr>
-<tr id="row_0_568_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_layer_kernel.xhtml" target="_self">NEMinMaxLayerKernel</a></td><td class="desc">Interface for the kernel to perform min max search on a 3D tensor </td></tr>
-<tr id="row_0_569_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_location.xhtml" target="_self">NEMinMaxLocation</a></td><td class="desc">Basic function to execute min and max location </td></tr>
-<tr id="row_0_570_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_location_kernel.xhtml" target="_self">NEMinMaxLocationKernel</a></td><td class="desc">Interface for the kernel to find min max locations of an image </td></tr>
-<tr id="row_0_571_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_linear_filter.xhtml" target="_self">NENonLinearFilter</a></td><td class="desc">Basic function to execute non linear filter </td></tr>
-<tr id="row_0_572_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_linear_filter_kernel.xhtml" target="_self">NENonLinearFilterKernel</a></td><td class="desc">Interface for the kernel to apply a non-linear filter </td></tr>
-<tr id="row_0_573_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_maxima_suppression3x3.xhtml" target="_self">NENonMaximaSuppression3x3</a></td><td class="desc">Basic function to execute non-maxima suppression over a 3x3 window </td></tr>
-<tr id="row_0_574_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_maxima_suppression3x3_kernel.xhtml" target="_self">NENonMaximaSuppression3x3Kernel</a></td><td class="desc">Interface to perform Non-Maxima suppression over a 3x3 window using NEON </td></tr>
-<tr id="row_0_575_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_normalization_layer.xhtml" target="_self">NENormalizationLayer</a></td><td class="desc">Basic function to compute a normalization layer </td></tr>
-<tr id="row_0_576_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_normalization_layer_kernel.xhtml" target="_self">NENormalizationLayerKernel</a></td><td class="desc">Interface for the normalization layer kernel </td></tr>
-<tr id="row_0_577_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_optical_flow.xhtml" target="_self">NEOpticalFlow</a></td><td class="desc">Basic function to execute optical flow </td></tr>
-<tr id="row_0_578_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_permute.xhtml" target="_self">NEPermute</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_permute_kernel.xhtml">NEPermuteKernel</a> </td></tr>
-<tr id="row_0_579_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_permute_kernel.xhtml" target="_self">NEPermuteKernel</a></td><td class="desc">NEON kernel to perform tensor permutation </td></tr>
-<tr id="row_0_580_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_phase.xhtml" target="_self">NEPhase</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_kernel.xhtml" title="Template interface for the kernel to compute magnitude and phase. ">NEMagnitudePhaseKernel</a> </td></tr>
-<tr id="row_0_581_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pixel_wise_multiplication.xhtml" target="_self">NEPixelWiseMultiplication</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_pixel_wise_multiplication_kernel.xhtml">NEPixelWiseMultiplicationKernel</a> </td></tr>
-<tr id="row_0_582_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pixel_wise_multiplication_kernel.xhtml" target="_self">NEPixelWiseMultiplicationKernel</a></td><td class="desc">Interface for the kernel to perform addition between two tensors </td></tr>
-<tr id="row_0_583_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pooling_layer.xhtml" target="_self">NEPoolingLayer</a></td><td class="desc">Basic function to simulate a pooling layer with the specified pooling operation </td></tr>
-<tr id="row_0_584_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pooling_layer_kernel.xhtml" target="_self">NEPoolingLayerKernel</a></td><td class="desc">Interface for the pooling layer kernel </td></tr>
-<tr id="row_0_585_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_quantization_layer.xhtml" target="_self">NEQuantizationLayer</a></td><td class="desc">Basic function to simulate a quantization layer </td></tr>
-<tr id="row_0_586_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_quantization_layer_kernel.xhtml" target="_self">NEQuantizationLayerKernel</a></td><td class="desc">Interface for the quantization layer kernel </td></tr>
-<tr id="row_0_587_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reduction_operation.xhtml" target="_self">NEReductionOperation</a></td><td class="desc">Basic function to simulate a reduction operation </td></tr>
-<tr id="row_0_588_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reduction_operation_kernel.xhtml" target="_self">NEReductionOperationKernel</a></td><td class="desc">NEON kernel to perform a reduction operation </td></tr>
-<tr id="row_0_589_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_remap.xhtml" target="_self">NERemap</a></td><td class="desc">Basic function to execute remap </td></tr>
-<tr id="row_0_590_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_remap_kernel.xhtml" target="_self">NERemapKernel</a></td><td class="desc">NEON kernel to perform a remap on a tensor </td></tr>
-<tr id="row_0_591_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reshape_layer.xhtml" target="_self">NEReshapeLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_reshape_layer_kernel.xhtml">NEReshapeLayerKernel</a> </td></tr>
-<tr id="row_0_592_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reshape_layer_kernel.xhtml" target="_self">NEReshapeLayerKernel</a></td><td class="desc">Interface for the kernel to perform tensor reshaping </td></tr>
-<tr id="row_0_593_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer.xhtml" target="_self">NEROIPoolingLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer_kernel.xhtml">NEROIPoolingLayerKernel</a> </td></tr>
-<tr id="row_0_594_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer_kernel.xhtml" target="_self">NEROIPoolingLayerKernel</a></td><td class="desc">Interface for the <a class="el" href="structarm__compute_1_1_r_o_i.xhtml" title="Region of interest. ">ROI</a> pooling layer kernel </td></tr>
-<tr id="row_0_595_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scale.xhtml" target="_self">NEScale</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_scale_kernel.xhtml">NEScaleKernel</a> </td></tr>
-<tr id="row_0_596_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scale_kernel.xhtml" target="_self">NEScaleKernel</a></td><td class="desc">NEON kernel to perform scaling on a tensor </td></tr>
-<tr id="row_0_597_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scharr3x3.xhtml" target="_self">NEScharr3x3</a></td><td class="desc">Basic function to execute scharr 3x3 filter </td></tr>
-<tr id="row_0_598_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scharr3x3_kernel.xhtml" target="_self">NEScharr3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Scharr filter on a tensor </td></tr>
-<tr id="row_0_599_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_separable_convolution_hor_kernel.xhtml" target="_self">NESeparableConvolutionHorKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the Horizontal pass of a Separable Convolution </td></tr>
-<tr id="row_0_600_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_separable_convolution_vert_kernel.xhtml" target="_self">NESeparableConvolutionVertKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the Vertical pass of a Separable Convolution </td></tr>
-<tr id="row_0_601_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel3x3.xhtml" target="_self">NESobel3x3</a></td><td class="desc">Basic function to execute sobel 3x3 filter </td></tr>
-<tr id="row_0_602_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel3x3_kernel.xhtml" target="_self">NESobel3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Sobel X filter on a tensor </td></tr>
-<tr id="row_0_603_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel5x5.xhtml" target="_self">NESobel5x5</a></td><td class="desc">Basic function to execute sobel 5x5 filter </td></tr>
-<tr id="row_0_604_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel5x5_hor_kernel.xhtml" target="_self">NESobel5x5HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 5x5 Sobel filter on a tensor </td></tr>
-<tr id="row_0_605_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel5x5_vert_kernel.xhtml" target="_self">NESobel5x5VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 5x5 Sobel Y filter on a tensor </td></tr>
-<tr id="row_0_606_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel7x7.xhtml" target="_self">NESobel7x7</a></td><td class="desc">Basic function to execute sobel 7x7 filter </td></tr>
-<tr id="row_0_607_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel7x7_hor_kernel.xhtml" target="_self">NESobel7x7HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 7x7 Sobel filter on a tensor </td></tr>
-<tr id="row_0_608_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel7x7_vert_kernel.xhtml" target="_self">NESobel7x7VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 7x7 Sobel Y filter on a tensor </td></tr>
-<tr id="row_0_609_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_softmax_layer.xhtml" target="_self">NESoftmaxLayer</a></td><td class="desc">Basic function to compute a SoftmaxLayer </td></tr>
-<tr id="row_0_610_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_table_lookup.xhtml" target="_self">NETableLookup</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_table_lookup_kernel.xhtml">NETableLookupKernel</a> </td></tr>
-<tr id="row_0_611_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_table_lookup_kernel.xhtml" target="_self">NETableLookupKernel</a></td><td class="desc">Interface for the kernel to perform table lookup calculations </td></tr>
-<tr id="row_0_612_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_threshold.xhtml" target="_self">NEThreshold</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_threshold_kernel.xhtml">NEThresholdKernel</a> </td></tr>
-<tr id="row_0_613_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_threshold_kernel.xhtml" target="_self">NEThresholdKernel</a></td><td class="desc">Interface for the thresholding kernel </td></tr>
-<tr id="row_0_614_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_transpose.xhtml" target="_self">NETranspose</a></td><td class="desc">Basic function to transpose a matrix on NEON </td></tr>
-<tr id="row_0_615_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_transpose_kernel.xhtml" target="_self">NETransposeKernel</a></td><td class="desc">NEON kernel which transposes the elements of a matrix </td></tr>
-<tr id="row_0_616_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_affine.xhtml" target="_self">NEWarpAffine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_warp_affine_kernel.xhtml">NEWarpAffineKernel</a> </td></tr>
-<tr id="row_0_617_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_affine_kernel.xhtml" target="_self">NEWarpAffineKernel</a></td><td class="desc">Template interface for the kernel to compute warp affine </td></tr>
-<tr id="row_0_618_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_perspective.xhtml" target="_self">NEWarpPerspective</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_warp_perspective_kernel.xhtml">NEWarpPerspectiveKernel</a> </td></tr>
-<tr id="row_0_619_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_perspective_kernel.xhtml" target="_self">NEWarpPerspectiveKernel</a></td><td class="desc">Template interface for the kernel to compute warp perspective </td></tr>
-<tr id="row_0_620_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_weights_reshape_kernel.xhtml" target="_self">NEWeightsReshapeKernel</a></td><td class="desc">NEON kernel to perform reshaping on the weights used by convolution and locally connected layer </td></tr>
-<tr id="row_0_621_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_convolution_layer.xhtml" target="_self">NEWinogradConvolutionLayer</a></td><td class="desc">Basic function to simulate a convolution layer </td></tr>
-<tr id="row_0_622_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml" target="_self">NEWinogradLayerBatchedGEMMKernel</a></td><td class="desc">NEON kernel to perform Winograd </td></tr>
-<tr id="row_0_623_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_input_kernel.xhtml" target="_self">NEWinogradLayerTransformInputKernel</a></td><td class="desc">NEON kernel to perform Winograd input transform </td></tr>
-<tr id="row_0_624_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_output_kernel.xhtml" target="_self">NEWinogradLayerTransformOutputKernel</a></td><td class="desc">NEON kernel to perform Winograd output transform </td></tr>
-<tr id="row_0_625_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml" target="_self">NEWinogradLayerTransformWeightsKernel</a></td><td class="desc">NEON kernel to perform Winograd weights transform </td></tr>
-<tr id="row_0_626_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_normalization_layer_info.xhtml" target="_self">NormalizationLayerInfo</a></td><td class="desc">Normalization Layer Information class </td></tr>
-<tr id="row_0_627_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_offset_lifetime_manager.xhtml" target="_self">OffsetLifetimeManager</a></td><td class="desc">Concrete class that tracks the lifetime of registered tensors and calculates the systems memory requirements in terms of a single blob and a list of offsets </td></tr>
-<tr id="row_0_628_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_offset_memory_pool.xhtml" target="_self">OffsetMemoryPool</a></td><td class="desc">Offset based memory pool </td></tr>
-<tr id="row_0_629_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_o_m_p_scheduler.xhtml" target="_self">OMPScheduler</a></td><td class="desc">Pool of threads to automatically split a kernel's execution among several threads </td></tr>
-<tr id="row_0_630_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_optical_flow_parameters.xhtml" target="_self">OpticalFlowParameters</a></td><td class="desc">Parameters of Optical Flow algorithm </td></tr>
-<tr id="row_0_631_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml" target="_self">PadStrideInfo</a></td><td class="desc">Padding and stride information class </td></tr>
-<tr id="row_0_632_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pixel_value.xhtml" target="_self">PixelValue</a></td><td class="desc">Class describing the value of a pixel for any image format </td></tr>
-<tr id="row_0_633_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pooling_layer_info.xhtml" target="_self">PoolingLayerInfo</a></td><td class="desc">Pooling Layer Information class </td></tr>
-<tr id="row_0_634_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pool_manager.xhtml" target="_self">PoolManager</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> pool manager </td></tr>
-<tr id="row_0_635_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_program.xhtml" target="_self">Program</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_program.xhtml" title="Program class. ">Program</a> class </td></tr>
-<tr id="row_0_636_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pyramid.xhtml" target="_self">Pyramid</a></td><td class="desc">Basic implementation of the pyramid interface </td></tr>
-<tr id="row_0_637_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pyramid_info.xhtml" target="_self">PyramidInfo</a></td><td class="desc">Store the <a class="el" href="classarm__compute_1_1_pyramid.xhtml" title="Basic implementation of the pyramid interface. ">Pyramid</a>'s metadata </td></tr>
-<tr id="row_0_638_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_quantization_info.xhtml" target="_self">QuantizationInfo</a></td><td class="desc">Quantization settings (used for QASYMM8 data type) </td></tr>
-<tr id="row_0_639_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_rectangle.xhtml" target="_self">Rectangle</a></td><td class="desc"><a class="el" href="structarm__compute_1_1_rectangle.xhtml" title="Rectangle type. ">Rectangle</a> type </td></tr>
-<tr id="row_0_640_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_r_o_i.xhtml" target="_self">ROI</a></td><td class="desc">Region of interest </td></tr>
-<tr id="row_0_641_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_r_o_i_pooling_layer_info.xhtml" target="_self">ROIPoolingLayerInfo</a></td><td class="desc"><a class="el" href="structarm__compute_1_1_r_o_i.xhtml" title="Region of interest. ">ROI</a> Pooling Layer Information class </td></tr>
-<tr id="row_0_642_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_scheduler.xhtml" target="_self">Scheduler</a></td><td class="desc">Configurable scheduler which supports multiple multithreading APIs and choosing between different schedulers at runtime </td></tr>
-<tr id="row_0_643_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_semaphore.xhtml" target="_self">Semaphore</a></td><td class="desc">Semamphore class </td></tr>
-<tr id="row_0_644_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_single_thread_scheduler.xhtml" target="_self">SingleThreadScheduler</a></td><td class="desc">Pool of threads to automatically split a kernel's execution among several threads </td></tr>
-<tr id="row_0_645_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_size2_d.xhtml" target="_self">Size2D</a></td><td class="desc">Class for specifying the size of an image or rectangle </td></tr>
-<tr id="row_0_646_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_status.xhtml" target="_self">Status</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_status.xhtml" title="Status class. ">Status</a> class </td></tr>
-<tr id="row_0_647_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_steps.xhtml" target="_self">Steps</a></td><td class="desc">Class to describe a number of elements in each dimension </td></tr>
-<tr id="row_0_648_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_strides.xhtml" target="_self">Strides</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_strides.xhtml" title="Strides of an item in bytes. ">Strides</a> of an item in bytes </td></tr>
-<tr id="row_0_649_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_sub_tensor.xhtml" target="_self">SubTensor</a></td><td class="desc">Basic implementation of the sub-tensor interface </td></tr>
-<tr id="row_0_650_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_sub_tensor_info.xhtml" target="_self">SubTensorInfo</a></td><td class="desc">Store the sub tensor's metadata </td></tr>
-<tr id="row_0_651_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_tensor.xhtml" target="_self">Tensor</a></td><td class="desc">Basic implementation of the tensor interface </td></tr>
-<tr id="row_0_652_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_tensor_allocator.xhtml" target="_self">TensorAllocator</a></td><td class="desc">Basic implementation of a CPU memory tensor allocator </td></tr>
-<tr id="row_0_653_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_tensor_info.xhtml" target="_self">TensorInfo</a></td><td class="desc">Store the tensor's metadata </td></tr>
-<tr id="row_0_654_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_tensor_shape.xhtml" target="_self">TensorShape</a></td><td class="desc">Shape of a tensor </td></tr>
-<tr id="row_0_655_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_thread_info.xhtml" target="_self">ThreadInfo</a></td><td class="desc">Information about executing thread and CPU </td></tr>
-<tr id="row_0_656_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_valid_region.xhtml" target="_self">ValidRegion</a></td><td class="desc">Container for valid region of a window </td></tr>
-<tr id="row_0_657_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_weights_info.xhtml" target="_self">WeightsInfo</a></td><td class="desc">Convolution Layer Weights Information class </td></tr>
-<tr id="row_0_658_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_658_" class="arrow" onclick="toggleFolder('0_658_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_window.xhtml" target="_self">Window</a></td><td class="desc">Describe a multidimensional execution window </td></tr>
-<tr id="row_0_658_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_window_1_1_dimension.xhtml" target="_self">Dimension</a></td><td class="desc">Describe one of the image's dimensions with a start, end and step </td></tr>
-<tr id="row_0_659_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_winograd_info.xhtml" target="_self">WinogradInfo</a></td><td class="desc">Winograd information </td></tr>
+<tr id="row_0_24_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_blob_lifetime_manager.xhtml" target="_self">BlobLifetimeManager</a></td><td class="desc">Concrete class that tracks the lifetime of registered tensors and calculates the systems memory requirements in terms of blobs </td></tr>
+<tr id="row_0_25_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_blob_memory_pool.xhtml" target="_self">BlobMemoryPool</a></td><td class="desc">Blob memory pool </td></tr>
+<tr id="row_0_26_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_border_size.xhtml" target="_self">BorderSize</a></td><td class="desc">Container for 2D border size </td></tr>
+<tr id="row_0_27_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_absolute_difference.xhtml" target="_self">CLAbsoluteDifference</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_absolute_difference_kernel.xhtml">CLAbsoluteDifferenceKernel</a> </td></tr>
+<tr id="row_0_28_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_absolute_difference_kernel.xhtml" target="_self">CLAbsoluteDifferenceKernel</a></td><td class="desc">Interface for the absolute difference kernel </td></tr>
+<tr id="row_0_29_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate.xhtml" target="_self">CLAccumulate</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml">CLAccumulateKernel</a> </td></tr>
+<tr id="row_0_30_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml" target="_self">CLAccumulateKernel</a></td><td class="desc">Interface for the accumulate kernel </td></tr>
+<tr id="row_0_31_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_squared.xhtml" target="_self">CLAccumulateSquared</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_accumulate_squared_kernel.xhtml">CLAccumulateSquaredKernel</a> </td></tr>
+<tr id="row_0_32_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_squared_kernel.xhtml" target="_self">CLAccumulateSquaredKernel</a></td><td class="desc">Interface for the accumulate squared kernel </td></tr>
+<tr id="row_0_33_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_weighted.xhtml" target="_self">CLAccumulateWeighted</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml">CLAccumulateWeightedKernel</a> </td></tr>
+<tr id="row_0_34_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml" target="_self">CLAccumulateWeightedKernel</a></td><td class="desc">Interface for the accumulate weighted kernel </td></tr>
+<tr id="row_0_35_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_activation_layer.xhtml" target="_self">CLActivationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_activation_layer_kernel.xhtml">CLActivationLayerKernel</a> </td></tr>
+<tr id="row_0_36_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_activation_layer_kernel.xhtml" target="_self">CLActivationLayerKernel</a></td><td class="desc">Interface for the activation layer kernel </td></tr>
+<tr id="row_0_37_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_addition.xhtml" target="_self">CLArithmeticAddition</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_arithmetic_addition_kernel.xhtml">CLArithmeticAdditionKernel</a> </td></tr>
+<tr id="row_0_38_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_addition_kernel.xhtml" target="_self">CLArithmeticAdditionKernel</a></td><td class="desc">Interface for the arithmetic addition kernel </td></tr>
+<tr id="row_0_39_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_division.xhtml" target="_self">CLArithmeticDivision</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_arithmetic_division_kernel.xhtml">CLArithmeticDivisionKernel</a> </td></tr>
+<tr id="row_0_40_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_division_kernel.xhtml" target="_self">CLArithmeticDivisionKernel</a></td><td class="desc">Interface for the arithmetic division kernel </td></tr>
+<tr id="row_0_41_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_subtraction.xhtml" target="_self">CLArithmeticSubtraction</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_arithmetic_subtraction_kernel.xhtml">CLArithmeticSubtractionKernel</a> </td></tr>
+<tr id="row_0_42_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_subtraction_kernel.xhtml" target="_self">CLArithmeticSubtractionKernel</a></td><td class="desc">Interface for the arithmetic subtraction kernel </td></tr>
+<tr id="row_0_43_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_array.xhtml" target="_self">CLArray</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_c_l_array.xhtml" title="CLArray implementation. ">CLArray</a> implementation </td></tr>
+<tr id="row_0_44_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml" target="_self">CLBatchNormalizationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_normalization_layer_kernel.xhtml">CLNormalizationLayerKernel</a> and simulate a batch normalization layer </td></tr>
+<tr id="row_0_45_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer_kernel.xhtml" target="_self">CLBatchNormalizationLayerKernel</a></td><td class="desc">Interface for the BatchNormalization layer kernel </td></tr>
+<tr id="row_0_46_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_and.xhtml" target="_self">CLBitwiseAnd</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_and_kernel.xhtml">CLBitwiseAndKernel</a> </td></tr>
+<tr id="row_0_47_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_and_kernel.xhtml" target="_self">CLBitwiseAndKernel</a></td><td class="desc">Interface for the bitwise AND operation kernel </td></tr>
+<tr id="row_0_48_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_not.xhtml" target="_self">CLBitwiseNot</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_not_kernel.xhtml">CLBitwiseNotKernel</a> </td></tr>
+<tr id="row_0_49_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_not_kernel.xhtml" target="_self">CLBitwiseNotKernel</a></td><td class="desc">Interface for the bitwise NOT operation kernel </td></tr>
+<tr id="row_0_50_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_or.xhtml" target="_self">CLBitwiseOr</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_or_kernel.xhtml">CLBitwiseOrKernel</a> </td></tr>
+<tr id="row_0_51_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_or_kernel.xhtml" target="_self">CLBitwiseOrKernel</a></td><td class="desc">Interface for the bitwise OR operation kernel </td></tr>
+<tr id="row_0_52_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_xor.xhtml" target="_self">CLBitwiseXor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_xor_kernel.xhtml">CLBitwiseXorKernel</a> </td></tr>
+<tr id="row_0_53_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_xor_kernel.xhtml" target="_self">CLBitwiseXorKernel</a></td><td class="desc">Interface for the bitwise XOR operation kernel </td></tr>
+<tr id="row_0_54_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_box3x3.xhtml" target="_self">CLBox3x3</a></td><td class="desc">Basic function to execute box filter 3x3 </td></tr>
+<tr id="row_0_55_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_box3x3_kernel.xhtml" target="_self">CLBox3x3Kernel</a></td><td class="desc">Interface for the box 3x3 filter kernel </td></tr>
+<tr id="row_0_56_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_buffer_allocator.xhtml" target="_self">CLBufferAllocator</a></td><td class="desc">Default OpenCL cl buffer allocator implementation </td></tr>
+<tr id="row_0_57_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_buffer_memory_region.xhtml" target="_self">CLBufferMemoryRegion</a></td><td class="desc">OpenCL buffer memory region implementation </td></tr>
+<tr id="row_0_58_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_build_options.xhtml" target="_self">CLBuildOptions</a></td><td class="desc">Build options </td></tr>
+<tr id="row_0_59_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml" target="_self">CLCannyEdge</a></td><td class="desc">Basic function to execute canny edge on OpenCL </td></tr>
+<tr id="row_0_60_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_combine.xhtml" target="_self">CLChannelCombine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_channel_combine_kernel.xhtml">CLChannelCombineKernel</a> to perform channel combination </td></tr>
+<tr id="row_0_61_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_combine_kernel.xhtml" target="_self">CLChannelCombineKernel</a></td><td class="desc">Interface for the channel combine kernel </td></tr>
+<tr id="row_0_62_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_extract.xhtml" target="_self">CLChannelExtract</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_channel_extract_kernel.xhtml">CLChannelExtractKernel</a> to perform channel extraction </td></tr>
+<tr id="row_0_63_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_extract_kernel.xhtml" target="_self">CLChannelExtractKernel</a></td><td class="desc">Interface for the channel extract kernel </td></tr>
+<tr id="row_0_64_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_shuffle_layer.xhtml" target="_self">CLChannelShuffleLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_channel_shuffle_layer_kernel.xhtml">CLChannelShuffleLayerKernel</a> </td></tr>
+<tr id="row_0_65_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_shuffle_layer_kernel.xhtml" target="_self">CLChannelShuffleLayerKernel</a></td><td class="desc">Interface for the channel shuffle kernel </td></tr>
+<tr id="row_0_66_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_coarse_s_v_m_memory_region.xhtml" target="_self">CLCoarseSVMMemoryRegion</a></td><td class="desc">OpenCL coarse-grain SVM memory region implementation </td></tr>
+<tr id="row_0_67_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_coefficient_table.xhtml" target="_self">CLCoefficientTable</a></td><td class="desc">Structure for storing Spatial Gradient Matrix and the minimum eigenvalue for each keypoint </td></tr>
+<tr id="row_0_68_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_col2_im_kernel.xhtml" target="_self">CLCol2ImKernel</a></td><td class="desc">Interface for the col2im reshaping kernel </td></tr>
+<tr id="row_0_69_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_color_convert.xhtml" target="_self">CLColorConvert</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_color_convert_kernel.xhtml">CLColorConvertKernel</a> </td></tr>
+<tr id="row_0_70_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_color_convert_kernel.xhtml" target="_self">CLColorConvertKernel</a></td><td class="desc">Interface for the color convert kernel </td></tr>
+<tr id="row_0_71_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_concatenate_layer.xhtml" target="_self">CLConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along a given axis </td></tr>
+<tr id="row_0_72_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convert_fully_connected_weights.xhtml" target="_self">CLConvertFullyConnectedWeights</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_convert_fully_connected_weights_kernel.xhtml">CLConvertFullyConnectedWeightsKernel</a> </td></tr>
+<tr id="row_0_73_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convert_fully_connected_weights_kernel.xhtml" target="_self">CLConvertFullyConnectedWeightsKernel</a></td><td class="desc">Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa </td></tr>
+<tr id="row_0_74_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution3x3.xhtml" target="_self">CLConvolution3x3</a></td><td class="desc">Basic function to execute convolution of size 3x3 </td></tr>
+<tr id="row_0_75_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_kernel.xhtml" target="_self">CLConvolutionKernel</a></td><td class="desc">Interface for the kernel to run an arbitrary size convolution on a tensor </td></tr>
+<tr id="row_0_76_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml" target="_self">CLConvolutionLayer</a></td><td class="desc">Basic function to compute the convolution layer </td></tr>
+<tr id="row_0_77_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_layer_reshape_weights.xhtml" target="_self">CLConvolutionLayerReshapeWeights</a></td><td class="desc">Function to reshape and transpose the weights </td></tr>
+<tr id="row_0_78_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_rectangle.xhtml" target="_self">CLConvolutionRectangle</a></td><td class="desc">Basic function to execute non-square convolution </td></tr>
+<tr id="row_0_79_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_rectangle_kernel.xhtml" target="_self">CLConvolutionRectangleKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the running convolution on a rectangle matrix </td></tr>
+<tr id="row_0_80_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_square.xhtml" target="_self">CLConvolutionSquare</a></td><td class="desc">Basic function to execute square convolution.Currently it supports 5x5, 7x7, 9x9 </td></tr>
+<tr id="row_0_81_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_copy.xhtml" target="_self">CLCopy</a></td><td class="desc"></td></tr>
+<tr id="row_0_82_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_copy_kernel.xhtml" target="_self">CLCopyKernel</a></td><td class="desc">OpenCL kernel to perform a copy between two tensors </td></tr>
+<tr id="row_0_83_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_copy_to_array_kernel.xhtml" target="_self">CLCopyToArrayKernel</a></td><td class="desc">CL kernel to copy keypoints information to ICLKeyPointArray and counts the number of key points </td></tr>
+<tr id="row_0_84_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_deconvolution_layer.xhtml" target="_self">CLDeconvolutionLayer</a></td><td class="desc">Function to run the deconvolution layer </td></tr>
+<tr id="row_0_85_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_deconvolution_layer_upsample.xhtml" target="_self">CLDeconvolutionLayerUpsample</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_deconvolution_layer_upsample_kernel.xhtml">CLDeconvolutionLayerUpsampleKernel</a> </td></tr>
+<tr id="row_0_86_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_deconvolution_layer_upsample_kernel.xhtml" target="_self">CLDeconvolutionLayerUpsampleKernel</a></td><td class="desc">Interface for the Deconvolution layer kernel on OpenCL </td></tr>
+<tr id="row_0_87_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depth_concatenate_layer.xhtml" target="_self">CLDepthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
+<tr id="row_0_88_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depth_concatenate_layer_kernel.xhtml" target="_self">CLDepthConcatenateLayerKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
+<tr id="row_0_89_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depth_convert_layer.xhtml" target="_self">CLDepthConvertLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_depth_convert_layer_kernel.xhtml">CLDepthConvertLayerKernel</a> </td></tr>
+<tr id="row_0_90_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depth_convert_layer_kernel.xhtml" target="_self">CLDepthConvertLayerKernel</a></td><td class="desc">Interface for the depth conversion kernel </td></tr>
+<tr id="row_0_91_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer.xhtml" target="_self">CLDepthwiseConvolutionLayer</a></td><td class="desc">Basic function to execute a generic depthwise convolution </td></tr>
+<tr id="row_0_92_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3.xhtml" target="_self">CLDepthwiseConvolutionLayer3x3</a></td><td class="desc">Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC) </td></tr>
+<tr id="row_0_93_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_c_h_w_kernel.xhtml" target="_self">CLDepthwiseConvolutionLayer3x3NCHWKernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor when the data layout is NCHW </td></tr>
+<tr id="row_0_94_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution_layer3x3_n_h_w_c_kernel.xhtml" target="_self">CLDepthwiseConvolutionLayer3x3NHWCKernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor when the data layout is NHWC </td></tr>
+<tr id="row_0_95_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_im2_col_kernel.xhtml" target="_self">CLDepthwiseIm2ColKernel</a></td><td class="desc">Interface for the depthwise im2col reshape kernel </td></tr>
+<tr id="row_0_96_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_separable_convolution_layer.xhtml" target="_self">CLDepthwiseSeparableConvolutionLayer</a></td><td class="desc">Basic function to execute depthwise convolution </td></tr>
+<tr id="row_0_97_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_vector_to_tensor_kernel.xhtml" target="_self">CLDepthwiseVectorToTensorKernel</a></td><td class="desc">Interface for the depthwise vector to tensor kernel </td></tr>
+<tr id="row_0_98_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_weights_reshape_kernel.xhtml" target="_self">CLDepthwiseWeightsReshapeKernel</a></td><td class="desc">Interface for the depthwise weights reshape kernel </td></tr>
+<tr id="row_0_99_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dequantization_layer.xhtml" target="_self">CLDequantizationLayer</a></td><td class="desc">Basic function to simulate a dequantization layer </td></tr>
+<tr id="row_0_100_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml" target="_self">CLDequantizationLayerKernel</a></td><td class="desc">Interface for the dequantization layer kernel </td></tr>
+<tr id="row_0_101_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_derivative.xhtml" target="_self">CLDerivative</a></td><td class="desc">Basic function to execute first order derivative operator </td></tr>
+<tr id="row_0_102_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_derivative_kernel.xhtml" target="_self">CLDerivativeKernel</a></td><td class="desc">Interface for the derivative kernel </td></tr>
+<tr id="row_0_103_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_device_options.xhtml" target="_self">CLDeviceOptions</a></td><td class="desc">OpenCL device options </td></tr>
+<tr id="row_0_104_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dilate.xhtml" target="_self">CLDilate</a></td><td class="desc">Basic function to execute dilate </td></tr>
+<tr id="row_0_105_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dilate_kernel.xhtml" target="_self">CLDilateKernel</a></td><td class="desc">Interface for the dilate kernel </td></tr>
+<tr id="row_0_106_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml" target="_self">CLDirectConvolutionLayer</a></td><td class="desc">Basic function to execute direct convolution function: </td></tr>
+<tr id="row_0_107_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml" target="_self">CLDirectConvolutionLayerKernel</a></td><td class="desc">Interface for the direct convolution kernel </td></tr>
+<tr id="row_0_108_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer_output_stage_kernel.xhtml" target="_self">CLDirectConvolutionLayerOutputStageKernel</a></td><td class="desc">OpenCL kernel to accumulate the biases, if provided, or downscale in case of quantized input </td></tr>
+<tr id="row_0_109_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_distribution1_d.xhtml" target="_self">CLDistribution1D</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_c_l_distribution1_d.xhtml" title="CLDistribution1D object class. ">CLDistribution1D</a> object class </td></tr>
+<tr id="row_0_110_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel.xhtml" target="_self">CLEdgeNonMaxSuppressionKernel</a></td><td class="desc">OpenCL kernel to perform Non-Maxima suppression for Canny Edge </td></tr>
+<tr id="row_0_111_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_edge_trace_kernel.xhtml" target="_self">CLEdgeTraceKernel</a></td><td class="desc">OpenCL kernel to perform Edge tracing </td></tr>
+<tr id="row_0_112_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_equalize_histogram.xhtml" target="_self">CLEqualizeHistogram</a></td><td class="desc">Basic function to execute histogram equalization </td></tr>
+<tr id="row_0_113_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_erode.xhtml" target="_self">CLErode</a></td><td class="desc">Basic function to execute erode </td></tr>
+<tr id="row_0_114_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_erode_kernel.xhtml" target="_self">CLErodeKernel</a></td><td class="desc">Interface for the erode kernel </td></tr>
+<tr id="row_0_115_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fast_corners.xhtml" target="_self">CLFastCorners</a></td><td class="desc">Basic function to execute fast corners </td></tr>
+<tr id="row_0_116_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fast_corners_kernel.xhtml" target="_self">CLFastCornersKernel</a></td><td class="desc">CL kernel to perform fast corners </td></tr>
+<tr id="row_0_117_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fill_border.xhtml" target="_self">CLFillBorder</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml">CLFillBorderKernel</a> </td></tr>
+<tr id="row_0_118_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml" target="_self">CLFillBorderKernel</a></td><td class="desc">Interface for filling the border of a kernel </td></tr>
+<tr id="row_0_119_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fine_s_v_m_memory_region.xhtml" target="_self">CLFineSVMMemoryRegion</a></td><td class="desc">OpenCL fine-grain SVM memory region implementation </td></tr>
+<tr id="row_0_120_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_flatten_layer.xhtml" target="_self">CLFlattenLayer</a></td><td class="desc">Basic function to execute flatten </td></tr>
+<tr id="row_0_121_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_flatten_layer_kernel.xhtml" target="_self">CLFlattenLayerKernel</a></td><td class="desc">OpenCL interface for the flatten kernel </td></tr>
+<tr id="row_0_122_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_floor.xhtml" target="_self">CLFloor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_floor_kernel.xhtml">CLFloorKernel</a> </td></tr>
+<tr id="row_0_123_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_floor_kernel.xhtml" target="_self">CLFloorKernel</a></td><td class="desc">OpenCL kernel to perform a floor operation </td></tr>
+<tr id="row_0_124_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer.xhtml" target="_self">CLFullyConnectedLayer</a></td><td class="desc">Basic function to compute a Fully Connected layer on OpenCL </td></tr>
+<tr id="row_0_125_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer_reshape_weights.xhtml" target="_self">CLFullyConnectedLayerReshapeWeights</a></td><td class="desc">Basic function to reshape the weights of Fully Connected layer with OpenCL </td></tr>
+<tr id="row_0_126_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian3x3.xhtml" target="_self">CLGaussian3x3</a></td><td class="desc">Basic function to execute gaussian filter 3x3 </td></tr>
+<tr id="row_0_127_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian3x3_kernel.xhtml" target="_self">CLGaussian3x3Kernel</a></td><td class="desc">Interface for the Gaussian 3x3 filter kernel </td></tr>
+<tr id="row_0_128_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian5x5.xhtml" target="_self">CLGaussian5x5</a></td><td class="desc">Basic function to execute gaussian filter 5x5 </td></tr>
+<tr id="row_0_129_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian5x5_hor_kernel.xhtml" target="_self">CLGaussian5x5HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 5x5 Gaussian filter on a tensor </td></tr>
+<tr id="row_0_130_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian5x5_vert_kernel.xhtml" target="_self">CLGaussian5x5VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 5x5 Gaussian filter on a tensor </td></tr>
+<tr id="row_0_131_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid.xhtml" target="_self">CLGaussianPyramid</a></td><td class="desc">Common interface for all Gaussian pyramid functions </td></tr>
+<tr id="row_0_132_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_half.xhtml" target="_self">CLGaussianPyramidHalf</a></td><td class="desc">Basic function to execute gaussian pyramid with HALF scale factor </td></tr>
+<tr id="row_0_133_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_hor_kernel.xhtml" target="_self">CLGaussianPyramidHorKernel</a></td><td class="desc">OpenCL kernel to perform a Gaussian filter and half scaling across width (horizontal pass) </td></tr>
+<tr id="row_0_134_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_orb.xhtml" target="_self">CLGaussianPyramidOrb</a></td><td class="desc">Basic function to execute gaussian pyramid with ORB scale factor </td></tr>
+<tr id="row_0_135_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_vert_kernel.xhtml" target="_self">CLGaussianPyramidVertKernel</a></td><td class="desc">OpenCL kernel to perform a Gaussian filter and half scaling across height (vertical pass) </td></tr>
+<tr id="row_0_136_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m.xhtml" target="_self">CLGEMM</a></td><td class="desc">Basic function to execute GEMM on OpenCL </td></tr>
+<tr id="row_0_137_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_convolution_layer.xhtml" target="_self">CLGEMMConvolutionLayer</a></td><td class="desc">Basic function to compute the convolution layer </td></tr>
+<tr id="row_0_138_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4.xhtml" target="_self">CLGEMMInterleave4x4</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4_kernel.xhtml" title="OpenCL kernel which interleaves the elements of a matrix A in chunk of 4x4. ">CLGEMMInterleave4x4Kernel</a> </td></tr>
+<tr id="row_0_139_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4_kernel.xhtml" target="_self">CLGEMMInterleave4x4Kernel</a></td><td class="desc">OpenCL kernel which interleaves the elements of a matrix A in chunk of 4x4 </td></tr>
+<tr id="row_0_140_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_a_reduction_kernel.xhtml" target="_self">CLGEMMLowpMatrixAReductionKernel</a></td><td class="desc">OpenCL kernel used to compute the row-vectors of sums of all the entries in each row of Matrix A </td></tr>
+<tr id="row_0_141_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_b_reduction_kernel.xhtml" target="_self">CLGEMMLowpMatrixBReductionKernel</a></td><td class="desc">OpenCL kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B </td></tr>
+<tr id="row_0_142_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core.xhtml" target="_self">CLGEMMLowpMatrixMultiplyCore</a></td><td class="desc">Basic function to execute GEMMLowpMatrixMultiplyCore on OpenCL </td></tr>
+<tr id="row_0_143_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml" target="_self">CLGEMMLowpMatrixMultiplyKernel</a></td><td class="desc">OpenCL kernel to multiply matrices </td></tr>
+<tr id="row_0_144_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_offset_contribution_kernel.xhtml" target="_self">CLGEMMLowpOffsetContributionKernel</a></td><td class="desc">OpenCL kernel used to add the offset contribution after <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml">CLGEMMLowpMatrixMultiplyKernel</a> </td></tr>
+<tr id="row_0_145_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" target="_self">CLGEMMLowpQuantizeDownInt32ToUint8Scale</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" title="Basic function to execute CLGEMMLowpQuantizeDownInt32ToUint8Scale on OpenCL. ">CLGEMMLowpQuantizeDownInt32ToUint8Scale</a> on OpenCL </td></tr>
+<tr id="row_0_146_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" target="_self">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" title="Basic function to execute CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint on OpenCL. ">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a> on OpenCL </td></tr>
+<tr id="row_0_147_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point_kernel.xhtml" target="_self">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel</a></td><td class="desc">OpenCL kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 </td></tr>
+<tr id="row_0_148_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_kernel.xhtml" target="_self">CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel</a></td><td class="desc">OpenCL kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 </td></tr>
+<tr id="row_0_149_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_accumulate_biases_kernel.xhtml" target="_self">CLGEMMMatrixAccumulateBiasesKernel</a></td><td class="desc">Interface to add a bias to each row of the input tensor </td></tr>
+<tr id="row_0_150_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_addition_kernel.xhtml" target="_self">CLGEMMMatrixAdditionKernel</a></td><td class="desc">OpenCL kernel to perform the in-place matrix addition between 2 matrices, taking into account that the second matrix might be weighted by a scalar value beta </td></tr>
+<tr id="row_0_151_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_multiply_kernel.xhtml" target="_self">CLGEMMMatrixMultiplyKernel</a></td><td class="desc">OpenCL kernel to multiply two input matrices "A" and "B" </td></tr>
+<tr id="row_0_152_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_vector_multiply_kernel.xhtml" target="_self">CLGEMMMatrixVectorMultiplyKernel</a></td><td class="desc">Interface for the GEMM matrix vector multiply kernel </td></tr>
+<tr id="row_0_153_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_transpose1x_w.xhtml" target="_self">CLGEMMTranspose1xW</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_transpose1x_w_kernel.xhtml" title="OpenCL kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / e...">CLGEMMTranspose1xWKernel</a> </td></tr>
+<tr id="row_0_154_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_transpose1x_w_kernel.xhtml" target="_self">CLGEMMTranspose1xWKernel</a></td><td class="desc">OpenCL kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / element size of the tensor) </td></tr>
+<tr id="row_0_155_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gradient_kernel.xhtml" target="_self">CLGradientKernel</a></td><td class="desc">OpenCL kernel to perform Gradient computation </td></tr>
+<tr id="row_0_156_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_harris_corners.xhtml" target="_self">CLHarrisCorners</a></td><td class="desc">Basic function to execute harris corners detection </td></tr>
+<tr id="row_0_157_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_harris_score_kernel.xhtml" target="_self">CLHarrisScoreKernel</a></td><td class="desc">Interface for the harris score kernel </td></tr>
+<tr id="row_0_158_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_histogram.xhtml" target="_self">CLHistogram</a></td><td class="desc">Basic function to execute histogram </td></tr>
+<tr id="row_0_159_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_histogram_border_kernel.xhtml" target="_self">CLHistogramBorderKernel</a></td><td class="desc">Interface to run the histogram kernel to handle the leftover part of image </td></tr>
+<tr id="row_0_160_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_histogram_kernel.xhtml" target="_self">CLHistogramKernel</a></td><td class="desc">Interface to run the histogram kernel </td></tr>
+<tr id="row_0_161_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g.xhtml" target="_self">CLHOG</a></td><td class="desc">OpenCL implementation of <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-object </td></tr>
+<tr id="row_0_162_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_block_normalization_kernel.xhtml" target="_self">CLHOGBlockNormalizationKernel</a></td><td class="desc">OpenCL kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> block normalization </td></tr>
+<tr id="row_0_163_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_descriptor.xhtml" target="_self">CLHOGDescriptor</a></td><td class="desc">Basic function to calculate <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> descriptor </td></tr>
+<tr id="row_0_164_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_detector.xhtml" target="_self">CLHOGDetector</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector based on linear SVM </td></tr>
+<tr id="row_0_165_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_detector_kernel.xhtml" target="_self">CLHOGDetectorKernel</a></td><td class="desc">OpenCL kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector kernel using linear SVM </td></tr>
+<tr id="row_0_166_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_gradient.xhtml" target="_self">CLHOGGradient</a></td><td class="desc">Basic function to calculate the gradient for <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
+<tr id="row_0_167_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml" target="_self">CLHOGMultiDetection</a></td><td class="desc">Basic function to detect multiple objects (or the same object at different scales) on the same input image using <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
+<tr id="row_0_168_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_orientation_binning_kernel.xhtml" target="_self">CLHOGOrientationBinningKernel</a></td><td class="desc">OpenCL kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> Orientation Binning </td></tr>
+<tr id="row_0_169_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_im2_col_kernel.xhtml" target="_self">CLIm2ColKernel</a></td><td class="desc">Interface for the im2col reshape kernel </td></tr>
+<tr id="row_0_170_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_integral_image.xhtml" target="_self">CLIntegralImage</a></td><td class="desc">Basic function to execute integral image </td></tr>
+<tr id="row_0_171_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_integral_image_hor_kernel.xhtml" target="_self">CLIntegralImageHorKernel</a></td><td class="desc">Interface to run the horizontal pass of the integral image kernel </td></tr>
+<tr id="row_0_172_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_integral_image_vert_kernel.xhtml" target="_self">CLIntegralImageVertKernel</a></td><td class="desc">Interface to run the vertical pass of the integral image kernel </td></tr>
+<tr id="row_0_173_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml" target="_self">CLKernelLibrary</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml" title="CLKernelLibrary class. ">CLKernelLibrary</a> class </td></tr>
+<tr id="row_0_174_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l2_normalize_layer.xhtml" target="_self">CLL2NormalizeLayer</a></td><td class="desc">Basic function to perform a L2 normalization on a given axis </td></tr>
+<tr id="row_0_175_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l2_normalize_layer_kernel.xhtml" target="_self">CLL2NormalizeLayerKernel</a></td><td class="desc">Interface for performing a L2 normalize on a given axis given the square sum of it in this axis </td></tr>
+<tr id="row_0_176_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_laplacian_pyramid.xhtml" target="_self">CLLaplacianPyramid</a></td><td class="desc">Basic function to execute laplacian pyramid </td></tr>
+<tr id="row_0_177_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_laplacian_reconstruct.xhtml" target="_self">CLLaplacianReconstruct</a></td><td class="desc">Basic function to execute laplacian reconstruction </td></tr>
+<tr id="row_0_178_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_l_k_internal_keypoint.xhtml" target="_self">CLLKInternalKeypoint</a></td><td class="desc">Internal keypoint structure for Lucas-Kanade Optical Flow </td></tr>
+<tr id="row_0_179_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_finalize_kernel.xhtml" target="_self">CLLKTrackerFinalizeKernel</a></td><td class="desc">Interface to run the finalize step of LKTracker, where it truncates the coordinates stored in new_points array </td></tr>
+<tr id="row_0_180_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_init_kernel.xhtml" target="_self">CLLKTrackerInitKernel</a></td><td class="desc">Interface to run the initialization step of LKTracker </td></tr>
+<tr id="row_0_181_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_stage0_kernel.xhtml" target="_self">CLLKTrackerStage0Kernel</a></td><td class="desc">Interface to run the first stage of LKTracker, where A11, A12, A22, min_eig, ival, ixval and iyval are computed </td></tr>
+<tr id="row_0_182_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_stage1_kernel.xhtml" target="_self">CLLKTrackerStage1Kernel</a></td><td class="desc">Interface to run the second stage of LKTracker, where the motion vectors of the given points are computed </td></tr>
+<tr id="row_0_183_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_locally_connected_layer.xhtml" target="_self">CLLocallyConnectedLayer</a></td><td class="desc">Basic function to compute the locally connected layer </td></tr>
+<tr id="row_0_184_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_locally_connected_matrix_multiply_kernel.xhtml" target="_self">CLLocallyConnectedMatrixMultiplyKernel</a></td><td class="desc">OpenCL kernel to multiply each row of first tensor with low 2 dimensions of second tensor </td></tr>
+<tr id="row_0_185_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_max_kernel.xhtml" target="_self">CLLogits1DMaxKernel</a></td><td class="desc">Interface for the identifying the max value of 1D Logits </td></tr>
+<tr id="row_0_186_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_max_shift_exp_sum_kernel.xhtml" target="_self">CLLogits1DMaxShiftExpSumKernel</a></td><td class="desc">Interface for max, shifting, exponentiating and summing the logits </td></tr>
+<tr id="row_0_187_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_norm_kernel.xhtml" target="_self">CLLogits1DNormKernel</a></td><td class="desc">Interface for calculating the final step of the Softmax Layer where each logit value is multiplied by the inverse of the sum of the logits </td></tr>
+<tr id="row_0_188_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_shift_exp_sum_kernel.xhtml" target="_self">CLLogits1DShiftExpSumKernel</a></td><td class="desc">Interface for shifting, exponentiating and summing the logits </td></tr>
+<tr id="row_0_189_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_s_t_m_layer.xhtml" target="_self">CLLSTMLayer</a></td><td class="desc">This function performs a single time step in a Long Short-Term <a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> (LSTM) layer </td></tr>
+<tr id="row_0_190_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_lut.xhtml" target="_self">CLLut</a></td><td class="desc">Basic implementation of the OpenCL lut interface </td></tr>
+<tr id="row_0_191_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_lut_allocator.xhtml" target="_self">CLLutAllocator</a></td><td class="desc">Basic implementation of a CL memory LUT allocator </td></tr>
+<tr id="row_0_192_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_magnitude.xhtml" target="_self">CLMagnitude</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml">CLMagnitudePhaseKernel</a> </td></tr>
+<tr id="row_0_193_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml" target="_self">CLMagnitudePhaseKernel</a></td><td class="desc">Template interface for the kernel to compute magnitude and phase </td></tr>
+<tr id="row_0_194_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_mean_std_dev.xhtml" target="_self">CLMeanStdDev</a></td><td class="desc">Basic function to execute mean and standard deviation by calling <a class="el" href="classarm__compute_1_1_c_l_mean_std_dev_kernel.xhtml">CLMeanStdDevKernel</a> </td></tr>
+<tr id="row_0_195_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_mean_std_dev_kernel.xhtml" target="_self">CLMeanStdDevKernel</a></td><td class="desc">Interface for the kernel to calculate mean and standard deviation of input image pixels </td></tr>
+<tr id="row_0_196_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_median3x3.xhtml" target="_self">CLMedian3x3</a></td><td class="desc">Basic function to execute median filter </td></tr>
+<tr id="row_0_197_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_median3x3_kernel.xhtml" target="_self">CLMedian3x3Kernel</a></td><td class="desc">Interface for the median 3x3 filter kernel </td></tr>
+<tr id="row_0_198_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_memory.xhtml" target="_self">CLMemory</a></td><td class="desc">OpenCL implementation of memory object </td></tr>
+<tr id="row_0_199_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_kernel.xhtml" target="_self">CLMinMaxKernel</a></td><td class="desc">Interface for the kernel to perform min max search on an image </td></tr>
+<tr id="row_0_200_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_layer_kernel.xhtml" target="_self">CLMinMaxLayerKernel</a></td><td class="desc">Interface for the kernel to perform min max search on a 3D tensor </td></tr>
+<tr id="row_0_201_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_location.xhtml" target="_self">CLMinMaxLocation</a></td><td class="desc">Basic function to execute min and max location </td></tr>
+<tr id="row_0_202_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_location_kernel.xhtml" target="_self">CLMinMaxLocationKernel</a></td><td class="desc">Interface for the kernel to find min max locations of an image </td></tr>
+<tr id="row_0_203_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_multi_h_o_g.xhtml" target="_self">CLMultiHOG</a></td><td class="desc">Basic implementation of the CL multi <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-objects </td></tr>
+<tr id="row_0_204_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_multi_image.xhtml" target="_self">CLMultiImage</a></td><td class="desc">Basic implementation of the CL multi-planar image interface </td></tr>
+<tr id="row_0_205_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_linear_filter.xhtml" target="_self">CLNonLinearFilter</a></td><td class="desc">Basic function to execute non linear filter </td></tr>
+<tr id="row_0_206_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_linear_filter_kernel.xhtml" target="_self">CLNonLinearFilterKernel</a></td><td class="desc">Interface for the kernel to apply a non-linear filter </td></tr>
+<tr id="row_0_207_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_maxima_suppression3x3.xhtml" target="_self">CLNonMaximaSuppression3x3</a></td><td class="desc">Basic function to execute non-maxima suppression over a 3x3 window </td></tr>
+<tr id="row_0_208_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_maxima_suppression3x3_kernel.xhtml" target="_self">CLNonMaximaSuppression3x3Kernel</a></td><td class="desc">Interface to perform Non-Maxima suppression over a 3x3 window using OpenCL </td></tr>
+<tr id="row_0_209_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_normalization_layer.xhtml" target="_self">CLNormalizationLayer</a></td><td class="desc">Basic function to compute a normalization layer </td></tr>
+<tr id="row_0_210_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_normalization_layer_kernel.xhtml" target="_self">CLNormalizationLayerKernel</a></td><td class="desc">Interface for the normalization layer kernel </td></tr>
+<tr id="row_0_211_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_old_value.xhtml" target="_self">CLOldValue</a></td><td class="desc">Structure for storing ival, ixval and iyval for each point inside the window </td></tr>
+<tr id="row_0_212_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_optical_flow.xhtml" target="_self">CLOpticalFlow</a></td><td class="desc">Basic function to execute optical flow </td></tr>
+<tr id="row_0_213_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_permute.xhtml" target="_self">CLPermute</a></td><td class="desc">Basic function to execute an <a class="el" href="classarm__compute_1_1_c_l_permute_kernel.xhtml">CLPermuteKernel</a> </td></tr>
+<tr id="row_0_214_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_permute_kernel.xhtml" target="_self">CLPermuteKernel</a></td><td class="desc">OpenCL kernel to perform tensor permutation </td></tr>
+<tr id="row_0_215_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_phase.xhtml" target="_self">CLPhase</a></td><td class="desc">Basic function to execute an <a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml">CLMagnitudePhaseKernel</a> </td></tr>
+<tr id="row_0_216_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication.xhtml" target="_self">CLPixelWiseMultiplication</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication_kernel.xhtml">CLPixelWiseMultiplicationKernel</a> </td></tr>
+<tr id="row_0_217_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication_kernel.xhtml" target="_self">CLPixelWiseMultiplicationKernel</a></td><td class="desc">Interface for the pixelwise multiplication kernel </td></tr>
+<tr id="row_0_218_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pooling_layer.xhtml" target="_self">CLPoolingLayer</a></td><td class="desc">Basic function to simulate a pooling layer with the specified pooling operation </td></tr>
+<tr id="row_0_219_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pooling_layer_kernel.xhtml" target="_self">CLPoolingLayerKernel</a></td><td class="desc">Interface for the pooling layer kernel </td></tr>
+<tr id="row_0_220_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pyramid.xhtml" target="_self">CLPyramid</a></td><td class="desc">Basic implementation of the OpenCL pyramid interface </td></tr>
+<tr id="row_0_221_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_quantization_layer.xhtml" target="_self">CLQuantizationLayer</a></td><td class="desc">Basic function to simulate a quantization layer </td></tr>
+<tr id="row_0_222_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_quantization_layer_kernel.xhtml" target="_self">CLQuantizationLayerKernel</a></td><td class="desc">Interface for the quantization layer kernel </td></tr>
+<tr id="row_0_223_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reduction_operation.xhtml" target="_self">CLReductionOperation</a></td><td class="desc">Perform reduction operation </td></tr>
+<tr id="row_0_224_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reduction_operation_kernel.xhtml" target="_self">CLReductionOperationKernel</a></td><td class="desc">Interface for the reduction operation kernel </td></tr>
+<tr id="row_0_225_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_remap.xhtml" target="_self">CLRemap</a></td><td class="desc">Basic function to execute remap </td></tr>
+<tr id="row_0_226_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_remap_kernel.xhtml" target="_self">CLRemapKernel</a></td><td class="desc">OpenCL kernel to perform a remap on a tensor </td></tr>
+<tr id="row_0_227_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reshape_layer.xhtml" target="_self">CLReshapeLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml">CLReshapeLayerKernel</a> </td></tr>
+<tr id="row_0_228_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml" target="_self">CLReshapeLayerKernel</a></td><td class="desc">Interface for the kernel to perform tensor reshaping </td></tr>
+<tr id="row_0_229_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_r_n_n_layer.xhtml" target="_self">CLRNNLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_r_n_n_layer.xhtml">CLRNNLayer</a> </td></tr>
+<tr id="row_0_230_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer.xhtml" target="_self">CLROIPoolingLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer_kernel.xhtml">CLROIPoolingLayerKernel</a> </td></tr>
+<tr id="row_0_231_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer_kernel.xhtml" target="_self">CLROIPoolingLayerKernel</a></td><td class="desc">Interface for the <a class="el" href="structarm__compute_1_1_r_o_i.xhtml" title="Region of interest. ">ROI</a> pooling layer kernel </td></tr>
+<tr id="row_0_232_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scale.xhtml" target="_self">CLScale</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_scale_kernel.xhtml">CLScaleKernel</a> </td></tr>
+<tr id="row_0_233_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scale_kernel.xhtml" target="_self">CLScaleKernel</a></td><td class="desc">Interface for the scale kernel </td></tr>
+<tr id="row_0_234_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scharr3x3.xhtml" target="_self">CLScharr3x3</a></td><td class="desc">Basic function to execute scharr 3x3 filter </td></tr>
+<tr id="row_0_235_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scharr3x3_kernel.xhtml" target="_self">CLScharr3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Scharr filter on a tensor </td></tr>
+<tr id="row_0_236_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" target="_self">CLScheduler</a></td><td class="desc">Provides global access to a CL context and command queue </td></tr>
+<tr id="row_0_237_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_separable_convolution_hor_kernel.xhtml" target="_self">CLSeparableConvolutionHorKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the Horizontal pass of a Separable Convolution </td></tr>
+<tr id="row_0_238_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_separable_convolution_vert_kernel.xhtml" target="_self">CLSeparableConvolutionVertKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the Vertical pass of a Separable Convolution </td></tr>
+<tr id="row_0_239_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel3x3.xhtml" target="_self">CLSobel3x3</a></td><td class="desc">Basic function to execute sobel 3x3 filter </td></tr>
+<tr id="row_0_240_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel3x3_kernel.xhtml" target="_self">CLSobel3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Sobel filter on a tensor </td></tr>
+<tr id="row_0_241_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel5x5.xhtml" target="_self">CLSobel5x5</a></td><td class="desc">Basic function to execute sobel 5x5 filter </td></tr>
+<tr id="row_0_242_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel5x5_hor_kernel.xhtml" target="_self">CLSobel5x5HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 5x5 Sobel filter on a tensor </td></tr>
+<tr id="row_0_243_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel5x5_vert_kernel.xhtml" target="_self">CLSobel5x5VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 5x5 Sobel filter on a tensor </td></tr>
+<tr id="row_0_244_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel7x7.xhtml" target="_self">CLSobel7x7</a></td><td class="desc">Basic function to execute sobel 7x7 filter </td></tr>
+<tr id="row_0_245_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel7x7_hor_kernel.xhtml" target="_self">CLSobel7x7HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 7x7 Sobel filter on a tensor </td></tr>
+<tr id="row_0_246_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel7x7_vert_kernel.xhtml" target="_self">CLSobel7x7VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 7x7 Sobel filter on a tensor </td></tr>
+<tr id="row_0_247_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_softmax_layer.xhtml" target="_self">CLSoftmaxLayer</a></td><td class="desc">Basic function to compute a SoftmaxLayer </td></tr>
+<tr id="row_0_248_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sub_tensor.xhtml" target="_self">CLSubTensor</a></td><td class="desc">Basic implementation of the OpenCL sub-tensor interface </td></tr>
+<tr id="row_0_249_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_symbols.xhtml" target="_self">CLSymbols</a></td><td class="desc">Class for loading OpenCL symbols </td></tr>
+<tr id="row_0_250_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_table_lookup.xhtml" target="_self">CLTableLookup</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_table_lookup_kernel.xhtml">CLTableLookupKernel</a> </td></tr>
+<tr id="row_0_251_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_table_lookup_kernel.xhtml" target="_self">CLTableLookupKernel</a></td><td class="desc">Interface for the kernel to perform table lookup calculations </td></tr>
+<tr id="row_0_252_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml" target="_self">CLTensor</a></td><td class="desc">Basic implementation of the OpenCL tensor interface </td></tr>
+<tr id="row_0_253_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml" target="_self">CLTensorAllocator</a></td><td class="desc">Basic implementation of a CL memory tensor allocator </td></tr>
+<tr id="row_0_254_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_threshold.xhtml" target="_self">CLThreshold</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_threshold_kernel.xhtml">CLThresholdKernel</a> </td></tr>
+<tr id="row_0_255_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_threshold_kernel.xhtml" target="_self">CLThresholdKernel</a></td><td class="desc">Interface for the thresholding kernel </td></tr>
+<tr id="row_0_256_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_transpose.xhtml" target="_self">CLTranspose</a></td><td class="desc">Basic function to transpose a matrix on OpenCL </td></tr>
+<tr id="row_0_257_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_transpose_kernel.xhtml" target="_self">CLTransposeKernel</a></td><td class="desc">OpenCL kernel which transposes the elements of a matrix </td></tr>
+<tr id="row_0_258_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_tuner.xhtml" target="_self">CLTuner</a></td><td class="desc">Basic implementation of the OpenCL tuner interface </td></tr>
+<tr id="row_0_259_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_affine.xhtml" target="_self">CLWarpAffine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_warp_affine_kernel.xhtml">CLWarpAffineKernel</a> for AFFINE transformation </td></tr>
+<tr id="row_0_260_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_affine_kernel.xhtml" target="_self">CLWarpAffineKernel</a></td><td class="desc">Interface for the warp affine kernel </td></tr>
+<tr id="row_0_261_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_perspective.xhtml" target="_self">CLWarpPerspective</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_warp_perspective_kernel.xhtml">CLWarpPerspectiveKernel</a> for PERSPECTIVE transformation </td></tr>
+<tr id="row_0_262_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_perspective_kernel.xhtml" target="_self">CLWarpPerspectiveKernel</a></td><td class="desc">Interface for the warp perspective kernel </td></tr>
+<tr id="row_0_263_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_weights_reshape_kernel.xhtml" target="_self">CLWeightsReshapeKernel</a></td><td class="desc">OpenCL kernel to perform reshaping on the weights used by convolution and locally connected layer </td></tr>
+<tr id="row_0_264_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml" target="_self">CLWidthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along x axis </td></tr>
+<tr id="row_0_265_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer_kernel.xhtml" target="_self">CLWidthConcatenateLayerKernel</a></td><td class="desc">Interface for the width concatenate kernel </td></tr>
+<tr id="row_0_266_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_convolution_layer.xhtml" target="_self">CLWinogradConvolutionLayer</a></td><td class="desc">Basic function to execute Winograd-based convolution on OpenCL </td></tr>
+<tr id="row_0_267_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_filter_transform_kernel.xhtml" target="_self">CLWinogradFilterTransformKernel</a></td><td class="desc">Interface for the Winograd filter transform kernel </td></tr>
+<tr id="row_0_268_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_input_transform.xhtml" target="_self">CLWinogradInputTransform</a></td><td class="desc">Basic function to execute a <a class="el" href="classarm__compute_1_1_c_l_winograd_input_transform_kernel.xhtml">CLWinogradInputTransformKernel</a> </td></tr>
+<tr id="row_0_269_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_input_transform_kernel.xhtml" target="_self">CLWinogradInputTransformKernel</a></td><td class="desc">OpenCL kernel to perform Winograd input transform </td></tr>
+<tr id="row_0_270_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_output_transform_kernel.xhtml" target="_self">CLWinogradOutputTransformKernel</a></td><td class="desc">Interface for the Winograd output transform kernel </td></tr>
+<tr id="row_0_271_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_coordinates.xhtml" target="_self">Coordinates</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_coordinates.xhtml" title="Coordinates of an item. ">Coordinates</a> of an item </td></tr>
+<tr id="row_0_272_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_coordinates2_d.xhtml" target="_self">Coordinates2D</a></td><td class="desc">Coordinate type </td></tr>
+<tr id="row_0_273_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_coordinates3_d.xhtml" target="_self">Coordinates3D</a></td><td class="desc">Coordinate type </td></tr>
+<tr id="row_0_274_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_corner_candidates_kernel.xhtml" target="_self">CPPCornerCandidatesKernel</a></td><td class="desc">CPP kernel to perform corner candidates </td></tr>
+<tr id="row_0_275_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_detection_window_non_maxima_suppression_kernel.xhtml" target="_self">CPPDetectionWindowNonMaximaSuppressionKernel</a></td><td class="desc">CPP kernel to perform in-place computation of euclidean distance on IDetectionWindowArray </td></tr>
+<tr id="row_0_276_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_permute.xhtml" target="_self">CPPPermute</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_p_p_permute_kernel.xhtml">CPPPermuteKernel</a> </td></tr>
+<tr id="row_0_277_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_permute_kernel.xhtml" target="_self">CPPPermuteKernel</a></td><td class="desc">CPP kernel to perform tensor permutation </td></tr>
+<tr id="row_0_278_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml" target="_self">CPPScheduler</a></td><td class="desc">C++11 implementation of a pool of threads to automatically split a kernel's execution among several threads </td></tr>
+<tr id="row_0_279_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_sort_euclidean_distance_kernel.xhtml" target="_self">CPPSortEuclideanDistanceKernel</a></td><td class="desc">CPP kernel to perform sorting and euclidean distance </td></tr>
+<tr id="row_0_280_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_upsample.xhtml" target="_self">CPPUpsample</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_p_p_upsample.xhtml">CPPUpsample</a> </td></tr>
+<tr id="row_0_281_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_upsample_kernel.xhtml" target="_self">CPPUpsampleKernel</a></td><td class="desc">CPP kernel to perform tensor upsample </td></tr>
+<tr id="row_0_282_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_u_info.xhtml" target="_self">CPUInfo</a></td><td class="desc"></td></tr>
+<tr id="row_0_283_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_detection_window.xhtml" target="_self">DetectionWindow</a></td><td class="desc">Detection window used for the object detection </td></tr>
+<tr id="row_0_284_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_dimensions.xhtml" target="_self">Dimensions</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_dimensions.xhtml" title="Dimensions with dimensionality. ">Dimensions</a> with dimensionality </td></tr>
+<tr id="row_0_285_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_distribution1_d.xhtml" target="_self">Distribution1D</a></td><td class="desc">Basic implementation of the 1D distribution interface </td></tr>
+<tr id="row_0_286_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1enable__bitwise__ops.xhtml" target="_self">enable_bitwise_ops</a></td><td class="desc">Disable bitwise operations by default </td></tr>
+<tr id="row_0_287_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1enable__bitwise__ops_3_01arm__compute_1_1_g_p_u_target_01_4.xhtml" target="_self">enable_bitwise_ops< arm_compute::GPUTarget ></a></td><td class="desc">Enable bitwise operations on GPUTarget enumerations </td></tr>
+<tr id="row_0_288_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_fully_connected_layer_info.xhtml" target="_self">FullyConnectedLayerInfo</a></td><td class="desc">Fully connected layer info </td></tr>
+<tr id="row_0_289_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_absolute_difference.xhtml" target="_self">GCAbsoluteDifference</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_absolute_difference_kernel.xhtml">GCAbsoluteDifferenceKernel</a> </td></tr>
+<tr id="row_0_290_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_absolute_difference_kernel.xhtml" target="_self">GCAbsoluteDifferenceKernel</a></td><td class="desc">Interface for the absolute difference kernel </td></tr>
+<tr id="row_0_291_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_activation_layer.xhtml" target="_self">GCActivationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_activation_layer_kernel.xhtml">GCActivationLayerKernel</a> </td></tr>
+<tr id="row_0_292_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_activation_layer_kernel.xhtml" target="_self">GCActivationLayerKernel</a></td><td class="desc">Interface for the activation layer kernel </td></tr>
+<tr id="row_0_293_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_arithmetic_addition.xhtml" target="_self">GCArithmeticAddition</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_arithmetic_addition_kernel.xhtml">GCArithmeticAdditionKernel</a> </td></tr>
+<tr id="row_0_294_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_arithmetic_addition_kernel.xhtml" target="_self">GCArithmeticAdditionKernel</a></td><td class="desc">Interface for the arithmetic addition kernel </td></tr>
+<tr id="row_0_295_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_batch_normalization_layer.xhtml" target="_self">GCBatchNormalizationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_batch_normalization_layer_kernel.xhtml">GCBatchNormalizationLayerKernel</a> and simulate a batch normalization layer </td></tr>
+<tr id="row_0_296_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_batch_normalization_layer_kernel.xhtml" target="_self">GCBatchNormalizationLayerKernel</a></td><td class="desc">Interface for the BatchNormalization layer kernel </td></tr>
+<tr id="row_0_297_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_buffer_allocator.xhtml" target="_self">GCBufferAllocator</a></td><td class="desc">Default GLES buffer allocator implementation </td></tr>
+<tr id="row_0_298_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_col2_im_kernel.xhtml" target="_self">GCCol2ImKernel</a></td><td class="desc">Interface for the col2im reshaping kernel </td></tr>
+<tr id="row_0_299_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_convolution_layer.xhtml" target="_self">GCConvolutionLayer</a></td><td class="desc">Basic function to compute the convolution layer </td></tr>
+<tr id="row_0_300_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_convolution_layer_reshape_weights.xhtml" target="_self">GCConvolutionLayerReshapeWeights</a></td><td class="desc">Function to reshape and transpose the weights </td></tr>
+<tr id="row_0_301_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depth_concatenate_layer.xhtml" target="_self">GCDepthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
+<tr id="row_0_302_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depth_concatenate_layer_kernel.xhtml" target="_self">GCDepthConcatenateLayerKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
+<tr id="row_0_303_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depthwise_convolution_layer3x3.xhtml" target="_self">GCDepthwiseConvolutionLayer3x3</a></td><td class="desc">Basic function to execute a depthwise convolution for kernel size 3x3xC </td></tr>
+<tr id="row_0_304_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depthwise_convolution_layer3x3_kernel.xhtml" target="_self">GCDepthwiseConvolutionLayer3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor </td></tr>
+<tr id="row_0_305_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer.xhtml" target="_self">GCDirectConvolutionLayer</a></td><td class="desc">Basic function to execute direct convolution function </td></tr>
+<tr id="row_0_306_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer_kernel.xhtml" target="_self">GCDirectConvolutionLayerKernel</a></td><td class="desc">Interface for the direct convolution kernel </td></tr>
+<tr id="row_0_307_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_dropout_layer.xhtml" target="_self">GCDropoutLayer</a></td><td class="desc">Basic function to do dropout op </td></tr>
+<tr id="row_0_308_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_dropout_layer_kernel.xhtml" target="_self">GCDropoutLayerKernel</a></td><td class="desc">Interface for the dropout layer kernel </td></tr>
+<tr id="row_0_309_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fill_border.xhtml" target="_self">GCFillBorder</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml">GCFillBorderKernel</a> </td></tr>
+<tr id="row_0_310_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml" target="_self">GCFillBorderKernel</a></td><td class="desc">Interface for filling the border of a kernel </td></tr>
+<tr id="row_0_311_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer.xhtml" target="_self">GCFullyConnectedLayer</a></td><td class="desc">Basic function to compute a Fully Connected layer on OpenGL ES </td></tr>
+<tr id="row_0_312_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer_reshape_weights.xhtml" target="_self">GCFullyConnectedLayerReshapeWeights</a></td><td class="desc">Basic function to reshape the weights of Fully Connected layer with OpenGL ES </td></tr>
+<tr id="row_0_313_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m.xhtml" target="_self">GCGEMM</a></td><td class="desc">Basic function to execute GEMM on OpenGLES Compute </td></tr>
+<tr id="row_0_314_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_interleave4x4.xhtml" target="_self">GCGEMMInterleave4x4</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_interleave4x4_kernel.xhtml" title="OpenGL ES kernel which interleaves the elements of a matrix A in chunk of 4x4. ">GCGEMMInterleave4x4Kernel</a> </td></tr>
+<tr id="row_0_315_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_interleave4x4_kernel.xhtml" target="_self">GCGEMMInterleave4x4Kernel</a></td><td class="desc">OpenGL ES kernel which interleaves the elements of a matrix A in chunk of 4x4 </td></tr>
+<tr id="row_0_316_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_accumulate_biases_kernel.xhtml" target="_self">GCGEMMMatrixAccumulateBiasesKernel</a></td><td class="desc">Interface to add a bias to each row of the input tensor </td></tr>
+<tr id="row_0_317_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_addition_kernel.xhtml" target="_self">GCGEMMMatrixAdditionKernel</a></td><td class="desc">OpenGL ES kernel to perform the in-place matrix addition between 2 matrices, taking into account that the second matrix might be weighted by a scalar value beta </td></tr>
+<tr id="row_0_318_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_multiply_kernel.xhtml" target="_self">GCGEMMMatrixMultiplyKernel</a></td><td class="desc">GLES Compute kernel to multiply two input matrices "A" and "B" or to multiply a vector "A" by a matrix "B" </td></tr>
+<tr id="row_0_319_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_transpose1x_w.xhtml" target="_self">GCGEMMTranspose1xW</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_transpose1x_w_kernel.xhtml" title="OpenGLES kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 /...">GCGEMMTranspose1xWKernel</a> </td></tr>
+<tr id="row_0_320_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_transpose1x_w_kernel.xhtml" target="_self">GCGEMMTranspose1xWKernel</a></td><td class="desc">OpenGLES kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / element size of the tensor) </td></tr>
+<tr id="row_0_321_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_im2_col_kernel.xhtml" target="_self">GCIm2ColKernel</a></td><td class="desc">Interface for the im2col reshape kernel </td></tr>
+<tr id="row_0_322_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_kernel.xhtml" target="_self">GCKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_g_c_kernel.xhtml" title="GCKernel class. ">GCKernel</a> class </td></tr>
+<tr id="row_0_323_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_kernel_library.xhtml" target="_self">GCKernelLibrary</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_g_c_kernel_library.xhtml" title="GCKernelLibrary class. ">GCKernelLibrary</a> class </td></tr>
+<tr id="row_0_324_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_logits1_d_max_kernel.xhtml" target="_self">GCLogits1DMaxKernel</a></td><td class="desc">Interface for the identifying the max value of 1D Logits </td></tr>
+<tr id="row_0_325_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_logits1_d_norm_kernel.xhtml" target="_self">GCLogits1DNormKernel</a></td><td class="desc">Interface for calculating the final step of the Softmax Layer where each logit value is multiplied by the inverse of the sum of the logits </td></tr>
+<tr id="row_0_326_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_logits1_d_shift_exp_sum_kernel.xhtml" target="_self">GCLogits1DShiftExpSumKernel</a></td><td class="desc">Interface for shifting the logits values around the max value and exponentiating the result </td></tr>
+<tr id="row_0_327_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalization_layer.xhtml" target="_self">GCNormalizationLayer</a></td><td class="desc">Basic function to compute a normalization layer </td></tr>
+<tr id="row_0_328_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalization_layer_kernel.xhtml" target="_self">GCNormalizationLayerKernel</a></td><td class="desc">Interface for the normalization layer kernel </td></tr>
+<tr id="row_0_329_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer.xhtml" target="_self">GCNormalizePlanarYUVLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer_kernel.xhtml">GCNormalizePlanarYUVLayerKernel</a> </td></tr>
+<tr id="row_0_330_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer_kernel.xhtml" target="_self">GCNormalizePlanarYUVLayerKernel</a></td><td class="desc">Interface for the NormalizePlanarYUV layer kernel </td></tr>
+<tr id="row_0_331_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pixel_wise_multiplication.xhtml" target="_self">GCPixelWiseMultiplication</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_pixel_wise_multiplication_kernel.xhtml">GCPixelWiseMultiplicationKernel</a> </td></tr>
+<tr id="row_0_332_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pixel_wise_multiplication_kernel.xhtml" target="_self">GCPixelWiseMultiplicationKernel</a></td><td class="desc">Interface for the pixelwise multiplication kernel </td></tr>
+<tr id="row_0_333_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pooling_layer.xhtml" target="_self">GCPoolingLayer</a></td><td class="desc">Basic function to simulate a pooling layer with the specified pooling operation </td></tr>
+<tr id="row_0_334_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pooling_layer_kernel.xhtml" target="_self">GCPoolingLayerKernel</a></td><td class="desc">Interface for the pooling layer kernel </td></tr>
+<tr id="row_0_335_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_program.xhtml" target="_self">GCProgram</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_g_c_program.xhtml" title="GCProgram class. ">GCProgram</a> class </td></tr>
+<tr id="row_0_336_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_scale.xhtml" target="_self">GCScale</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_scale_kernel.xhtml">GCScaleKernel</a> </td></tr>
+<tr id="row_0_337_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_scale_kernel.xhtml" target="_self">GCScaleKernel</a></td><td class="desc">Interface for the scale kernel </td></tr>
+<tr id="row_0_338_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_scheduler.xhtml" target="_self">GCScheduler</a></td><td class="desc">Provides global access to a OpenGL ES context and command queue </td></tr>
+<tr id="row_0_339_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_softmax_layer.xhtml" target="_self">GCSoftmaxLayer</a></td><td class="desc">Basic function to compute a SoftmaxLayer </td></tr>
+<tr id="row_0_340_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_tensor.xhtml" target="_self">GCTensor</a></td><td class="desc">Interface for OpenGL ES tensor </td></tr>
+<tr id="row_0_341_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_tensor_allocator.xhtml" target="_self">GCTensorAllocator</a></td><td class="desc">Basic implementation of a GLES memory tensor allocator </td></tr>
+<tr id="row_0_342_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_tensor_shift.xhtml" target="_self">GCTensorShift</a></td><td class="desc">Basic function to execute shift function for tensor </td></tr>
+<tr id="row_0_343_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_tensor_shift_kernel.xhtml" target="_self">GCTensorShiftKernel</a></td><td class="desc">Interface for the kernel to shift valid data on a tensor </td></tr>
+<tr id="row_0_344_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_transpose.xhtml" target="_self">GCTranspose</a></td><td class="desc">Basic function to transpose a matrix on OpenGL ES </td></tr>
+<tr id="row_0_345_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_transpose_kernel.xhtml" target="_self">GCTransposeKernel</a></td><td class="desc">OpenGL ES kernel which transposes the elements of a matrix </td></tr>
+<tr id="row_0_346_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_weights_reshape_kernel.xhtml" target="_self">GCWeightsReshapeKernel</a></td><td class="desc">GLES Compute kernel to perform reshaping on the weights used by convolution and locally connected layer </td></tr>
+<tr id="row_0_347_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_e_m_m_info.xhtml" target="_self">GEMMInfo</a></td><td class="desc">GEMM information class </td></tr>
+<tr id="row_0_348_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml" target="_self">GEMMReshapeInfo</a></td><td class="desc">GEMM reshape information class </td></tr>
+<tr id="row_0_349_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_l_buffer_wrapper.xhtml" target="_self">GLBufferWrapper</a></td><td class="desc"></td></tr>
+<tr id="row_0_350_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_h_o_g.xhtml" target="_self">HOG</a></td><td class="desc">CPU implementation of <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-object </td></tr>
+<tr id="row_0_351_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_h_o_g_info.xhtml" target="_self">HOGInfo</a></td><td class="desc">Store the <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a>'s metadata </td></tr>
+<tr id="row_0_352_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_access_window.xhtml" target="_self">IAccessWindow</a></td><td class="desc">Interface describing methods to update access window and padding based on kernel parameters </td></tr>
+<tr id="row_0_353_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_allocator.xhtml" target="_self">IAllocator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_allocator.xhtml" title="Default malloc allocator implementation. ">Allocator</a> interface </td></tr>
+<tr id="row_0_354_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_array.xhtml" target="_self">IArray</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_array.xhtml" title="Basic implementation of the IArray interface which allocates a static number of T values...">Array</a> of type T </td></tr>
+<tr id="row_0_355_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml" target="_self">ICLArray</a></td><td class="desc">Interface for OpenCL <a class="el" href="classarm__compute_1_1_array.xhtml" title="Basic implementation of the IArray interface which allocates a static number of T values...">Array</a> </td></tr>
+<tr id="row_0_356_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_depthwise_convolution_layer3x3_kernel.xhtml" target="_self">ICLDepthwiseConvolutionLayer3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor </td></tr>
+<tr id="row_0_357_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_distribution1_d.xhtml" target="_self">ICLDistribution1D</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_i_c_l_distribution1_d.xhtml" title="ICLDistribution1D interface class. ">ICLDistribution1D</a> interface class </td></tr>
+<tr id="row_0_358_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_g_e_m_m_lowp_reduction_kernel.xhtml" target="_self">ICLGEMMLowpReductionKernel</a></td><td class="desc">Common interface for all OpenCL reduction kernels </td></tr>
+<tr id="row_0_359_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_h_o_g.xhtml" target="_self">ICLHOG</a></td><td class="desc">Interface for OpenCL <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-object </td></tr>
+<tr id="row_0_360_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml" target="_self">ICLKernel</a></td><td class="desc">Common interface for all the OpenCL kernels </td></tr>
+<tr id="row_0_361_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_lut.xhtml" target="_self">ICLLut</a></td><td class="desc">Interface for OpenCL LUT </td></tr>
+<tr id="row_0_362_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_memory_region.xhtml" target="_self">ICLMemoryRegion</a></td><td class="desc">OpenCL memory region interface </td></tr>
+<tr id="row_0_363_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml" target="_self">ICLMultiHOG</a></td><td class="desc">Interface for storing multiple <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-objects </td></tr>
+<tr id="row_0_364_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_multi_image.xhtml" target="_self">ICLMultiImage</a></td><td class="desc">Interface for OpenCL multi-planar images </td></tr>
+<tr id="row_0_365_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_simple2_d_kernel.xhtml" target="_self">ICLSimple2DKernel</a></td><td class="desc">Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output </td></tr>
+<tr id="row_0_366_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_simple3_d_kernel.xhtml" target="_self">ICLSimple3DKernel</a></td><td class="desc">Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output </td></tr>
+<tr id="row_0_367_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_simple_function.xhtml" target="_self">ICLSimpleFunction</a></td><td class="desc">Basic interface for functions which have a single OpenCL kernel </td></tr>
+<tr id="row_0_368_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_simple_kernel.xhtml" target="_self">ICLSimpleKernel</a></td><td class="desc">Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output </td></tr>
+<tr id="row_0_369_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_s_v_m_memory_region.xhtml" target="_self">ICLSVMMemoryRegion</a></td><td class="desc">OpenCL SVM memory region interface </td></tr>
+<tr id="row_0_370_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml" target="_self">ICLTensor</a></td><td class="desc">Interface for OpenCL tensor </td></tr>
+<tr id="row_0_371_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_tuner.xhtml" target="_self">ICLTuner</a></td><td class="desc">Basic interface for tuning the OpenCL kernels </td></tr>
+<tr id="row_0_372_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml" target="_self">ICPPKernel</a></td><td class="desc">Common interface for all kernels implemented in C++ </td></tr>
+<tr id="row_0_373_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_p_p_simple_function.xhtml" target="_self">ICPPSimpleFunction</a></td><td class="desc">Basic interface for functions which have a single CPP kernel </td></tr>
+<tr id="row_0_374_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_p_p_simple_kernel.xhtml" target="_self">ICPPSimpleKernel</a></td><td class="desc">Interface for simple C++ kernels having 1 tensor input and 1 tensor output </td></tr>
+<tr id="row_0_375_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_distribution.xhtml" target="_self">IDistribution</a></td><td class="desc">Interface for distribution objects </td></tr>
+<tr id="row_0_376_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_distribution1_d.xhtml" target="_self">IDistribution1D</a></td><td class="desc">1D Distribution interface </td></tr>
+<tr id="row_0_377_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_function.xhtml" target="_self">IFunction</a></td><td class="desc">Base class for all functions </td></tr>
+<tr id="row_0_378_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_kernel.xhtml" target="_self">IGCKernel</a></td><td class="desc">Common interface for all the GLES kernels </td></tr>
+<tr id="row_0_379_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_simple2_d_kernel.xhtml" target="_self">IGCSimple2DKernel</a></td><td class="desc">Interface for simple OpenGL ES kernels having 1 tensor input and 1 tensor output </td></tr>
+<tr id="row_0_380_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_simple3_d_kernel.xhtml" target="_self">IGCSimple3DKernel</a></td><td class="desc">Interface for simple GLES kernels having 1 tensor input and 1 tensor output </td></tr>
+<tr id="row_0_381_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_simple_function.xhtml" target="_self">IGCSimpleFunction</a></td><td class="desc">Basic interface for functions which have a single OpenGL ES kernel </td></tr>
+<tr id="row_0_382_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_simple_kernel.xhtml" target="_self">IGCSimpleKernel</a></td><td class="desc">Interface for simple OpenGL ES kernels having 1 tensor input and 1 tensor output </td></tr>
+<tr id="row_0_383_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml" target="_self">IGCTensor</a></td><td class="desc">Interface for GLES Compute tensor </td></tr>
+<tr id="row_0_384_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_h_o_g.xhtml" target="_self">IHOG</a></td><td class="desc">Interface for <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-object </td></tr>
+<tr id="row_0_385_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_kernel.xhtml" target="_self">IKernel</a></td><td class="desc">Common information for all the kernels </td></tr>
+<tr id="row_0_386_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_lifetime_manager.xhtml" target="_self">ILifetimeManager</a></td><td class="desc">Interface for managing the lifetime of objects </td></tr>
+<tr id="row_0_387_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_lut.xhtml" target="_self">ILut</a></td><td class="desc">Lookup Table object interface </td></tr>
+<tr id="row_0_388_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_lut_allocator.xhtml" target="_self">ILutAllocator</a></td><td class="desc">Basic interface to allocate LUTs' </td></tr>
+<tr id="row_0_389_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_memory_group.xhtml" target="_self">IMemoryGroup</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> group interface </td></tr>
+<tr id="row_0_390_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml" target="_self">IMemoryManager</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> manager interface to handle allocations of backing memory </td></tr>
+<tr id="row_0_391_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_memory_pool.xhtml" target="_self">IMemoryPool</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> Pool Inteface </td></tr>
+<tr id="row_0_392_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_memory_region.xhtml" target="_self">IMemoryRegion</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> region interface </td></tr>
+<tr id="row_0_393_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_multi_h_o_g.xhtml" target="_self">IMultiHOG</a></td><td class="desc">Interface for storing multiple <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-objects </td></tr>
+<tr id="row_0_394_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_multi_image.xhtml" target="_self">IMultiImage</a></td><td class="desc">Interface for multi-planar images </td></tr>
+<tr id="row_0_395_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_g_e_m_m_lowp_reduction_kernel.xhtml" target="_self">INEGEMMLowpReductionKernel</a></td><td class="desc">Common interface for all NEON reduction kernels </td></tr>
+<tr id="row_0_396_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_harris_score_kernel.xhtml" target="_self">INEHarrisScoreKernel</a></td><td class="desc">Common interface for all Harris Score kernels </td></tr>
+<tr id="row_0_397_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_simple_function.xhtml" target="_self">INESimpleFunction</a></td><td class="desc">Basic interface for functions which have a single NEON kernel </td></tr>
+<tr id="row_0_398_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_warp_kernel.xhtml" target="_self">INEWarpKernel</a></td><td class="desc">Common interface for warp affine and warp perspective </td></tr>
+<tr id="row_0_399_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_input_kernel.xhtml" target="_self">INEWinogradLayerTransformInputKernel</a></td><td class="desc">Interface for the NEON kernel to perform Winograd input transform </td></tr>
+<tr id="row_0_400_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_output_kernel.xhtml" target="_self">INEWinogradLayerTransformOutputKernel</a></td><td class="desc">Interface for the NEON kernel to perform Winograd output transform </td></tr>
+<tr id="row_0_401_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel.xhtml" target="_self">INEWinogradLayerTransformWeightsKernel</a></td><td class="desc">Interface for the NEON kernel to perform Winograd weights transform </td></tr>
+<tr id="row_0_402_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_internal_key_point.xhtml" target="_self">InternalKeyPoint</a></td><td class="desc">Internal keypoint class for Lucas-Kanade Optical Flow </td></tr>
+<tr id="row_0_403_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_i_o_format_info.xhtml" target="_self">IOFormatInfo</a></td><td class="desc">IO formatting information class </td></tr>
+<tr id="row_0_404_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_pool_manager.xhtml" target="_self">IPoolManager</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> pool manager interface </td></tr>
+<tr id="row_0_405_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_pyramid.xhtml" target="_self">IPyramid</a></td><td class="desc">Interface for pyramid data-object </td></tr>
+<tr id="row_0_406_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_406_" class="arrow" onclick="toggleFolder('0_406_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_scheduler.xhtml" target="_self">IScheduler</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_scheduler.xhtml" title="Configurable scheduler which supports multiple multithreading APIs and choosing between different sch...">Scheduler</a> interface to run kernels </td></tr>
+<tr id="row_0_406_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_scheduler_1_1_hints.xhtml" target="_self">Hints</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_scheduler.xhtml" title="Configurable scheduler which supports multiple multithreading APIs and choosing between different sch...">Scheduler</a> hints </td></tr>
+<tr id="row_0_407_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_simple_lifetime_manager.xhtml" target="_self">ISimpleLifetimeManager</a></td><td class="desc">Abstract class of the simple lifetime manager interface </td></tr>
+<tr id="row_0_408_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_tensor.xhtml" target="_self">ITensor</a></td><td class="desc">Interface for NEON tensor </td></tr>
+<tr id="row_0_409_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_tensor_allocator.xhtml" target="_self">ITensorAllocator</a></td><td class="desc">Interface to allocate tensors </td></tr>
+<tr id="row_0_410_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml" target="_self">ITensorInfo</a></td><td class="desc">Store the tensor's metadata </td></tr>
+<tr id="row_0_411_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_iterator.xhtml" target="_self">Iterator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> updated by <a class="el" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a> for each window element </td></tr>
+<tr id="row_0_412_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_kernel.xhtml" target="_self">Kernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> class </td></tr>
+<tr id="row_0_413_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_key_point.xhtml" target="_self">KeyPoint</a></td><td class="desc"><a class="el" href="struct_keypoint.xhtml">Keypoint</a> type </td></tr>
+<tr id="row_0_414_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_l_s_t_m_params.xhtml" target="_self">LSTMParams</a></td><td class="desc"></td></tr>
+<tr id="row_0_415_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_lut.xhtml" target="_self">Lut</a></td><td class="desc">Basic implementation of the LUT interface </td></tr>
+<tr id="row_0_416_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_lut_allocator.xhtml" target="_self">LutAllocator</a></td><td class="desc">Basic implementation of a CPU memory LUT allocator </td></tr>
+<tr id="row_0_417_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_memory.xhtml" target="_self">Memory</a></td><td class="desc">CPU implementation of memory object </td></tr>
+<tr id="row_0_418_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_memory_group_base.xhtml" target="_self">MemoryGroupBase</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> group </td></tr>
+<tr id="row_0_419_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_memory_manager_on_demand.xhtml" target="_self">MemoryManagerOnDemand</a></td><td class="desc">On-demand memory manager </td></tr>
+<tr id="row_0_420_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_memory_region.xhtml" target="_self">MemoryRegion</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> region CPU implementation </td></tr>
+<tr id="row_0_421_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_min_max_location_values.xhtml" target="_self">MinMaxLocationValues</a></td><td class="desc">Min and max values and locations </td></tr>
+<tr id="row_0_422_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_multi_h_o_g.xhtml" target="_self">MultiHOG</a></td><td class="desc">CPU implementation of multi <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> data-object </td></tr>
+<tr id="row_0_423_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_multi_image.xhtml" target="_self">MultiImage</a></td><td class="desc">Basic implementation of the multi-planar image interface </td></tr>
+<tr id="row_0_424_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_multi_image_info.xhtml" target="_self">MultiImageInfo</a></td><td class="desc">Store the multi-planar image's metadata </td></tr>
+<tr id="row_0_425_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_absolute_difference.xhtml" target="_self">NEAbsoluteDifference</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_absolute_difference_kernel.xhtml">NEAbsoluteDifferenceKernel</a> </td></tr>
+<tr id="row_0_426_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_absolute_difference_kernel.xhtml" target="_self">NEAbsoluteDifferenceKernel</a></td><td class="desc">Interface for the absolute difference kernel </td></tr>
+<tr id="row_0_427_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate.xhtml" target="_self">NEAccumulate</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_accumulate_kernel.xhtml">NEAccumulateKernel</a> </td></tr>
+<tr id="row_0_428_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_kernel.xhtml" target="_self">NEAccumulateKernel</a></td><td class="desc">Interface for the accumulate kernel </td></tr>
+<tr id="row_0_429_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_squared.xhtml" target="_self">NEAccumulateSquared</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_accumulate_squared_kernel.xhtml">NEAccumulateSquaredKernel</a> </td></tr>
+<tr id="row_0_430_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_squared_kernel.xhtml" target="_self">NEAccumulateSquaredKernel</a></td><td class="desc">Interface for the accumulate squared kernel </td></tr>
+<tr id="row_0_431_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_weighted.xhtml" target="_self">NEAccumulateWeighted</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_accumulate_weighted_kernel.xhtml">NEAccumulateWeightedKernel</a> </td></tr>
+<tr id="row_0_432_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_weighted_kernel.xhtml" target="_self">NEAccumulateWeightedKernel</a></td><td class="desc">Interface for the accumulate weighted kernel </td></tr>
+<tr id="row_0_433_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_activation_layer.xhtml" target="_self">NEActivationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_activation_layer_kernel.xhtml">NEActivationLayerKernel</a> </td></tr>
+<tr id="row_0_434_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_activation_layer_kernel.xhtml" target="_self">NEActivationLayerKernel</a></td><td class="desc">Interface for the activation layer kernel </td></tr>
+<tr id="row_0_435_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_addition.xhtml" target="_self">NEArithmeticAddition</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_arithmetic_addition_kernel.xhtml">NEArithmeticAdditionKernel</a> </td></tr>
+<tr id="row_0_436_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_addition_kernel.xhtml" target="_self">NEArithmeticAdditionKernel</a></td><td class="desc">Interface for the kernel to perform addition between two tensors </td></tr>
+<tr id="row_0_437_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_subtraction.xhtml" target="_self">NEArithmeticSubtraction</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_arithmetic_subtraction_kernel.xhtml">NEArithmeticSubtractionKernel</a> </td></tr>
+<tr id="row_0_438_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_subtraction_kernel.xhtml" target="_self">NEArithmeticSubtractionKernel</a></td><td class="desc">Interface for the kernel to perform subtraction between two tensors </td></tr>
+<tr id="row_0_439_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_batch_normalization_layer.xhtml" target="_self">NEBatchNormalizationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_normalization_layer_kernel.xhtml">NENormalizationLayerKernel</a> and simulate a batch normalization layer </td></tr>
+<tr id="row_0_440_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_batch_normalization_layer_kernel.xhtml" target="_self">NEBatchNormalizationLayerKernel</a></td><td class="desc">Interface for the batch normalization layer kernel </td></tr>
+<tr id="row_0_441_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_and.xhtml" target="_self">NEBitwiseAnd</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_and_kernel.xhtml">NEBitwiseAndKernel</a> </td></tr>
+<tr id="row_0_442_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_and_kernel.xhtml" target="_self">NEBitwiseAndKernel</a></td><td class="desc">Interface for the kernel to perform bitwise AND between XY-planes of two tensors </td></tr>
+<tr id="row_0_443_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_not.xhtml" target="_self">NEBitwiseNot</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_not_kernel.xhtml">NEBitwiseNotKernel</a> </td></tr>
+<tr id="row_0_444_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_not_kernel.xhtml" target="_self">NEBitwiseNotKernel</a></td><td class="desc">Interface for the kernel to perform bitwise NOT operation </td></tr>
+<tr id="row_0_445_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_or.xhtml" target="_self">NEBitwiseOr</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_or_kernel.xhtml">NEBitwiseOrKernel</a> </td></tr>
+<tr id="row_0_446_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_or_kernel.xhtml" target="_self">NEBitwiseOrKernel</a></td><td class="desc">Interface for the kernel to perform bitwise inclusive OR between two tensors </td></tr>
+<tr id="row_0_447_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_xor.xhtml" target="_self">NEBitwiseXor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_xor_kernel.xhtml">NEBitwiseXorKernel</a> </td></tr>
+<tr id="row_0_448_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_xor_kernel.xhtml" target="_self">NEBitwiseXorKernel</a></td><td class="desc">Interface for the kernel to perform bitwise exclusive OR (XOR) between two tensors </td></tr>
+<tr id="row_0_449_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_box3x3.xhtml" target="_self">NEBox3x3</a></td><td class="desc">Basic function to execute box filter 3x3 </td></tr>
+<tr id="row_0_450_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_box3x3_kernel.xhtml" target="_self">NEBox3x3Kernel</a></td><td class="desc">NEON kernel to perform a Box 3x3 filter </td></tr>
+<tr id="row_0_451_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml" target="_self">NECannyEdge</a></td><td class="desc">Basic function to execute canny edge on NEON </td></tr>
+<tr id="row_0_452_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_combine.xhtml" target="_self">NEChannelCombine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_channel_combine_kernel.xhtml">NEChannelCombineKernel</a> to perform channel combination </td></tr>
+<tr id="row_0_453_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_combine_kernel.xhtml" target="_self">NEChannelCombineKernel</a></td><td class="desc">Interface for the channel combine kernel </td></tr>
+<tr id="row_0_454_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_extract.xhtml" target="_self">NEChannelExtract</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_channel_extract_kernel.xhtml">NEChannelExtractKernel</a> to perform channel extraction </td></tr>
+<tr id="row_0_455_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_extract_kernel.xhtml" target="_self">NEChannelExtractKernel</a></td><td class="desc">Interface for the channel extract kernel </td></tr>
+<tr id="row_0_456_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_col2_im.xhtml" target="_self">NECol2Im</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_col2_im.xhtml">NECol2Im</a> </td></tr>
+<tr id="row_0_457_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_col2_im_kernel.xhtml" target="_self">NECol2ImKernel</a></td><td class="desc">NEON kernel to perform col2im reshaping </td></tr>
+<tr id="row_0_458_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_color_convert.xhtml" target="_self">NEColorConvert</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_color_convert_kernel.xhtml">NEColorConvertKernel</a> to perform color conversion </td></tr>
+<tr id="row_0_459_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_color_convert_kernel.xhtml" target="_self">NEColorConvertKernel</a></td><td class="desc">Interface for the color convert kernel </td></tr>
+<tr id="row_0_460_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_concatenate_layer.xhtml" target="_self">NEConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along a given axis </td></tr>
+<tr id="row_0_461_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convert_fully_connected_weights.xhtml" target="_self">NEConvertFullyConnectedWeights</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_convert_fully_connected_weights_kernel.xhtml">NEConvertFullyConnectedWeightsKernel</a> </td></tr>
+<tr id="row_0_462_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convert_fully_connected_weights_kernel.xhtml" target="_self">NEConvertFullyConnectedWeightsKernel</a></td><td class="desc">Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa </td></tr>
+<tr id="row_0_463_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution3x3.xhtml" target="_self">NEConvolution3x3</a></td><td class="desc">Basic function to execute convolution of size 3x3 </td></tr>
+<tr id="row_0_464_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_kernel.xhtml" target="_self">NEConvolutionKernel</a></td><td class="desc">Interface for the kernel to run an arbitrary size convolution on a tensor </td></tr>
+<tr id="row_0_465_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml" target="_self">NEConvolutionLayer</a></td><td class="desc">Basic function to simulate a convolution layer </td></tr>
+<tr id="row_0_466_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_layer_reshape_weights.xhtml" target="_self">NEConvolutionLayerReshapeWeights</a></td><td class="desc">Function to reshape the weights </td></tr>
+<tr id="row_0_467_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_rectangle.xhtml" target="_self">NEConvolutionRectangle</a></td><td class="desc">Basic function to execute non-square convolution </td></tr>
+<tr id="row_0_468_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_rectangle_kernel.xhtml" target="_self">NEConvolutionRectangleKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the running convolution on a rectangle matrix </td></tr>
+<tr id="row_0_469_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_square.xhtml" target="_self">NEConvolutionSquare</a></td><td class="desc">Basic function to execute convolution of size 5x5, 7x7, 9x9 </td></tr>
+<tr id="row_0_470_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_copy.xhtml" target="_self">NECopy</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_copy_kernel.xhtml">NECopyKernel</a> </td></tr>
+<tr id="row_0_471_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_copy_kernel.xhtml" target="_self">NECopyKernel</a></td><td class="desc">NEON kernel to perform a copy between two tensors </td></tr>
+<tr id="row_0_472_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_cumulative_distribution_kernel.xhtml" target="_self">NECumulativeDistributionKernel</a></td><td class="desc">Interface for the cumulative distribution (cummulative summmation) calculation kernel </td></tr>
+<tr id="row_0_473_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_deconvolution_layer.xhtml" target="_self">NEDeconvolutionLayer</a></td><td class="desc">Function to run the deconvolution layer </td></tr>
+<tr id="row_0_474_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_concatenate_layer.xhtml" target="_self">NEDepthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
+<tr id="row_0_475_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_concatenate_layer_kernel.xhtml" target="_self">NEDepthConcatenateLayerKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
+<tr id="row_0_476_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_convert_layer.xhtml" target="_self">NEDepthConvertLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_depth_convert_layer_kernel.xhtml">NEDepthConvertLayerKernel</a> </td></tr>
+<tr id="row_0_477_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_convert_layer_kernel.xhtml" target="_self">NEDepthConvertLayerKernel</a></td><td class="desc">Depth conversion kernel </td></tr>
+<tr id="row_0_478_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml" target="_self">NEDepthwiseConvolutionLayer</a></td><td class="desc">Basic function to execute a generic depthwise convolution </td></tr>
+<tr id="row_0_479_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3.xhtml" target="_self">NEDepthwiseConvolutionLayer3x3</a></td><td class="desc">Basic function to execute a depthwise convolution for kernel size 3x3xC </td></tr>
+<tr id="row_0_480_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml" target="_self">NEDepthwiseConvolutionLayer3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor </td></tr>
+<tr id="row_0_481_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_im2_col_kernel.xhtml" target="_self">NEDepthwiseIm2ColKernel</a></td><td class="desc">Interface for the depthwise im2col reshape kernel </td></tr>
+<tr id="row_0_482_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_separable_convolution_layer.xhtml" target="_self">NEDepthwiseSeparableConvolutionLayer</a></td><td class="desc">Basic function to execute depthwise convolution </td></tr>
+<tr id="row_0_483_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_vector_to_tensor_kernel.xhtml" target="_self">NEDepthwiseVectorToTensorKernel</a></td><td class="desc">Interface for the depthwise vector to tensor kernel </td></tr>
+<tr id="row_0_484_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_weights_reshape_kernel.xhtml" target="_self">NEDepthwiseWeightsReshapeKernel</a></td><td class="desc">Interface for the depthwise weights reshape kernel </td></tr>
+<tr id="row_0_485_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dequantization_layer.xhtml" target="_self">NEDequantizationLayer</a></td><td class="desc">Basic function to simulate a dequantization layer </td></tr>
+<tr id="row_0_486_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dequantization_layer_kernel.xhtml" target="_self">NEDequantizationLayerKernel</a></td><td class="desc">Interface for the dequantization layer kernel </td></tr>
+<tr id="row_0_487_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_derivative.xhtml" target="_self">NEDerivative</a></td><td class="desc">Basic function to execute first order derivative operator </td></tr>
+<tr id="row_0_488_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_derivative_kernel.xhtml" target="_self">NEDerivativeKernel</a></td><td class="desc">Interface for the kernel to run the derivative along the X/Y directions on a tensor </td></tr>
+<tr id="row_0_489_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dilate.xhtml" target="_self">NEDilate</a></td><td class="desc">Basic function to execute dilate </td></tr>
+<tr id="row_0_490_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dilate_kernel.xhtml" target="_self">NEDilateKernel</a></td><td class="desc">Interface for the kernel to perform boolean image dilatation </td></tr>
+<tr id="row_0_491_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer.xhtml" target="_self">NEDirectConvolutionLayer</a></td><td class="desc">Function to run the direct convolution </td></tr>
+<tr id="row_0_492_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml" target="_self">NEDirectConvolutionLayerKernel</a></td><td class="desc">NEON interface for Direct Convolution Layer kernel </td></tr>
+<tr id="row_0_493_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_output_stage_kernel.xhtml" target="_self">NEDirectConvolutionLayerOutputStageKernel</a></td><td class="desc">NEON kernel to accumulate the biases, if provided, or downscale in case of quantized input </td></tr>
+<tr id="row_0_494_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_edge_non_max_suppression_kernel.xhtml" target="_self">NEEdgeNonMaxSuppressionKernel</a></td><td class="desc">NEON kernel to perform Non-Maxima suppression for Canny Edge </td></tr>
+<tr id="row_0_495_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_edge_trace_kernel.xhtml" target="_self">NEEdgeTraceKernel</a></td><td class="desc">NEON kernel to perform Edge tracing </td></tr>
+<tr id="row_0_496_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_equalize_histogram.xhtml" target="_self">NEEqualizeHistogram</a></td><td class="desc">Basic function to execute histogram equalization </td></tr>
+<tr id="row_0_497_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_erode.xhtml" target="_self">NEErode</a></td><td class="desc">Basic function to execute erode </td></tr>
+<tr id="row_0_498_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_erode_kernel.xhtml" target="_self">NEErodeKernel</a></td><td class="desc">Interface for the kernel to perform boolean image erosion </td></tr>
+<tr id="row_0_499_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fast_corners.xhtml" target="_self">NEFastCorners</a></td><td class="desc">Basic function to execute fast corners </td></tr>
+<tr id="row_0_500_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fast_corners_kernel.xhtml" target="_self">NEFastCornersKernel</a></td><td class="desc">NEON kernel to perform fast corners </td></tr>
+<tr id="row_0_501_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_array_kernel.xhtml" target="_self">NEFillArrayKernel</a></td><td class="desc">This kernel adds all texels greater than or equal to the threshold value to the keypoint array </td></tr>
+<tr id="row_0_502_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_border.xhtml" target="_self">NEFillBorder</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml">NEFillBorderKernel</a> </td></tr>
+<tr id="row_0_503_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml" target="_self">NEFillBorderKernel</a></td><td class="desc">Interface for the kernel to fill borders </td></tr>
+<tr id="row_0_504_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_inner_border_kernel.xhtml" target="_self">NEFillInnerBorderKernel</a></td><td class="desc">Interface for the kernel to fill the interior borders </td></tr>
+<tr id="row_0_505_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_flatten_layer.xhtml" target="_self">NEFlattenLayer</a></td><td class="desc">Basic function to execute flatten </td></tr>
+<tr id="row_0_506_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_floor.xhtml" target="_self">NEFloor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_floor_kernel.xhtml">NEFloorKernel</a> </td></tr>
+<tr id="row_0_507_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_floor_kernel.xhtml" target="_self">NEFloorKernel</a></td><td class="desc">NEON kernel to perform a floor operation </td></tr>
+<tr id="row_0_508_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer.xhtml" target="_self">NEFullyConnectedLayer</a></td><td class="desc">Basic function to compute a Fully Connected layer on NEON </td></tr>
+<tr id="row_0_509_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer_reshape_weights.xhtml" target="_self">NEFullyConnectedLayerReshapeWeights</a></td><td class="desc">Basic function to reshape the weights of Fully Connected layer with NEON </td></tr>
+<tr id="row_0_510_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian3x3.xhtml" target="_self">NEGaussian3x3</a></td><td class="desc">Basic function to execute gaussian filter 3x3 </td></tr>
+<tr id="row_0_511_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian3x3_kernel.xhtml" target="_self">NEGaussian3x3Kernel</a></td><td class="desc">NEON kernel to perform a Gaussian 3x3 filter </td></tr>
+<tr id="row_0_512_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian5x5.xhtml" target="_self">NEGaussian5x5</a></td><td class="desc">Basic function to execute gaussian filter 5x5 </td></tr>
+<tr id="row_0_513_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian5x5_hor_kernel.xhtml" target="_self">NEGaussian5x5HorKernel</a></td><td class="desc">NEON kernel to perform a Gaussian 5x5 filter (horizontal pass) </td></tr>
+<tr id="row_0_514_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian5x5_vert_kernel.xhtml" target="_self">NEGaussian5x5VertKernel</a></td><td class="desc">NEON kernel to perform a Gaussian 5x5 filter (vertical pass) </td></tr>
+<tr id="row_0_515_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid.xhtml" target="_self">NEGaussianPyramid</a></td><td class="desc">Common interface for all Gaussian pyramid functions </td></tr>
+<tr id="row_0_516_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_half.xhtml" target="_self">NEGaussianPyramidHalf</a></td><td class="desc">Basic function to execute gaussian pyramid with HALF scale factor </td></tr>
+<tr id="row_0_517_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_hor_kernel.xhtml" target="_self">NEGaussianPyramidHorKernel</a></td><td class="desc">NEON kernel to perform a GaussianPyramid (horizontal pass) </td></tr>
+<tr id="row_0_518_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_orb.xhtml" target="_self">NEGaussianPyramidOrb</a></td><td class="desc">Basic function to execute gaussian pyramid with ORB scale factor </td></tr>
+<tr id="row_0_519_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_vert_kernel.xhtml" target="_self">NEGaussianPyramidVertKernel</a></td><td class="desc">NEON kernel to perform a GaussianPyramid (vertical pass) </td></tr>
+<tr id="row_0_520_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m.xhtml" target="_self">NEGEMM</a></td><td class="desc">Basic function to execute GEMM on NEON </td></tr>
+<tr id="row_0_521_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_assembly_base_kernel.xhtml" target="_self">NEGEMMAssemblyBaseKernel</a></td><td class="desc">Base class for GEMM NEON kernels implemented in Assembly </td></tr>
+<tr id="row_0_522_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_522_" class="arrow" onclick="toggleFolder('0_522_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_assembly_dispatch.xhtml" target="_self">NEGEMMAssemblyDispatch</a></td><td class="desc">Assembly kernel glue </td></tr>
+<tr id="row_0_522_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_assembly_dispatch_1_1_i_fallback.xhtml" target="_self">IFallback</a></td><td class="desc"></td></tr>
+<tr id="row_0_523_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_convolution_layer.xhtml" target="_self">NEGEMMConvolutionLayer</a></td><td class="desc">Basic function to compute the convolution layer </td></tr>
+<tr id="row_0_524_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_interleave4x4.xhtml" target="_self">NEGEMMInterleave4x4</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_interleave4x4_kernel.xhtml" title="NEON kernel to interleave the elements of a matrix. ">NEGEMMInterleave4x4Kernel</a> </td></tr>
+<tr id="row_0_525_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_interleave4x4_kernel.xhtml" target="_self">NEGEMMInterleave4x4Kernel</a></td><td class="desc">NEON kernel to interleave the elements of a matrix </td></tr>
+<tr id="row_0_526_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_interleaved_wrapper.xhtml" target="_self">NEGEMMInterleavedWrapper</a></td><td class="desc">Equivalent to arm_gemm::GemmInterleaved but using Compute Library types </td></tr>
+<tr id="row_0_527_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_assembly_matrix_multiply_core.xhtml" target="_self">NEGEMMLowpAssemblyMatrixMultiplyCore</a></td><td class="desc">Basic function to execute matrix multiply assembly kernels </td></tr>
+<tr id="row_0_528_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_a_reduction_kernel.xhtml" target="_self">NEGEMMLowpMatrixAReductionKernel</a></td><td class="desc">NEON kernel used to compute the row-vectors of sums of all the entries in each row of Matrix A </td></tr>
+<tr id="row_0_529_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_b_reduction_kernel.xhtml" target="_self">NEGEMMLowpMatrixBReductionKernel</a></td><td class="desc">NEON kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B </td></tr>
+<tr id="row_0_530_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_multiply_core.xhtml" target="_self">NEGEMMLowpMatrixMultiplyCore</a></td><td class="desc">Basic function to execute GEMMLowpMatrixMultiplyCore on NEON </td></tr>
+<tr id="row_0_531_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_multiply_kernel.xhtml" target="_self">NEGEMMLowpMatrixMultiplyKernel</a></td><td class="desc">NEON kernel to multiply matrices </td></tr>
+<tr id="row_0_532_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_offset_contribution_kernel.xhtml" target="_self">NEGEMMLowpOffsetContributionKernel</a></td><td class="desc">NEON kernel used to add the offset contribution after <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_multiply_kernel.xhtml">NEGEMMLowpMatrixMultiplyKernel</a> </td></tr>
+<tr id="row_0_533_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8Scale</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" title="Basic function to execute NEGEMMLowpQuantizeDownInt32ToUint8Scale on NEON. ">NEGEMMLowpQuantizeDownInt32ToUint8Scale</a> on NEON </td></tr>
+<tr id="row_0_534_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" title="Basic function to execute NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint on NEON. ">NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a> on NEON </td></tr>
+<tr id="row_0_535_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point_kernel.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel</a></td><td class="desc">NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 </td></tr>
+<tr id="row_0_536_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_kernel.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel</a></td><td class="desc">NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 </td></tr>
+<tr id="row_0_537_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_accumulate_biases_kernel.xhtml" target="_self">NEGEMMMatrixAccumulateBiasesKernel</a></td><td class="desc">NEON kernel to add a bias to each row of the input tensor </td></tr>
+<tr id="row_0_538_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_addition_kernel.xhtml" target="_self">NEGEMMMatrixAdditionKernel</a></td><td class="desc">NEON kernel to perform the in-place matrix addition between 2 matrices taking into account that the second matrix might be weighted by a scalar value beta: </td></tr>
+<tr id="row_0_539_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_multiply_kernel.xhtml" target="_self">NEGEMMMatrixMultiplyKernel</a></td><td class="desc">NEON kernel to multiply two input matrices "A" and "B" </td></tr>
+<tr id="row_0_540_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_vector_multiply_kernel.xhtml" target="_self">NEGEMMMatrixVectorMultiplyKernel</a></td><td class="desc">Interface for the GEMM matrix vector multiply kernel </td></tr>
+<tr id="row_0_541_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_transpose1x_w.xhtml" target="_self">NEGEMMTranspose1xW</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_transpose1x_w_kernel.xhtml" title="NEON kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / ele...">NEGEMMTranspose1xWKernel</a> </td></tr>
+<tr id="row_0_542_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_transpose1x_w_kernel.xhtml" target="_self">NEGEMMTranspose1xWKernel</a></td><td class="desc">NEON kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / element size of the tensor) </td></tr>
+<tr id="row_0_543_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gradient_kernel.xhtml" target="_self">NEGradientKernel</a></td><td class="desc">Computes magnitude and quantised phase from inputs gradients </td></tr>
+<tr id="row_0_544_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_harris_corners.xhtml" target="_self">NEHarrisCorners</a></td><td class="desc">Basic function to execute harris corners detection </td></tr>
+<tr id="row_0_545_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_harris_score_kernel.xhtml" target="_self">NEHarrisScoreKernel</a></td><td class="desc">Template NEON kernel to perform Harris Score </td></tr>
+<tr id="row_0_546_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_histogram.xhtml" target="_self">NEHistogram</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_histogram_kernel.xhtml">NEHistogramKernel</a> </td></tr>
+<tr id="row_0_547_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_histogram_kernel.xhtml" target="_self">NEHistogramKernel</a></td><td class="desc">Interface for the histogram kernel </td></tr>
+<tr id="row_0_548_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_block_normalization_kernel.xhtml" target="_self">NEHOGBlockNormalizationKernel</a></td><td class="desc">NEON kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> block normalization </td></tr>
+<tr id="row_0_549_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_descriptor.xhtml" target="_self">NEHOGDescriptor</a></td><td class="desc">Basic function to calculate <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> descriptor </td></tr>
+<tr id="row_0_550_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_detector.xhtml" target="_self">NEHOGDetector</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector based on linear SVM </td></tr>
+<tr id="row_0_551_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_detector_kernel.xhtml" target="_self">NEHOGDetectorKernel</a></td><td class="desc">NEON kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector kernel using linear SVM </td></tr>
+<tr id="row_0_552_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_gradient.xhtml" target="_self">NEHOGGradient</a></td><td class="desc">Basic function to calculate the gradient for <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
+<tr id="row_0_553_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_multi_detection.xhtml" target="_self">NEHOGMultiDetection</a></td><td class="desc">Basic function to detect multiple objects (or the same object at different scales) on the same input image using <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
+<tr id="row_0_554_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_orientation_binning_kernel.xhtml" target="_self">NEHOGOrientationBinningKernel</a></td><td class="desc">NEON kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> Orientation Binning </td></tr>
+<tr id="row_0_555_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_im2_col.xhtml" target="_self">NEIm2Col</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_im2_col_kernel.xhtml">NEIm2ColKernel</a> </td></tr>
+<tr id="row_0_556_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_im2_col_kernel.xhtml" target="_self">NEIm2ColKernel</a></td><td class="desc">Interface for the im2col reshape kernel </td></tr>
+<tr id="row_0_557_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_integral_image.xhtml" target="_self">NEIntegralImage</a></td><td class="desc">Basic function to run a <a class="el" href="classarm__compute_1_1_n_e_integral_image_kernel.xhtml">NEIntegralImageKernel</a> </td></tr>
+<tr id="row_0_558_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_integral_image_kernel.xhtml" target="_self">NEIntegralImageKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> to perform an image integral on an image </td></tr>
+<tr id="row_0_559_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_l2_normalize_layer.xhtml" target="_self">NEL2NormalizeLayer</a></td><td class="desc">Basic function to perform a L2 normalization on a given axis </td></tr>
+<tr id="row_0_560_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_l2_normalize_layer_kernel.xhtml" target="_self">NEL2NormalizeLayerKernel</a></td><td class="desc">Interface for performing a L2 normalize on a given axis given the square sum of it in this axis </td></tr>
+<tr id="row_0_561_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_laplacian_pyramid.xhtml" target="_self">NELaplacianPyramid</a></td><td class="desc">Basic function to execute laplacian pyramid </td></tr>
+<tr id="row_0_562_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_laplacian_reconstruct.xhtml" target="_self">NELaplacianReconstruct</a></td><td class="desc">Basic function to execute laplacian reconstruction </td></tr>
+<tr id="row_0_563_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_n_e_l_k_internal_keypoint.xhtml" target="_self">NELKInternalKeypoint</a></td><td class="desc">Internal keypoint class for Lucas-Kanade Optical Flow </td></tr>
+<tr id="row_0_564_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_l_k_tracker_kernel.xhtml" target="_self">NELKTrackerKernel</a></td><td class="desc">Interface for the Lucas-Kanade tracker kernel </td></tr>
+<tr id="row_0_565_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_locally_connected_layer.xhtml" target="_self">NELocallyConnectedLayer</a></td><td class="desc">Basic function to compute the locally connected layer </td></tr>
+<tr id="row_0_566_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_locally_connected_matrix_multiply_kernel.xhtml" target="_self">NELocallyConnectedMatrixMultiplyKernel</a></td><td class="desc">NEON kernel to multiply each row of first tensor with low 2 dimensions of second tensor </td></tr>
+<tr id="row_0_567_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_logits1_d_max_kernel.xhtml" target="_self">NELogits1DMaxKernel</a></td><td class="desc">Interface for the identifying the max value of 1D Logits </td></tr>
+<tr id="row_0_568_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_logits1_d_softmax_kernel.xhtml" target="_self">NELogits1DSoftmaxKernel</a></td><td class="desc">Interface for softmax computation for QASYMM8 with pre-computed max </td></tr>
+<tr id="row_0_569_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_magnitude.xhtml" target="_self">NEMagnitude</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_kernel.xhtml" title="Template interface for the kernel to compute magnitude and phase. ">NEMagnitudePhaseKernel</a> </td></tr>
+<tr id="row_0_570_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_kernel.xhtml" target="_self">NEMagnitudePhaseKernel</a></td><td class="desc">Template interface for the kernel to compute magnitude and phase </td></tr>
+<tr id="row_0_571_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_mean_std_dev.xhtml" target="_self">NEMeanStdDev</a></td><td class="desc">Basic function to execute mean and std deviation </td></tr>
+<tr id="row_0_572_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_mean_std_dev_kernel.xhtml" target="_self">NEMeanStdDevKernel</a></td><td class="desc">Interface for the kernel to calculate mean and standard deviation of input image pixels </td></tr>
+<tr id="row_0_573_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_median3x3.xhtml" target="_self">NEMedian3x3</a></td><td class="desc">Basic function to execute median filter </td></tr>
+<tr id="row_0_574_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_median3x3_kernel.xhtml" target="_self">NEMedian3x3Kernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> to perform a median filter on a tensor </td></tr>
+<tr id="row_0_575_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_kernel.xhtml" target="_self">NEMinMaxKernel</a></td><td class="desc">Interface for the kernel to perform min max search on an image </td></tr>
+<tr id="row_0_576_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_layer_kernel.xhtml" target="_self">NEMinMaxLayerKernel</a></td><td class="desc">Interface for the kernel to perform min max search on a 3D tensor </td></tr>
+<tr id="row_0_577_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_location.xhtml" target="_self">NEMinMaxLocation</a></td><td class="desc">Basic function to execute min and max location </td></tr>
+<tr id="row_0_578_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_location_kernel.xhtml" target="_self">NEMinMaxLocationKernel</a></td><td class="desc">Interface for the kernel to find min max locations of an image </td></tr>
+<tr id="row_0_579_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_linear_filter.xhtml" target="_self">NENonLinearFilter</a></td><td class="desc">Basic function to execute non linear filter </td></tr>
+<tr id="row_0_580_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_linear_filter_kernel.xhtml" target="_self">NENonLinearFilterKernel</a></td><td class="desc">Interface for the kernel to apply a non-linear filter </td></tr>
+<tr id="row_0_581_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_maxima_suppression3x3.xhtml" target="_self">NENonMaximaSuppression3x3</a></td><td class="desc">Basic function to execute non-maxima suppression over a 3x3 window </td></tr>
+<tr id="row_0_582_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_maxima_suppression3x3_kernel.xhtml" target="_self">NENonMaximaSuppression3x3Kernel</a></td><td class="desc">Interface to perform Non-Maxima suppression over a 3x3 window using NEON </td></tr>
+<tr id="row_0_583_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_normalization_layer.xhtml" target="_self">NENormalizationLayer</a></td><td class="desc">Basic function to compute a normalization layer </td></tr>
+<tr id="row_0_584_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_normalization_layer_kernel.xhtml" target="_self">NENormalizationLayerKernel</a></td><td class="desc">Interface for the normalization layer kernel </td></tr>
+<tr id="row_0_585_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_optical_flow.xhtml" target="_self">NEOpticalFlow</a></td><td class="desc">Basic function to execute optical flow </td></tr>
+<tr id="row_0_586_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_permute.xhtml" target="_self">NEPermute</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_permute_kernel.xhtml">NEPermuteKernel</a> </td></tr>
+<tr id="row_0_587_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_permute_kernel.xhtml" target="_self">NEPermuteKernel</a></td><td class="desc">NEON kernel to perform tensor permutation </td></tr>
+<tr id="row_0_588_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_phase.xhtml" target="_self">NEPhase</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_kernel.xhtml" title="Template interface for the kernel to compute magnitude and phase. ">NEMagnitudePhaseKernel</a> </td></tr>
+<tr id="row_0_589_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pixel_wise_multiplication.xhtml" target="_self">NEPixelWiseMultiplication</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_pixel_wise_multiplication_kernel.xhtml">NEPixelWiseMultiplicationKernel</a> </td></tr>
+<tr id="row_0_590_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pixel_wise_multiplication_kernel.xhtml" target="_self">NEPixelWiseMultiplicationKernel</a></td><td class="desc">Interface for the kernel to perform addition between two tensors </td></tr>
+<tr id="row_0_591_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pooling_layer.xhtml" target="_self">NEPoolingLayer</a></td><td class="desc">Basic function to simulate a pooling layer with the specified pooling operation </td></tr>
+<tr id="row_0_592_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pooling_layer_kernel.xhtml" target="_self">NEPoolingLayerKernel</a></td><td class="desc">Interface for the pooling layer kernel </td></tr>
+<tr id="row_0_593_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_quantization_layer.xhtml" target="_self">NEQuantizationLayer</a></td><td class="desc">Basic function to simulate a quantization layer </td></tr>
+<tr id="row_0_594_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_quantization_layer_kernel.xhtml" target="_self">NEQuantizationLayerKernel</a></td><td class="desc">Interface for the quantization layer kernel </td></tr>
+<tr id="row_0_595_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reduction_operation.xhtml" target="_self">NEReductionOperation</a></td><td class="desc">Basic function to simulate a reduction operation </td></tr>
+<tr id="row_0_596_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reduction_operation_kernel.xhtml" target="_self">NEReductionOperationKernel</a></td><td class="desc">NEON kernel to perform a reduction operation </td></tr>
+<tr id="row_0_597_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_remap.xhtml" target="_self">NERemap</a></td><td class="desc">Basic function to execute remap </td></tr>
+<tr id="row_0_598_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_remap_kernel.xhtml" target="_self">NERemapKernel</a></td><td class="desc">NEON kernel to perform a remap on a tensor </td></tr>
+<tr id="row_0_599_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reshape_layer.xhtml" target="_self">NEReshapeLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_reshape_layer_kernel.xhtml">NEReshapeLayerKernel</a> </td></tr>
+<tr id="row_0_600_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reshape_layer_kernel.xhtml" target="_self">NEReshapeLayerKernel</a></td><td class="desc">Interface for the kernel to perform tensor reshaping </td></tr>
+<tr id="row_0_601_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_r_n_n_layer.xhtml" target="_self">NERNNLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_r_n_n_layer.xhtml">NERNNLayer</a> </td></tr>
+<tr id="row_0_602_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer.xhtml" target="_self">NEROIPoolingLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer_kernel.xhtml">NEROIPoolingLayerKernel</a> </td></tr>
+<tr id="row_0_603_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer_kernel.xhtml" target="_self">NEROIPoolingLayerKernel</a></td><td class="desc">Interface for the <a class="el" href="structarm__compute_1_1_r_o_i.xhtml" title="Region of interest. ">ROI</a> pooling layer kernel </td></tr>
+<tr id="row_0_604_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scale.xhtml" target="_self">NEScale</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_scale_kernel.xhtml">NEScaleKernel</a> </td></tr>
+<tr id="row_0_605_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scale_kernel.xhtml" target="_self">NEScaleKernel</a></td><td class="desc">NEON kernel to perform scaling on a tensor </td></tr>
+<tr id="row_0_606_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scharr3x3.xhtml" target="_self">NEScharr3x3</a></td><td class="desc">Basic function to execute scharr 3x3 filter </td></tr>
+<tr id="row_0_607_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scharr3x3_kernel.xhtml" target="_self">NEScharr3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Scharr filter on a tensor </td></tr>
+<tr id="row_0_608_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_separable_convolution_hor_kernel.xhtml" target="_self">NESeparableConvolutionHorKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the Horizontal pass of a Separable Convolution </td></tr>
+<tr id="row_0_609_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_separable_convolution_vert_kernel.xhtml" target="_self">NESeparableConvolutionVertKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the Vertical pass of a Separable Convolution </td></tr>
+<tr id="row_0_610_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_simple_assembly_function.xhtml" target="_self">NESimpleAssemblyFunction</a></td><td class="desc">Basic interface for functions which have a single NEON GEMM wrapper kernel to run </td></tr>
+<tr id="row_0_611_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel3x3.xhtml" target="_self">NESobel3x3</a></td><td class="desc">Basic function to execute sobel 3x3 filter </td></tr>
+<tr id="row_0_612_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel3x3_kernel.xhtml" target="_self">NESobel3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Sobel X filter on a tensor </td></tr>
+<tr id="row_0_613_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel5x5.xhtml" target="_self">NESobel5x5</a></td><td class="desc">Basic function to execute sobel 5x5 filter </td></tr>
+<tr id="row_0_614_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel5x5_hor_kernel.xhtml" target="_self">NESobel5x5HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 5x5 Sobel filter on a tensor </td></tr>
+<tr id="row_0_615_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel5x5_vert_kernel.xhtml" target="_self">NESobel5x5VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 5x5 Sobel Y filter on a tensor </td></tr>
+<tr id="row_0_616_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel7x7.xhtml" target="_self">NESobel7x7</a></td><td class="desc">Basic function to execute sobel 7x7 filter </td></tr>
+<tr id="row_0_617_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel7x7_hor_kernel.xhtml" target="_self">NESobel7x7HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 7x7 Sobel filter on a tensor </td></tr>
+<tr id="row_0_618_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel7x7_vert_kernel.xhtml" target="_self">NESobel7x7VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 7x7 Sobel Y filter on a tensor </td></tr>
+<tr id="row_0_619_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_softmax_layer.xhtml" target="_self">NESoftmaxLayer</a></td><td class="desc">Basic function to compute a SoftmaxLayer </td></tr>
+<tr id="row_0_620_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_table_lookup.xhtml" target="_self">NETableLookup</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_table_lookup_kernel.xhtml">NETableLookupKernel</a> </td></tr>
+<tr id="row_0_621_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_table_lookup_kernel.xhtml" target="_self">NETableLookupKernel</a></td><td class="desc">Interface for the kernel to perform table lookup calculations </td></tr>
+<tr id="row_0_622_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_threshold.xhtml" target="_self">NEThreshold</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_threshold_kernel.xhtml">NEThresholdKernel</a> </td></tr>
+<tr id="row_0_623_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_threshold_kernel.xhtml" target="_self">NEThresholdKernel</a></td><td class="desc">Interface for the thresholding kernel </td></tr>
+<tr id="row_0_624_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_transpose.xhtml" target="_self">NETranspose</a></td><td class="desc">Basic function to transpose a matrix on NEON </td></tr>
+<tr id="row_0_625_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_transpose_kernel.xhtml" target="_self">NETransposeKernel</a></td><td class="desc">NEON kernel which transposes the elements of a matrix </td></tr>
+<tr id="row_0_626_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_affine.xhtml" target="_self">NEWarpAffine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_warp_affine_kernel.xhtml">NEWarpAffineKernel</a> </td></tr>
+<tr id="row_0_627_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_affine_kernel.xhtml" target="_self">NEWarpAffineKernel</a></td><td class="desc">Template interface for the kernel to compute warp affine </td></tr>
+<tr id="row_0_628_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_perspective.xhtml" target="_self">NEWarpPerspective</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_warp_perspective_kernel.xhtml">NEWarpPerspectiveKernel</a> </td></tr>
+<tr id="row_0_629_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_perspective_kernel.xhtml" target="_self">NEWarpPerspectiveKernel</a></td><td class="desc">Template interface for the kernel to compute warp perspective </td></tr>
+<tr id="row_0_630_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_weights_reshape_kernel.xhtml" target="_self">NEWeightsReshapeKernel</a></td><td class="desc">NEON kernel to perform reshaping on the weights used by convolution and locally connected layer </td></tr>
+<tr id="row_0_631_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_width_concatenate_layer.xhtml" target="_self">NEWidthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along x axis </td></tr>
+<tr id="row_0_632_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_width_concatenate_layer_kernel.xhtml" target="_self">NEWidthConcatenateLayerKernel</a></td><td class="desc">Interface for the width concatenate kernel </td></tr>
+<tr id="row_0_633_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_convolution_layer.xhtml" target="_self">NEWinogradConvolutionLayer</a></td><td class="desc">Basic function to simulate a convolution layer </td></tr>
+<tr id="row_0_634_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_configuration.xhtml" target="_self">NEWinogradLayerConfiguration</a></td><td class="desc">NEON kernel to perform Winograd </td></tr>
+<tr id="row_0_635_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_input_kernel.xhtml" target="_self">NEWinogradLayerTransformInputKernel</a></td><td class="desc">NEON kernel to perform Winograd input transform </td></tr>
+<tr id="row_0_636_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_output_kernel.xhtml" target="_self">NEWinogradLayerTransformOutputKernel</a></td><td class="desc">NEON kernel to perform Winograd output transform </td></tr>
+<tr id="row_0_637_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml" target="_self">NEWinogradLayerTransformWeightsKernel</a></td><td class="desc">NEON kernel to perform Winograd weights transform </td></tr>
+<tr id="row_0_638_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_normalization_layer_info.xhtml" target="_self">NormalizationLayerInfo</a></td><td class="desc">Normalization Layer Information class </td></tr>
+<tr id="row_0_639_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_offset_lifetime_manager.xhtml" target="_self">OffsetLifetimeManager</a></td><td class="desc">Concrete class that tracks the lifetime of registered tensors and calculates the systems memory requirements in terms of a single blob and a list of offsets </td></tr>
+<tr id="row_0_640_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_offset_memory_pool.xhtml" target="_self">OffsetMemoryPool</a></td><td class="desc">Offset based memory pool </td></tr>
+<tr id="row_0_641_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_o_m_p_scheduler.xhtml" target="_self">OMPScheduler</a></td><td class="desc">Pool of threads to automatically split a kernel's execution among several threads </td></tr>
+<tr id="row_0_642_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_optical_flow_parameters.xhtml" target="_self">OpticalFlowParameters</a></td><td class="desc">Parameters of Optical Flow algorithm </td></tr>
+<tr id="row_0_643_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml" target="_self">PadStrideInfo</a></td><td class="desc">Padding and stride information class </td></tr>
+<tr id="row_0_644_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pixel_value.xhtml" target="_self">PixelValue</a></td><td class="desc">Class describing the value of a pixel for any image format </td></tr>
+<tr id="row_0_645_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pooling_layer_info.xhtml" target="_self">PoolingLayerInfo</a></td><td class="desc">Pooling Layer Information class </td></tr>
+<tr id="row_0_646_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pool_manager.xhtml" target="_self">PoolManager</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> pool manager </td></tr>
+<tr id="row_0_647_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_program.xhtml" target="_self">Program</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_program.xhtml" title="Program class. ">Program</a> class </td></tr>
+<tr id="row_0_648_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pyramid.xhtml" target="_self">Pyramid</a></td><td class="desc">Basic implementation of the pyramid interface </td></tr>
+<tr id="row_0_649_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pyramid_info.xhtml" target="_self">PyramidInfo</a></td><td class="desc">Store the <a class="el" href="classarm__compute_1_1_pyramid.xhtml" title="Basic implementation of the pyramid interface. ">Pyramid</a>'s metadata </td></tr>
+<tr id="row_0_650_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_quantization_info.xhtml" target="_self">QuantizationInfo</a></td><td class="desc">Quantization settings (used for QASYMM8 data type) </td></tr>
+<tr id="row_0_651_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_rectangle.xhtml" target="_self">Rectangle</a></td><td class="desc"><a class="el" href="structarm__compute_1_1_rectangle.xhtml" title="Rectangle type. ">Rectangle</a> type </td></tr>
+<tr id="row_0_652_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_r_o_i.xhtml" target="_self">ROI</a></td><td class="desc">Region of interest </td></tr>
+<tr id="row_0_653_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_r_o_i_pooling_layer_info.xhtml" target="_self">ROIPoolingLayerInfo</a></td><td class="desc"><a class="el" href="structarm__compute_1_1_r_o_i.xhtml" title="Region of interest. ">ROI</a> Pooling Layer Information class </td></tr>
+<tr id="row_0_654_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_scheduler.xhtml" target="_self">Scheduler</a></td><td class="desc">Configurable scheduler which supports multiple multithreading APIs and choosing between different schedulers at runtime </td></tr>
+<tr id="row_0_655_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_semaphore.xhtml" target="_self">Semaphore</a></td><td class="desc">Semamphore class </td></tr>
+<tr id="row_0_656_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_single_thread_scheduler.xhtml" target="_self">SingleThreadScheduler</a></td><td class="desc">Pool of threads to automatically split a kernel's execution among several threads </td></tr>
+<tr id="row_0_657_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_size2_d.xhtml" target="_self">Size2D</a></td><td class="desc">Class for specifying the size of an image or rectangle </td></tr>
+<tr id="row_0_658_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_status.xhtml" target="_self">Status</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_status.xhtml" title="Status class. ">Status</a> class </td></tr>
+<tr id="row_0_659_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_steps.xhtml" target="_self">Steps</a></td><td class="desc">Class to describe a number of elements in each dimension </td></tr>
+<tr id="row_0_660_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_strides.xhtml" target="_self">Strides</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_strides.xhtml" title="Strides of an item in bytes. ">Strides</a> of an item in bytes </td></tr>
+<tr id="row_0_661_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_sub_tensor.xhtml" target="_self">SubTensor</a></td><td class="desc">Basic implementation of the sub-tensor interface </td></tr>
+<tr id="row_0_662_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_sub_tensor_info.xhtml" target="_self">SubTensorInfo</a></td><td class="desc">Store the sub tensor's metadata </td></tr>
+<tr id="row_0_663_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_tensor.xhtml" target="_self">Tensor</a></td><td class="desc">Basic implementation of the tensor interface </td></tr>
+<tr id="row_0_664_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_tensor_accessor.xhtml" target="_self">TensorAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> accessors to make it easier to interface with arm_gemm </td></tr>
+<tr id="row_0_665_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_tensor_allocator.xhtml" target="_self">TensorAllocator</a></td><td class="desc">Basic implementation of a CPU memory tensor allocator </td></tr>
+<tr id="row_0_666_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_tensor_info.xhtml" target="_self">TensorInfo</a></td><td class="desc">Store the tensor's metadata </td></tr>
+<tr id="row_0_667_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_tensor_shape.xhtml" target="_self">TensorShape</a></td><td class="desc">Shape of a tensor </td></tr>
+<tr id="row_0_668_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_thread_info.xhtml" target="_self">ThreadInfo</a></td><td class="desc">Information about executing thread and CPU </td></tr>
+<tr id="row_0_669_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_valid_region.xhtml" target="_self">ValidRegion</a></td><td class="desc">Container for valid region of a window </td></tr>
+<tr id="row_0_670_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_weights_info.xhtml" target="_self">WeightsInfo</a></td><td class="desc">Convolution Layer Weights Information class </td></tr>
+<tr id="row_0_671_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_671_" class="arrow" onclick="toggleFolder('0_671_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_window.xhtml" target="_self">Window</a></td><td class="desc">Describe a multidimensional execution window </td></tr>
+<tr id="row_0_671_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_window_1_1_dimension.xhtml" target="_self">Dimension</a></td><td class="desc">Describe one of the image's dimensions with a start, end and step </td></tr>
+<tr id="row_0_672_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_window_iterator.xhtml" target="_self">WindowIterator</a></td><td class="desc">Iterate over a portion of a <a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> </td></tr>
+<tr id="row_0_673_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_winograd_info.xhtml" target="_self">WinogradInfo</a></td><td class="desc">Winograd information </td></tr>
<tr id="row_1_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="struct_coordinates2_d.xhtml" target="_self">Coordinates2D</a></td><td class="desc">2D Coordinates structure </td></tr>
<tr id="row_2_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="struct_detection_window.xhtml" target="_self">DetectionWindow</a></td><td class="desc">Detection window struct </td></tr>
<tr id="row_3_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="struct_image.xhtml" target="_self">Image</a></td><td class="desc">Structure to hold <a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> information </td></tr>
@@ -1064,7 +1086,7 @@
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<img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.11 </li>
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