arm_compute v17.09
Change-Id: I4bf8f4e6e5f84ce0d5b6f5ba570d276879f42a81
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index ff4946e..c8565c0 100644
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@@ -4,7 +4,7 @@
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<div id="projectname">Compute Library
-  <span id="projectnumber">v17.06</span>
+  <span id="projectnumber">17.09</span>
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@@ -123,638 +121,870 @@
<p><a href="inherits.xhtml">Go to the graphical class hierarchy</a></p>
This inheritance list is sorted roughly, but not completely, alphabetically:</div><div class="directory">
<div class="levels">[detail level <span onclick="javascript:toggleLevel(1);">1</span><span onclick="javascript:toggleLevel(2);">2</span><span onclick="javascript:toggleLevel(3);">3</span><span onclick="javascript:toggleLevel(4);">4</span><span onclick="javascript:toggleLevel(5);">5</span><span onclick="javascript:toggleLevel(6);">6</span>]</div><table class="directory">
-<tr id="row_0_" 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="structarm__compute_1_1test_1_1cpp14_1_1___unique__if.xhtml" target="_self">_Unique_if< T ></a></td><td class="desc">Make_unqiue is missing in CPP11 </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="structarm__compute_1_1cpp14_1_1___unique__if.xhtml" target="_self">_Unique_if< T ></a></td><td class="desc"></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="structarm__compute_1_1test_1_1cpp14_1_1___unique__if_3_01_t[]_4.xhtml" target="_self">_Unique_if< T[]></a></td><td class="desc"></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="structarm__compute_1_1cpp14_1_1___unique__if_3_01_t[]_4.xhtml" target="_self">_Unique_if< T[]></a></td><td class="desc"></td></tr>
-<tr id="row_4_" 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="structarm__compute_1_1test_1_1cpp14_1_1___unique__if_3_01_t[_n]_4.xhtml" target="_self">_Unique_if< T[N]></a></td><td class="desc"></td></tr>
-<tr id="row_5_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1cpp14_1_1___unique__if_3_01_t[_n]_4.xhtml" target="_self">_Unique_if< T[N]></a></td><td class="desc"></td></tr>
-<tr id="row_6_" 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="classarm__compute_1_1test_1_1_activation_layer_data_object.xhtml" target="_self">ActivationLayerDataObject</a></td><td class="desc"></td></tr>
-<tr id="row_7_"><td class="entry"><span style="width:16px;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_8_" 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="classarm__compute_1_1test_1_1model__objects_1_1_alex_net.xhtml" target="_self">AlexNet< ITensorType, TensorType, SubTensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, NormalizationLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction, dt, fixed_point_position ></a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1model__objects_1_1_alex_net.xhtml" title="AlexNet model object. ">AlexNet</a> model object </td></tr>
-<tr id="row_9_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1model__objects_1_1_alex_net.xhtml" target="_self">AlexNet< ITensorType, TensorType, SubTensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, NormalizationLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction, dt ></a></td><td class="desc"></td></tr>
-<tr id="row_10_" 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="classarm__compute_1_1test_1_1_batch_normalization_layer_data_object.xhtml" target="_self">BatchNormalizationLayerDataObject</a></td><td class="desc"></td></tr>
-<tr id="row_11_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_border_modes.xhtml" target="_self">BorderModes</a></td><td class="desc">Data set containing all possible border modes </td></tr>
-<tr id="row_12_" 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="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_13_"><td class="entry"><span style="width:16px;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_14_" 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="structarm__compute_1_1test_1_1validation_1_1cl_1_1_c_l_fixture.xhtml" target="_self">CLFixture</a></td><td class="desc"></td></tr>
-<tr id="row_15_"><td class="entry"><span style="width:16px;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_16_" 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="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_17_"><td class="entry"><span style="width:16px;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_18_" 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="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_19_"><td class="entry"><span style="width:16px;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< T ></a></td><td class="desc">Find the signed promoted common type </td></tr>
-<tr id="row_20_" 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="classarm__compute_1_1detail_1_1compare__dimension.xhtml" target="_self">compare_dimension< T ></a></td><td class="desc">Functor to compare two <a class="el" href="classarm__compute_1_1_dimensions.xhtml">Dimensions</a> objects and throw an error on mismatch </td></tr>
-<tr id="row_21_"><td class="entry"><span style="width:16px;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< T ></a></td><td class="desc"></td></tr>
-<tr id="row_22_" 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="classarm__compute_1_1test_1_1_convert_policies.xhtml" target="_self">ConvertPolicies</a></td><td class="desc">Data set containing all possible convert/overflow policies </td></tr>
-<tr id="row_23_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_convolution_layer_data_object.xhtml" target="_self">ConvolutionLayerDataObject</a></td><td class="desc">Convolution Layer data object </td></tr>
-<tr id="row_24_" 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_coordinates2_d.xhtml" target="_self">Coordinates2D</a></td><td class="desc">2D Coordinates structure </td></tr>
-<tr id="row_25_"><td class="entry"><span style="width:16px;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_26_" 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="structarm__compute_1_1_coordinates3_d.xhtml" target="_self">Coordinates3D</a></td><td class="desc">Coordinate type </td></tr>
-<tr id="row_27_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_data_types.xhtml" target="_self">DataTypes< Size ></a></td><td class="desc">Abstract data set containing data types </td></tr>
-<tr id="row_28_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_28_" class="arrow" onclick="toggleFolder('28_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_data_types.xhtml" target="_self">DataTypes< 1 ></a></td><td class="desc"></td></tr>
-<tr id="row_28_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_n_n_fixed_point_data_types.xhtml" target="_self">CNNFixedPointDataTypes</a></td><td class="desc">Supported CNN fixed point types </td></tr>
-<tr id="row_28_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_n_n_float_data_types.xhtml" target="_self">CNNFloatDataTypes</a></td><td class="desc">Supported CNN float types </td></tr>
-<tr id="row_29_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_29_" class="arrow" onclick="toggleFolder('29_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_data_types.xhtml" target="_self">DataTypes< 14 ></a></td><td class="desc"></td></tr>
-<tr id="row_29_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_all_data_types.xhtml" target="_self">AllDataTypes</a></td><td class="desc">Data set containing all data types </td></tr>
-<tr id="row_30_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_30_" class="arrow" onclick="toggleFolder('30_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_data_types.xhtml" target="_self">DataTypes< 2 ></a></td><td class="desc"></td></tr>
-<tr id="row_30_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_n_n_data_types.xhtml" target="_self">CNNDataTypes</a></td><td class="desc">Supported CNN types </td></tr>
-<tr id="row_30_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_fixed_point_data_types.xhtml" target="_self">FixedPointDataTypes</a></td><td class="desc">Data set containing all fixed point data types </td></tr>
-<tr id="row_31_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_31_" class="arrow" onclick="toggleFolder('31_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_data_types.xhtml" target="_self">DataTypes< 3 ></a></td><td class="desc"></td></tr>
-<tr id="row_31_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_float_data_types.xhtml" target="_self">FloatDataTypes</a></td><td class="desc">Data set containing all floating point data types </td></tr>
-<tr id="row_32_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_32_" class="arrow" onclick="toggleFolder('32_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_data_types.xhtml" target="_self">DataTypes< 4 ></a></td><td class="desc"></td></tr>
-<tr id="row_32_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_signed_data_types.xhtml" target="_self">SignedDataTypes</a></td><td class="desc">Data set containing all signed data types </td></tr>
-<tr id="row_32_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_unsigned_data_types.xhtml" target="_self">UnsignedDataTypes</a></td><td class="desc">Data set containing all unsigned data types </td></tr>
-<tr id="row_33_"><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_34_" 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="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_35_"><td class="entry"><span style="width:16px;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">Window::Dimension</a></td><td class="desc">Describe one of the image's dimensions with a start, end and step </td></tr>
-<tr id="row_36_" 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="classarm__compute_1_1_dimensions.xhtml" target="_self">Dimensions< T ></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_37_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_37_" class="arrow" onclick="toggleFolder('37_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_dimensions.xhtml" target="_self">Dimensions< int ></a></td><td class="desc"></td></tr>
-<tr id="row_37_0_" class="even" style="display:none;"><td class="entry"><span 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_38_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_38_" class="arrow" onclick="toggleFolder('38_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_dimensions.xhtml" target="_self">Dimensions< size_t ></a></td><td class="desc"></td></tr>
-<tr id="row_38_0_" style="display:none;"><td class="entry"><span 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_38_1_" style="display:none;"><td class="entry"><span 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_39_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_39_" class="arrow" onclick="toggleFolder('39_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_dimensions.xhtml" target="_self">Dimensions< unsigned int ></a></td><td class="desc"></td></tr>
-<tr id="row_39_0_" class="even" style="display:none;"><td class="entry"><span 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_40_" 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="structarm__compute_1_1enable__bitwise__ops.xhtml" target="_self">enable_bitwise_ops< T ></a></td><td class="desc"></td></tr>
-<tr id="row_41_"><td class="entry"><span style="width:16px;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 operation operations on GPUTarget enumerations </td></tr>
-<tr id="row_42_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_42_" class="arrow" onclick="toggleFolder('42_')">►</span><span class="icona"><span class="icon">C</span></span><b>false_type</b></td><td class="desc"></td></tr>
-<tr id="row_42_0_" style="display:none;"><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_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_43_"><td class="entry"><span style="width:16px;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< T ></a></td><td class="desc">Arbitrary fixed-point arithmetic class </td></tr>
-<tr id="row_44_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_44_" class="arrow" onclick="toggleFolder('44_')">►</span><span class="icona"><span class="icon">C</span></span><b>Fixture</b></td><td class="desc"></td></tr>
-<tr id="row_44_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_activation_layer.xhtml" target="_self">ActivationLayer< DataSet, TensorType, Accessor, Function, dt ></a></td><td class="desc"></td></tr>
-<tr id="row_44_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_alex_net_fixture.xhtml" target="_self">AlexNetFixture< ITensorType, TensorType, SubTensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, NormalizationLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction, dt ></a></td><td class="desc"></td></tr>
-<tr id="row_44_2_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_convolution_layer.xhtml" target="_self">ConvolutionLayer< DataSet, TensorType, Accessor, Function, dt ></a></td><td class="desc"></td></tr>
-<tr id="row_44_3_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_fully_connected_layer.xhtml" target="_self">FullyConnectedLayer< DataSet, TensorType, Accessor, Function, dt ></a></td><td class="desc"></td></tr>
-<tr id="row_44_4_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_g_e_m_m.xhtml" target="_self">GEMM< DataSet, TensorType, Accessor, Function, data_type ></a></td><td class="desc"></td></tr>
-<tr id="row_44_5_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_g_e_m_m.xhtml" target="_self">GEMM< DataSet, TensorType, Accessor, Function, data_type ></a></td><td class="desc"></td></tr>
-<tr id="row_44_6_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_le_net5_fixture.xhtml" target="_self">LeNet5Fixture< TensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction ></a></td><td class="desc"></td></tr>
-<tr id="row_44_7_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_normalization_layer.xhtml" target="_self">NormalizationLayer< DataSet, TensorType, Accessor, Function, dt ></a></td><td class="desc"></td></tr>
-<tr id="row_44_8_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_pooling_layer.xhtml" target="_self">PoolingLayer< DataSet, TensorType, Accessor, Function, dt ></a></td><td class="desc"></td></tr>
-<tr id="row_45_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_fully_connected_layer_data_object.xhtml" target="_self">FullyConnectedLayerDataObject</a></td><td class="desc"></td></tr>
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-<tr id="row_48_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_48_" class="arrow" onclick="toggleFolder('48_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_generic_dataset.xhtml" target="_self">GenericDataset< T, Size ></a></td><td class="desc">Abstract data set containing multiple objects T </td></tr>
-<tr id="row_48_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_alex_net_activation_layer_dataset.xhtml" target="_self">AlexNetActivationLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_alex_net_convolution_layer_dataset.xhtml" target="_self">AlexNetConvolutionLayerDataset</a></td><td class="desc">AlexNet's convolution layers tensor shapes </td></tr>
-<tr id="row_48_2_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_alex_net_fully_connected_layer_dataset.xhtml" target="_self">AlexNetFullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_3_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_alex_net_normalization_layer_dataset.xhtml" target="_self">AlexNetNormalizationLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_4_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_alex_net_pooling_layer_dataset.xhtml" target="_self">AlexNetPoolingLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_5_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_goog_le_net_activation_layer_dataset.xhtml" target="_self">GoogLeNetActivationLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_6_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_goog_le_net_convolution_layer_dataset1.xhtml" target="_self">GoogLeNetConvolutionLayerDataset1</a></td><td class="desc">GoogleLeNet v1 convolution layers tensor shapes (Part 1) </td></tr>
-<tr id="row_48_7_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_goog_le_net_convolution_layer_dataset2.xhtml" target="_self">GoogLeNetConvolutionLayerDataset2</a></td><td class="desc">GoogleLeNet v1 convolution layers tensor shapes (Part 2) </td></tr>
-<tr id="row_48_8_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_goog_le_net_fully_connected_layer_dataset.xhtml" target="_self">GoogLeNetFullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_9_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_goog_le_net_normalization_layer_dataset.xhtml" target="_self">GoogLeNetNormalizationLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_10_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_goog_le_net_pooling_layer_dataset.xhtml" target="_self">GoogLeNetPoolingLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_11_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_large_fully_connected_layer_dataset.xhtml" target="_self">LargeFullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_12_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_le_net5_activation_layer_dataset.xhtml" target="_self">LeNet5ActivationLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_13_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_le_net5_convolution_layer_dataset.xhtml" target="_self">LeNet5ConvolutionLayerDataset</a></td><td class="desc">LeNet5's convolution layers tensor shapes </td></tr>
-<tr id="row_48_14_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_le_net5_fully_connected_layer_dataset.xhtml" target="_self">LeNet5FullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_15_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_le_net5_pooling_layer_dataset.xhtml" target="_self">LeNet5PoolingLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_16_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_random_batch_normalization_layer_dataset.xhtml" target="_self">RandomBatchNormalizationLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_17_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_random_pooling_layer_dataset.xhtml" target="_self">RandomPoolingLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_48_18_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_small_convolution_layer_dataset.xhtml" target="_self">SmallConvolutionLayerDataset</a></td><td class="desc">Data set containing small convolution layer shapes </td></tr>
-<tr id="row_48_19_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_small_fully_connected_layer_dataset.xhtml" target="_self">SmallFullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
-<tr id="row_49_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_49_" class="arrow" onclick="toggleFolder('49_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_generic_dataset.xhtml" target="_self">GenericDataset< ActivationLayerInfo::ActivationFunction, 9 ></a></td><td class="desc"></td></tr>
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-<tr id="row_50_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_50_" class="arrow" onclick="toggleFolder('50_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_generic_dataset.xhtml" target="_self">GenericDataset< GEMMDataObject, 32 ></a></td><td class="desc"></td></tr>
-<tr id="row_50_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_goog_le_net_g_e_m_m_dataset1.xhtml" target="_self">GoogLeNetGEMMDataset1</a></td><td class="desc"></td></tr>
-<tr id="row_50_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_goog_le_net_g_e_m_m_dataset2.xhtml" target="_self">GoogLeNetGEMMDataset2</a></td><td class="desc"></td></tr>
-<tr id="row_51_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_51_" class="arrow" onclick="toggleFolder('51_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_generic_dataset.xhtml" target="_self">GenericDataset< GEMMDataObject, 4 ></a></td><td class="desc"></td></tr>
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-<tr id="row_52_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_threshold_dataset.xhtml" target="_self">ThresholdDataset</a></td><td class="desc"></td></tr>
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-<tr id="row_55_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_55_" class="arrow" onclick="toggleFolder('55_')">►</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>
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-<tr id="row_56_0_" style="display:none;"><td class="entry"><span 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< T ></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_56_1_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_56_1_" class="arrow" onclick="toggleFolder('56_1_')">►</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< T ></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_56_1_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_c_l_array.xhtml" target="_self">CLArray< T ></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_57_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_57_" class="arrow" onclick="toggleFolder('57_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_array.xhtml" target="_self">IArray< NELKInternalKeypoint ></a></td><td class="desc"></td></tr>
-<tr id="row_57_0_" class="even" style="display:none;"><td class="entry"><span 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< NELKInternalKeypoint ></a></td><td class="desc"></td></tr>
-<tr id="row_58_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_58_" class="arrow" onclick="toggleFolder('58_')">►</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_58_0_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_58_0_" class="arrow" onclick="toggleFolder('58_0_')">►</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_58_0_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_distribution1_d.xhtml" target="_self">Distribution1D</a></td><td class="desc">Basic implementation of the 1D distribution interface </td></tr>
-<tr id="row_58_0_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_58_0_1_" class="arrow" onclick="toggleFolder('58_0_1_')">►</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_58_0_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_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_59_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_59_" class="arrow" onclick="toggleFolder('59_')">►</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_59_0_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_1_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_2_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_3_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_4_" class="even" style="display:none;"><td class="entry"><span style="width: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< matrix_size ></a></td><td class="desc">Basic function to execute square convolution.Currently it supports 5x5, 7x7, 9x9 </td></tr>
-<tr id="row_59_5_" class="even" style="display:none;"><td class="entry"><span style="width: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.xhtml" target="_self">CLDepthConcatenate</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
-<tr id="row_59_6_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_7_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_8_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_9_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_10_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_11_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_59_11_" class="arrow" onclick="toggleFolder('59_11_')">►</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_59_11_0_" class="even" 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_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_59_11_1_" class="even" 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_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_59_12_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_13_" class="even" style="display:none;"><td class="entry"><span style="width: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.xhtml" target="_self">CLGEMMLowp</a></td><td class="desc">Basic function to execute GEMMLowp on OpenCL </td></tr>
-<tr id="row_59_14_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_15_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_16_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_17_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_18_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_19_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_20_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_21_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_22_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_23_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_24_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_25_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_26_" class="even" style="display:none;"><td class="entry"><span style="width: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 simulate a normalization layer </td></tr>
-<tr id="row_59_27_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_28_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_29_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_30_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_31_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_59_31_" class="arrow" onclick="toggleFolder('59_31_')">►</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_59_31_0_" class="even" 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_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_59_31_1_" class="even" 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_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_59_31_2_" class="even" 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_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_59_31_3_" class="even" 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_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_59_31_4_" class="even" 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_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_59_31_5_" class="even" 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_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_59_31_6_" class="even" 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_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_59_31_7_" class="even" 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_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_59_31_8_" class="even" 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_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_59_31_9_" class="even" 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_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_59_31_10_" class="even" 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_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_59_31_11_" class="even" 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_c_l_box3x3.xhtml" target="_self">CLBox3x3</a></td><td class="desc">Basic function to execute box filter 3x3 </td></tr>
-<tr id="row_59_31_12_" class="even" 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_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_59_31_13_" class="even" 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_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_59_31_14_" class="even" 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_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_59_31_15_" class="even" 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_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_59_31_16_" class="even" 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_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_59_31_17_" class="even" 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_c_l_depth_convert.xhtml" target="_self">CLDepthConvert</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_depth_convert_kernel.xhtml">CLDepthConvertKernel</a> </td></tr>
-<tr id="row_59_31_18_" class="even" 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_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_59_31_19_" class="even" 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_c_l_dilate.xhtml" target="_self">CLDilate</a></td><td class="desc">Basic function to execute dilate </td></tr>
-<tr id="row_59_31_20_" class="even" 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_c_l_erode.xhtml" target="_self">CLErode</a></td><td class="desc">Basic function to execute erode </td></tr>
-<tr id="row_59_31_21_" class="even" 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_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_59_31_22_" class="even" 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_c_l_gaussian3x3.xhtml" target="_self">CLGaussian3x3</a></td><td class="desc">Basic function to execute gaussian filter 3x3 </td></tr>
-<tr id="row_59_31_23_" class="even" 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_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_59_31_24_" class="even" 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_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_59_31_25_" class="even" 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_c_l_median3x3.xhtml" target="_self">CLMedian3x3</a></td><td class="desc">Basic function to execute median filter </td></tr>
-<tr id="row_59_31_26_" class="even" 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_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_59_31_27_" class="even" 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_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_59_31_28_" class="even" 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_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_59_31_29_" class="even" 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_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_59_31_30_" class="even" 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_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_59_31_31_" class="even" 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_c_l_remap.xhtml" target="_self">CLRemap</a></td><td class="desc">Basic function to execute remap </td></tr>
-<tr id="row_59_31_32_" class="even" 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_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_59_31_33_" class="even" 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_c_l_scharr3x3.xhtml" target="_self">CLScharr3x3</a></td><td class="desc">Basic function to execute scharr 3x3 filter </td></tr>
-<tr id="row_59_31_34_" class="even" 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_c_l_sobel3x3.xhtml" target="_self">CLSobel3x3</a></td><td class="desc">Basic function to execute sobel 3x3 filter </td></tr>
-<tr id="row_59_31_35_" class="even" 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_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_59_31_36_" class="even" 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_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_59_31_37_" class="even" 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_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_59_31_38_" class="even" 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_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_59_31_39_" class="even" 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_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_59_32_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_59_32_" class="arrow" onclick="toggleFolder('59_32_')">►</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_59_32_0_" class="even" 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_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_59_32_1_" class="even" 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_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_59_32_2_" class="even" 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_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_59_32_3_" class="even" 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_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_59_32_4_" class="even" 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_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_59_32_5_" class="even" 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_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_59_32_6_" class="even" 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_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_59_32_7_" class="even" 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_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_59_32_8_" class="even" 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_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_59_32_9_" class="even" 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_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_59_32_10_" class="even" 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_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_59_32_11_" class="even" 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_box3x3.xhtml" target="_self">NEBox3x3</a></td><td class="desc">Basic function to execute box filter 3x3 </td></tr>
-<tr id="row_59_32_12_" class="even" 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_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_59_32_13_" class="even" 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_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_59_32_14_" class="even" 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_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_59_32_15_" class="even" 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_convolution3x3.xhtml" target="_self">NEConvolution3x3</a></td><td class="desc">Basic function to execute convolution of size 3x3 </td></tr>
-<tr id="row_59_32_16_" class="even" 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_convolution_rectangle.xhtml" target="_self">NEConvolutionRectangle</a></td><td class="desc">Basic function to execute non-square convolution </td></tr>
-<tr id="row_59_32_17_" class="even" 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_depth_convert.xhtml" target="_self">NEDepthConvert</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_depth_convert_kernel.xhtml">NEDepthConvertKernel</a> </td></tr>
-<tr id="row_59_32_18_" class="even" 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_dilate.xhtml" target="_self">NEDilate</a></td><td class="desc">Basic function to execute dilate </td></tr>
-<tr id="row_59_32_19_" class="even" 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_erode.xhtml" target="_self">NEErode</a></td><td class="desc">Basic function to execute erode </td></tr>
-<tr id="row_59_32_20_" class="even" 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_gaussian3x3.xhtml" target="_self">NEGaussian3x3</a></td><td class="desc">Basic function to execute gaussian filter 3x3 </td></tr>
-<tr id="row_59_32_21_" class="even" 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_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_59_32_22_" class="even" 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_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_59_32_23_" class="even" 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_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_59_32_24_" class="even" 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_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_59_32_25_" class="even" 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_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_59_32_26_" class="even" 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_median3x3.xhtml" target="_self">NEMedian3x3</a></td><td class="desc">Basic function to execute median filter </td></tr>
-<tr id="row_59_32_27_" class="even" 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_non_linear_filter.xhtml" target="_self">NENonLinearFilter</a></td><td class="desc">Basic function to execute non linear filter </td></tr>
-<tr id="row_59_32_28_" class="even" 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_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_59_32_29_" class="even" 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_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_59_32_30_" class="even" 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_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_59_32_31_" class="even" 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_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_59_32_32_" class="even" 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_remap.xhtml" target="_self">NERemap</a></td><td class="desc">Basic function to execute remap </td></tr>
-<tr id="row_59_32_33_" class="even" 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_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_59_32_34_" class="even" 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_scharr3x3.xhtml" target="_self">NEScharr3x3</a></td><td class="desc">Basic function to execute scharr 3x3 filter </td></tr>
-<tr id="row_59_32_35_" class="even" 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_sobel3x3.xhtml" target="_self">NESobel3x3</a></td><td class="desc">Basic function to execute sobel 3x3 filter </td></tr>
-<tr id="row_59_32_36_" class="even" 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_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_59_32_37_" class="even" 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_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_59_32_38_" class="even" 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_transpose.xhtml" target="_self">NETranspose</a></td><td class="desc">Basic function to transpose a matrix on NEON </td></tr>
-<tr id="row_59_32_39_" class="even" 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_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_59_32_40_" class="even" 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_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_59_33_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_34_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_35_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_36_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_37_" class="even" style="display:none;"><td class="entry"><span style="width: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< matrix_size ></a></td><td class="desc">Basic function to execute convolution of size 5x5, 7x7, 9x9 </td></tr>
-<tr id="row_59_38_" class="even" style="display:none;"><td class="entry"><span style="width: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.xhtml" target="_self">NEDepthConcatenate</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
-<tr id="row_59_39_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_40_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_41_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_42_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_43_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_44_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_45_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_46_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_47_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_59_47_" class="arrow" onclick="toggleFolder('59_47_')">►</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_59_47_0_" class="even" 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_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_59_47_1_" class="even" 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_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_59_48_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_49_" class="even" style="display:none;"><td class="entry"><span style="width: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.xhtml" target="_self">NEGEMMLowp</a></td><td class="desc">Basic function to execute GEMMLowp on NEON </td></tr>
-<tr id="row_59_50_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_51_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_52_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_53_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_54_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_55_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_56_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_57_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_58_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_59_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_60_" class="even" style="display:none;"><td class="entry"><span style="width: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 simulate a normalization layer </td></tr>
-<tr id="row_59_61_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_62_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_63_" class="even" style="display:none;"><td class="entry"><span style="width: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_59_64_" class="even" style="display:none;"><td class="entry"><span style="width: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_60_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_60_" class="arrow" onclick="toggleFolder('60_')">►</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_60_0_" style="display:none;"><td class="entry"><span 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_60_1_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_60_1_" class="arrow" onclick="toggleFolder('60_1_')">►</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_60_1_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_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_61_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_61_" class="arrow" onclick="toggleFolder('61_')">►</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_61_0_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_61_0_" class="arrow" onclick="toggleFolder('61_0_')">►</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_61_0_0_" class="even" 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_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_61_0_1_" class="even" 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_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_61_0_2_" class="even" 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_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_61_0_3_" class="even" 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_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_61_0_4_" class="even" 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_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_61_0_5_" class="even" 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_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_61_0_6_" class="even" 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_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_61_0_7_" class="even" 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_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_61_0_8_" class="even" 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_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_61_0_9_" class="even" 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_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_61_0_10_" class="even" 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_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_61_0_11_" class="even" 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_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_61_0_12_" class="even" 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_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_61_0_13_" class="even" 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_c_l_depth_concatenate_kernel.xhtml" target="_self">CLDepthConcatenateKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
-<tr id="row_61_0_14_" class="even" 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_c_l_derivative_kernel.xhtml" target="_self">CLDerivativeKernel</a></td><td class="desc">Interface for the derivative kernel </td></tr>
-<tr id="row_61_0_15_" class="even" 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_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_61_0_16_" class="even" 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_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_61_0_17_" class="even" 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_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_61_0_18_" class="even" 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_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_61_0_19_" class="even" 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_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_61_0_20_" class="even" 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_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml" target="_self">CLGEMMLowpMatrixMultiplyKernel</a></td><td class="desc">OpenCL kernel to compute low precision matrix multiplication kernel </td></tr>
-<tr id="row_61_0_21_" class="even" 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_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_61_0_22_" class="even" 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_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_61_0_23_" class="even" 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_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" or to multiply a vector "A" by a matrix "B" </td></tr>
-<tr id="row_61_0_24_" class="even" 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_c_l_gradient_kernel.xhtml" target="_self">CLGradientKernel</a></td><td class="desc">OpenCL kernel to perform Gradient computation </td></tr>
-<tr id="row_61_0_25_" class="even" 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_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_61_0_26_" class="even" 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_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_61_0_27_" class="even" 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_c_l_histogram_kernel.xhtml" target="_self">CLHistogramKernel</a></td><td class="desc">Interface to run the histogram kernel </td></tr>
-<tr id="row_61_0_28_" class="even" 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_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_61_0_29_" class="even" 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_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_61_0_30_" class="even" 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_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_61_0_31_" class="even" 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_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_61_0_32_" class="even" 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_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_61_0_33_" class="even" 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_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_61_0_34_" class="even" 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_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_61_0_35_" class="even" 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_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_61_0_36_" class="even" 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_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_61_0_37_" class="even" 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_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_61_0_38_" class="even" 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_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_61_0_39_" class="even" 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_c_l_logits1_d_shift_exp_sum_kernel.xhtml" target="_self">CLLogits1DShiftExpSumKernel</a></td><td class="desc">Interface for shifting the logits values around the max value and exponentiating the result </td></tr>
-<tr id="row_61_0_40_" class="even" 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_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_61_0_41_" class="even" 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_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_61_0_42_" class="even" 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_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_61_0_43_" class="even" 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_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_61_0_44_" class="even" 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_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_61_0_45_" class="even" 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_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_61_0_46_" class="even" 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_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_61_0_47_" class="even" 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_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_61_0_48_" class="even" 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_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_61_0_49_" class="even" 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_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_61_0_50_" class="even" 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_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_61_0_51_" class="even" 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_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_61_0_52_" class="even" 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_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_61_0_53_" class="even" 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_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_61_0_54_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_61_0_54_" class="arrow" onclick="toggleFolder('61_0_54_')">►</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"></td></tr>
-<tr id="row_61_0_54_0_" class="even" 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_1_c_l_convolution_layer_weights_reshape_kernel.xhtml" target="_self">CLConvolutionLayerWeightsReshapeKernel</a></td><td class="desc">Interface for the weights reshape kernel used by convolution and fully connected layers </td></tr>
-<tr id="row_61_0_54_1_" class="even" 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_1_c_l_locally_connected_layer_weights_reshape_kernel.xhtml" target="_self">CLLocallyConnectedLayerWeightsReshapeKernel</a></td><td class="desc">Interface for the weights reshape kernel used by locally connected layers </td></tr>
-<tr id="row_61_0_55_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_61_0_55_" class="arrow" onclick="toggleFolder('61_0_55_')">►</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_61_0_55_0_" class="even" 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_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_61_0_55_1_" class="even" 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_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_61_0_55_2_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_61_0_55_2_" class="arrow" onclick="toggleFolder('61_0_55_2_')">►</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_61_0_55_2_0_" class="even" 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_1_c_l_accumulate_kernel.xhtml" target="_self">CLAccumulateKernel</a></td><td class="desc">Interface for the accumulate kernel </td></tr>
-<tr id="row_61_0_55_2_1_" class="even" 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_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_61_0_55_2_2_" class="even" 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_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_61_0_55_2_3_" class="even" 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_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_61_0_55_2_4_" class="even" 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_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_61_0_55_2_5_" class="even" 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_1_c_l_convolution_kernel.xhtml" target="_self">CLConvolutionKernel< matrix_size ></a></td><td class="desc">Interface for the kernel to run an arbitrary size convolution on a tensor </td></tr>
-<tr id="row_61_0_55_2_6_" class="even" 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_1_c_l_depth_convert_kernel.xhtml" target="_self">CLDepthConvertKernel</a></td><td class="desc">Interface for the depth conversion kernel </td></tr>
-<tr id="row_61_0_55_2_7_" class="even" 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_1_c_l_dilate_kernel.xhtml" target="_self">CLDilateKernel</a></td><td class="desc">Interface for the dilate kernel </td></tr>
-<tr id="row_61_0_55_2_8_" class="even" 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_1_c_l_erode_kernel.xhtml" target="_self">CLErodeKernel</a></td><td class="desc">Interface for the erode kernel </td></tr>
-<tr id="row_61_0_55_2_9_" class="even" 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_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_61_0_55_2_10_" class="even" 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_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 1x4 if the input data type is F32 or in chunks of 1x8 if the input data type is F16 </td></tr>
-<tr id="row_61_0_55_2_11_" class="even" 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_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_61_0_55_2_12_" class="even" 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_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_61_0_55_2_13_" class="even" 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_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_61_0_55_2_14_" class="even" 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_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_61_0_55_2_15_" class="even" 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_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_61_0_55_2_16_" class="even" 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_1_c_l_scale_kernel.xhtml" target="_self">CLScaleKernel</a></td><td class="desc">Interface for the warp affine kernel </td></tr>
-<tr id="row_61_0_55_2_17_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span id="arr_61_0_55_2_17_" class="arrow" onclick="toggleFolder('61_0_55_2_17_')">►</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< matrix_size ></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_61_0_55_2_17_0_" class="even" style="display:none;"><td class="entry"><span style="width:96px;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_61_0_55_2_18_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span id="arr_61_0_55_2_18_" class="arrow" onclick="toggleFolder('61_0_55_2_18_')">►</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< matrix_size ></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_61_0_55_2_18_0_" class="even" style="display:none;"><td class="entry"><span style="width:96px;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_61_0_55_2_19_" class="even" 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_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_61_0_55_2_20_" class="even" 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_1_c_l_threshold_kernel.xhtml" target="_self">CLThresholdKernel</a></td><td class="desc">Interface for the thresholding kernel </td></tr>
-<tr id="row_61_0_55_2_21_" class="even" 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_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_61_0_55_2_22_" class="even" 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_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_61_0_55_2_23_" class="even" 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_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_61_0_55_2_24_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span id="arr_61_0_55_2_24_" class="arrow" onclick="toggleFolder('61_0_55_2_24_')">►</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_61_0_55_2_24_0_" class="even" style="display:none;"><td class="entry"><span style="width:96px;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_61_1_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_61_1_" class="arrow" onclick="toggleFolder('61_1_')">►</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_61_1_0_" class="even" 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_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_61_1_1_" class="even" 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_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_61_1_2_" class="even" 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_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_61_1_3_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_61_1_3_" class="arrow" onclick="toggleFolder('61_1_3_')">►</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 NEON kernels having 1 tensor input and 1 tensor output </td></tr>
-<tr id="row_61_1_3_0_" class="even" 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_1_n_e_accumulate_kernel.xhtml" target="_self">NEAccumulateKernel</a></td><td class="desc">Interface for the accumulate kernel </td></tr>
-<tr id="row_61_1_3_1_" class="even" 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_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_61_1_3_2_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_61_1_3_2_" class="arrow" onclick="toggleFolder('61_1_3_2_')">►</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_61_1_3_2_0_" class="even" 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_1_n_e_accumulate_weighted_f_p16_kernel.xhtml" target="_self">NEAccumulateWeightedFP16Kernel</a></td><td class="desc">Interface for the accumulate weighted kernel using F16 </td></tr>
-<tr id="row_61_1_3_3_" class="even" 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_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_61_1_3_4_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span id="arr_61_1_3_4_" class="arrow" onclick="toggleFolder('61_1_3_4_')">►</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_61_1_3_4_0_" class="even" 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_1_n_e_box3x3_f_p16_kernel.xhtml" target="_self">NEBox3x3FP16Kernel</a></td><td class="desc">NEON kernel to perform a Box 3x3 filter using F16 simd </td></tr>
-<tr id="row_61_1_3_5_" class="even" 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_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_61_1_3_6_" class="even" 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_1_n_e_convolution_kernel.xhtml" target="_self">NEConvolutionKernel< matrix_size ></a></td><td class="desc">Interface for the kernel to run an arbitrary size convolution on a tensor </td></tr>
-<tr id="row_61_1_3_7_" class="even" 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_1_n_e_depth_convert_kernel.xhtml" target="_self">NEDepthConvertKernel</a></td><td class="desc">Depth conversion kernel </td></tr>
-<tr id="row_61_1_3_8_" class="even" 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_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_61_1_3_9_" class="even" 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_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_61_1_3_10_" class="even" 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_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_61_1_3_11_" class="even" 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_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_61_1_3_12_" class="even" 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_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_61_1_3_13_" class="even" 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_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_61_1_3_14_" class="even" 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_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_61_1_3_15_" class="even" 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_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_61_1_3_16_" class="even" 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_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_61_1_3_17_" class="even" 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_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_61_1_3_18_" class="even" 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_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_61_1_3_19_" class="even" 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_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_61_1_3_20_" class="even" 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_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_61_1_3_21_" class="even" 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_1_n_e_separable_convolution_hor_kernel.xhtml" target="_self">NESeparableConvolutionHorKernel< matrix_size ></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_61_1_3_22_" class="even" 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_1_n_e_separable_convolution_vert_kernel.xhtml" target="_self">NESeparableConvolutionVertKernel< matrix_size ></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_61_1_3_23_" class="even" 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_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_61_1_4_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_61_1_4_" class="arrow" onclick="toggleFolder('61_1_4_')">►</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_61_1_4_0_" class="even" 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_1_n_e_harris_score_f_p16_kernel.xhtml" target="_self">NEHarrisScoreFP16Kernel< block_size ></a></td><td class="desc">Interface for the accumulate Weighted kernel using F16 </td></tr>
-<tr id="row_61_1_4_1_" class="even" 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_1_n_e_harris_score_kernel.xhtml" target="_self">NEHarrisScoreKernel< block_size ></a></td><td class="desc">Template NEON kernel to perform Harris Score </td></tr>
-<tr id="row_61_1_5_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_61_1_5_" class="arrow" onclick="toggleFolder('61_1_5_')">►</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_61_1_5_0_" class="even" 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_1_n_e_warp_affine_kernel.xhtml" target="_self">NEWarpAffineKernel< interpolation ></a></td><td class="desc">Template interface for the kernel to compute warp affine </td></tr>
-<tr id="row_61_1_5_1_" class="even" 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_1_n_e_warp_perspective_kernel.xhtml" target="_self">NEWarpPerspectiveKernel< interpolation ></a></td><td class="desc">Template interface for the kernel to compute warp perspective </td></tr>
-<tr id="row_61_1_6_" class="even" 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_absolute_difference_kernel.xhtml" target="_self">NEAbsoluteDifferenceKernel</a></td><td class="desc">Interface for the absolute difference kernel </td></tr>
-<tr id="row_61_1_7_" class="even" 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_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_61_1_8_" class="even" 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_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_61_1_9_" class="even" 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_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_61_1_10_" class="even" 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_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_61_1_11_" class="even" 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_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_61_1_12_" class="even" 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_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_61_1_13_" class="even" 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_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_61_1_14_" class="even" 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_channel_combine_kernel.xhtml" target="_self">NEChannelCombineKernel</a></td><td class="desc">Interface for the channel combine kernel </td></tr>
-<tr id="row_61_1_15_" class="even" 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_col2_im_kernel.xhtml" target="_self">NECol2ImKernel</a></td><td class="desc">NEON kernel to perform col2im reshaping </td></tr>
-<tr id="row_61_1_16_" class="even" 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_color_convert_kernel.xhtml" target="_self">NEColorConvertKernel</a></td><td class="desc">Interface for the color convert kernel </td></tr>
-<tr id="row_61_1_17_" class="even" 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_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_61_1_18_" class="even" 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_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_61_1_19_" class="even" 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_depth_concatenate_kernel.xhtml" target="_self">NEDepthConcatenateKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
-<tr id="row_61_1_20_" class="even" 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_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_61_1_21_" class="even" 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_direct_convolution_layer_bias_accumulate_kernel.xhtml" target="_self">NEDirectConvolutionLayerBiasAccumulateKernel</a></td><td class="desc">NEON kernel to accumulate the biases to each element of the input tensor </td></tr>
-<tr id="row_61_1_22_" class="even" 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_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_61_1_23_" class="even" 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_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_61_1_24_" class="even" 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_edge_trace_kernel.xhtml" target="_self">NEEdgeTraceKernel</a></td><td class="desc">NEON kernel to perform Edge tracing </td></tr>
-<tr id="row_61_1_25_" class="even" 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_fast_corners_kernel.xhtml" target="_self">NEFastCornersKernel</a></td><td class="desc">NEON kernel to perform fast corners </td></tr>
-<tr id="row_61_1_26_" class="even" 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_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_61_1_27_" class="even" 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_fill_border_kernel.xhtml" target="_self">NEFillBorderKernel</a></td><td class="desc">Interface for the kernel to fill borders </td></tr>
-<tr id="row_61_1_28_" class="even" 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_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_61_1_29_" class="even" 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_lowp_matrix_multiply_kernel.xhtml" target="_self">NEGEMMLowpMatrixMultiplyKernel</a></td><td class="desc">NEON kernel to multiply matrices </td></tr>
-<tr id="row_61_1_30_" class="even" 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_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_61_1_31_" class="even" 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_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_61_1_32_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_61_1_32_" class="arrow" onclick="toggleFolder('61_1_32_')">►</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_61_1_32_0_" class="even" 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_1_n_e_gradient_f_p16_kernel.xhtml" target="_self">NEGradientFP16Kernel</a></td><td class="desc">NEON kernel to perform Gradient computation </td></tr>
-<tr id="row_61_1_33_" class="even" 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_histogram_kernel.xhtml" target="_self">NEHistogramKernel</a></td><td class="desc">Interface for the histogram kernel </td></tr>
-<tr id="row_61_1_34_" class="even" 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_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_61_1_35_" class="even" 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_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_61_1_36_" class="even" 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_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_61_1_37_" class="even" 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_im2_col_kernel.xhtml" target="_self">NEIm2ColKernel</a></td><td class="desc">Interface for the im2col reshape kernel </td></tr>
-<tr id="row_61_1_38_" class="even" 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_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_61_1_39_" class="even" 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_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_61_1_40_" class="even" 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_logits1_d_norm_kernel.xhtml" target="_self">NELogits1DNormKernel</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_61_1_41_" class="even" 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_logits1_d_shift_exp_sum_kernel.xhtml" target="_self">NELogits1DShiftExpSumKernel</a></td><td class="desc">Interface for shifting the logits values around the max value and exponentiating the result </td></tr>
-<tr id="row_61_1_42_" class="even" 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_magnitude_phase_f_p16_kernel.xhtml" target="_self">NEMagnitudePhaseFP16Kernel< mag_type, phase_type ></a></td><td class="desc">Template interface for the kernel to compute magnitude and phase </td></tr>
-<tr id="row_61_1_43_" class="even" 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_magnitude_phase_kernel.xhtml" target="_self">NEMagnitudePhaseKernel< mag_type, phase_type ></a></td><td class="desc">Template interface for the kernel to compute magnitude and phase </td></tr>
-<tr id="row_61_1_44_" class="even" 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_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_61_1_45_" class="even" 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_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_61_1_46_" class="even" 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_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_61_1_47_" class="even" 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_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_61_1_48_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span id="arr_61_1_48_" class="arrow" onclick="toggleFolder('61_1_48_')">►</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_61_1_48_0_" class="even" 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_1_n_e_non_maxima_suppression3x3_f_p16_kernel.xhtml" target="_self">NENonMaximaSuppression3x3FP16Kernel</a></td><td class="desc">NEON kernel to perform Non-Maxima suppression 3x3 with intermediate results in F16 if the input data type is F32 </td></tr>
-<tr id="row_61_1_49_" class="even" 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_normalization_layer_kernel.xhtml" target="_self">NENormalizationLayerKernel</a></td><td class="desc">Interface for the normalization layer kernel </td></tr>
-<tr id="row_61_1_50_" class="even" 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_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_61_1_51_" class="even" 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_pooling_layer_kernel.xhtml" target="_self">NEPoolingLayerKernel</a></td><td class="desc">Interface for the pooling layer kernel </td></tr>
-<tr id="row_61_1_52_" class="even" 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_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_61_1_53_" class="even" 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_scale_kernel.xhtml" target="_self">NEScaleKernel</a></td><td class="desc">NEON kernel to perform scaling on a tensor </td></tr>
-<tr id="row_61_1_54_" class="even" 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_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_61_1_55_" class="even" 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_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_61_1_56_" class="even" 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_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_61_1_57_" class="even" 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_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_61_1_58_" class="even" 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_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_61_1_59_" class="even" 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_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_61_1_60_" class="even" 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_threshold_kernel.xhtml" target="_self">NEThresholdKernel</a></td><td class="desc">Interface for the thresholding kernel </td></tr>
-<tr id="row_61_1_61_" class="even" 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_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_61_1_62_" class="even" 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_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_62_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_62_" class="arrow" onclick="toggleFolder('62_')">►</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_62_0_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_62_0_" class="arrow" onclick="toggleFolder('62_0_')">►</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_62_0_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_c_l_lut.xhtml" target="_self">CLLut</a></td><td class="desc">Basic implementation of the OpenCL lut interface </td></tr>
-<tr id="row_62_1_" style="display:none;"><td class="entry"><span 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_63_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_63_" class="arrow" onclick="toggleFolder('63_')">►</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_63_0_" class="even" style="display:none;"><td class="entry"><span style="width: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_63_1_" class="even" style="display:none;"><td class="entry"><span 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_64_" 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_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>
-<tr id="row_65_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_image_dataset.xhtml" target="_self">ImageDataset< Size ></a></td><td class="desc">Abstract data set containing image names </td></tr>
-<tr id="row_66_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_66_" class="arrow" onclick="toggleFolder('66_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_image_dataset.xhtml" target="_self">ImageDataset< 2 ></a></td><td class="desc"></td></tr>
-<tr id="row_66_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_small_images.xhtml" target="_self">SmallImages</a></td><td class="desc">Data set containing names of small images </td></tr>
-<tr id="row_67_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_67_" class="arrow" onclick="toggleFolder('67_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_image_dataset.xhtml" target="_self">ImageDataset< 3 ></a></td><td class="desc"></td></tr>
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-<tr id="row_68_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_68_" class="arrow" onclick="toggleFolder('68_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_instrument_1_1_i_measurement.xhtml" target="_self">Instrument::IMeasurement</a></td><td class="desc">Interface defining a measurement, e.g </td></tr>
-<tr id="row_68_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_instrument_1_1_measurement.xhtml" target="_self">Instrument::Measurement< T ></a></td><td class="desc">Implementation of a <a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_instrument_1_1_measurement.xhtml" title="Implementation of a Measurement class for arihtmetic types. ">Measurement</a> class for arihtmetic types </td></tr>
-<tr id="row_69_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_69_" class="arrow" onclick="toggleFolder('69_')">►</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_69_0_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_69_0_" class="arrow" onclick="toggleFolder('69_0_')">►</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_69_0_0_" class="even" 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_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_69_1_" class="even" style="display:none;"><td class="entry"><span 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_70_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_70_" class="arrow" onclick="toggleFolder('70_')">►</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_70_0_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_70_0_" class="arrow" onclick="toggleFolder('70_0_')">►</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_70_0_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_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_70_1_" style="display:none;"><td class="entry"><span 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_71_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_71_" class="arrow" onclick="toggleFolder('71_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_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_71_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_cycle_counter.xhtml" target="_self">CycleCounter</a></td><td class="desc">Implementation of an instrument to count CPU cycles </td></tr>
-<tr id="row_71_1_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_instruction_counter.xhtml" target="_self">InstructionCounter</a></td><td class="desc">Implementation of an instrument to count executed CPU instructions </td></tr>
-<tr id="row_71_2_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1benchmark_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>
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-<tr id="row_73_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_interpolation_policies.xhtml" target="_self">InterpolationPolicies</a></td><td class="desc">Data set containing all possible interpolation policies </td></tr>
-<tr id="row_74_" 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="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_75_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_75_" class="arrow" onclick="toggleFolder('75_')">►</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_75_0_" class="even" style="display:none;"><td class="entry"><span style="width: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_75_1_" class="even" style="display:none;"><td class="entry"><span 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_76_" 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="structarm__compute_1_1traits_1_1is__contained.xhtml" target="_self">is_contained< T, Tuple ></a></td><td class="desc">Check if a type T is contained in a tuple Tuple of types </td></tr>
-<tr id="row_77_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_77_" class="arrow" onclick="toggleFolder('77_')">►</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< T, std::tuple< Ts... > ></a></td><td class="desc"></td></tr>
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-<tr id="row_78_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_78_" class="arrow" onclick="toggleFolder('78_')">►</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_78_0_" style="display:none;"><td class="entry"><span style="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_78_1_" style="display:none;"><td class="entry"><span 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_78_2_" style="display:none;"><td class="entry"><span 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_79_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_79_" class="arrow" onclick="toggleFolder('79_')">►</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_79_0_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_79_0_" class="arrow" onclick="toggleFolder('79_0_')">►</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_79_0_0_" class="even" 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_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_79_0_1_" class="even" 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_c_l_tensor.xhtml" target="_self">CLTensor</a></td><td class="desc">Basic implementation of the OpenCL tensor interface </td></tr>
-<tr id="row_79_1_" class="even" style="display:none;"><td class="entry"><span 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_79_2_" class="even" style="display:none;"><td class="entry"><span 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_80_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_80_" class="arrow" onclick="toggleFolder('80_')">►</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_80_0_" style="display:none;"><td class="entry"><span style="width: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_80_1_" style="display:none;"><td class="entry"><span 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_81_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_81_" class="arrow" onclick="toggleFolder('81_')">►</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_81_0_" class="even" style="display:none;"><td class="entry"><span 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_81_1_" class="even" style="display:none;"><td class="entry"><span 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_82_" 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="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_83_"><td class="entry"><span style="width:16px;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_84_" 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_keypoint.xhtml" target="_self">Keypoint</a></td><td class="desc"></td></tr>
-<tr id="row_85_"><td class="entry"><span style="width:16px;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_86_" 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="classarm__compute_1_1test_1_1model__objects_1_1_le_net5.xhtml" target="_self">LeNet5< TensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction ></a></td><td class="desc">Lenet5 model object </td></tr>
-<tr id="row_87_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1match__const.xhtml" target="_self">match_const< R, T ></a></td><td class="desc">Helper to create a constant type if the passed reference is constant </td></tr>
-<tr id="row_88_" 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="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_89_"><td class="entry"><span style="width:16px;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_90_" 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="classarm__compute_1_1test_1_1_normalization_layer_data_object.xhtml" target="_self">NormalizationLayerDataObject</a></td><td class="desc"></td></tr>
-<tr id="row_91_"><td class="entry"><span style="width:16px;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_92_" 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="classarm__compute_1_1test_1_1_normalization_types.xhtml" target="_self">NormalizationTypes</a></td><td class="desc">Data set containing all possible normalization types </td></tr>
-<tr id="row_93_"><td class="entry"><span style="width:16px;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_94_" 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="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_95_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_pooling_layer_data_object.xhtml" target="_self">PoolingLayerDataObject</a></td><td class="desc"></td></tr>
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-<tr id="row_97_"><td class="entry"><span style="width:16px;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_98_" 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="classarm__compute_1_1test_1_1benchmark_1_1_profiler.xhtml" target="_self">Profiler</a></td><td class="desc"></td></tr>
-<tr id="row_99_"><td class="entry"><span style="width:16px;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_100_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_100_" class="arrow" onclick="toggleFolder('100_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_program_options.xhtml" target="_self">ProgramOptions</a></td><td class="desc">Defines available commandline arguments and allows to parse them </td></tr>
-<tr id="row_100_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1performance_1_1_performance_program_options.xhtml" target="_self">PerformanceProgramOptions</a></td><td class="desc">Subclass of <a class="el" href="classarm__compute_1_1test_1_1_program_options.xhtml">ProgramOptions</a> that adds performance specific options </td></tr>
-<tr id="row_100_1_" style="display:none;"><td class="entry"><span style="width:32px;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_validation_program_options.xhtml" target="_self">ValidationProgramOptions</a></td><td class="desc">Subclass of <a class="el" href="classarm__compute_1_1test_1_1_program_options.xhtml">ProgramOptions</a> that adds validation specific options </td></tr>
-<tr id="row_101_"><td class="entry"><span style="width:16px;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< T ></a></td><td class="desc"></td></tr>
-<tr id="row_102_" 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="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote.xhtml" target="_self">promote< T ></a></td><td class="desc"></td></tr>
-<tr id="row_103_"><td class="entry"><span style="width:16px;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"></td></tr>
-<tr id="row_104_" 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="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"></td></tr>
-<tr id="row_105_"><td class="entry"><span style="width:16px;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"></td></tr>
-<tr id="row_106_" 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="structarm__compute_1_1test_1_1traits_1_1promote_3_01int32__t_01_4.xhtml" target="_self">promote< int32_t ></a></td><td class="desc"></td></tr>
-<tr id="row_107_"><td class="entry"><span style="width:16px;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"></td></tr>
-<tr id="row_108_" 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="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01int64__t_01_4.xhtml" target="_self">promote< int64_t ></a></td><td class="desc"></td></tr>
-<tr id="row_109_"><td class="entry"><span style="width:16px;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"></td></tr>
-<tr id="row_110_" 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="structarm__compute_1_1test_1_1traits_1_1promote_3_01int8__t_01_4.xhtml" target="_self">promote< int8_t ></a></td><td class="desc"></td></tr>
-<tr id="row_111_"><td class="entry"><span style="width:16px;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"></td></tr>
-<tr id="row_112_" 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="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint16__t_01_4.xhtml" target="_self">promote< uint16_t ></a></td><td class="desc"></td></tr>
-<tr id="row_113_"><td class="entry"><span style="width:16px;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"></td></tr>
-<tr id="row_114_" 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="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"></td></tr>
-<tr id="row_115_"><td class="entry"><span style="width:16px;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_01uint64__t_01_4.xhtml" target="_self">promote< uint64_t ></a></td><td class="desc"></td></tr>
-<tr id="row_116_" 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="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint8__t_01_4.xhtml" target="_self">promote< uint8_t ></a></td><td class="desc"></td></tr>
-<tr id="row_117_"><td class="entry"><span style="width:16px;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"></td></tr>
-<tr id="row_118_" 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="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_119_"><td class="entry"><span style="width:16px;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">Simple tensor object that stores elements in a consecutive chunk of memory </td></tr>
-<tr id="row_120_" 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="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_121_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_121_" class="arrow" onclick="toggleFolder('121_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_reference.xhtml" target="_self">Reference</a></td><td class="desc">Interface for reference implementations </td></tr>
-<tr id="row_121_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;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_reference_c_p_p.xhtml" target="_self">ReferenceCPP</a></td><td class="desc">C++ reference implementation </td></tr>
-<tr id="row_122_" 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="classarm__compute_1_1test_1_1_rounding_policies.xhtml" target="_self">RoundingPolicies</a></td><td class="desc">Data set containing all possible rounding policies </td></tr>
-<tr id="row_123_"><td class="entry"><span style="width:16px;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_124_" 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="classarm__compute_1_1test_1_1_shape_dataset.xhtml" target="_self">ShapeDataset< Size ></a></td><td class="desc">Abstract data set containing tensor shapes </td></tr>
-<tr id="row_125_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_125_" class="arrow" onclick="toggleFolder('125_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_shape_dataset.xhtml" target="_self">ShapeDataset< 1 ></a></td><td class="desc"></td></tr>
-<tr id="row_125_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_small1_d_shape.xhtml" target="_self">Small1DShape</a></td><td class="desc">Data set containing one 1D tensor shape </td></tr>
-<tr id="row_126_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_126_" class="arrow" onclick="toggleFolder('126_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_shape_dataset.xhtml" target="_self">ShapeDataset< 3 ></a></td><td class="desc"></td></tr>
-<tr id="row_126_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_direct_convolution_shapes.xhtml" target="_self">DirectConvolutionShapes</a></td><td class="desc">Data set containing direct convolution tensor shapes </td></tr>
-<tr id="row_126_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_large_shapes.xhtml" target="_self">LargeShapes</a></td><td class="desc">Data set containing large tensor shapes </td></tr>
-<tr id="row_126_2_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_small_shapes.xhtml" target="_self">SmallShapes</a></td><td class="desc">Data set containing small tensor shapes </td></tr>
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-<tr id="row_128_2_" style="display:none;"><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_1test_1_1validation_1_1tensor__visitors_1_1arithmetic__addition__visitor.xhtml" target="_self">arithmetic_addition_visitor</a></td><td class="desc"></td></tr>
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-<tr id="row_128_4_" style="display:none;"><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_1test_1_1validation_1_1tensor__visitors_1_1batch__normalization__layer__visitor.xhtml" target="_self">batch_normalization_layer_visitor</a></td><td class="desc"></td></tr>
-<tr id="row_128_5_" style="display:none;"><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_1test_1_1validation_1_1tensor__visitors_1_1convolution__layer__visitor.xhtml" target="_self">convolution_layer_visitor</a></td><td class="desc"></td></tr>
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-<tr id="row_128_7_" style="display:none;"><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_1test_1_1validation_1_1tensor__visitors_1_1fixed__point__operation__visitor.xhtml" target="_self">fixed_point_operation_visitor</a></td><td class="desc"></td></tr>
-<tr id="row_128_8_" style="display:none;"><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_1test_1_1validation_1_1tensor__visitors_1_1fixed__point__pixel__wise__multiplication__visitor.xhtml" target="_self">fixed_point_pixel_wise_multiplication_visitor</a></td><td class="desc"></td></tr>
-<tr id="row_128_9_" style="display:none;"><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_1test_1_1validation_1_1tensor__visitors_1_1fully__connected__layer__visitor.xhtml" target="_self">fully_connected_layer_visitor</a></td><td class="desc"></td></tr>
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-<tr id="row_128_11_" style="display:none;"><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_1test_1_1validation_1_1tensor__visitors_1_1normalization__layer__visitor.xhtml" target="_self">normalization_layer_visitor</a></td><td class="desc"></td></tr>
-<tr id="row_128_12_" style="display:none;"><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_1test_1_1validation_1_1tensor__visitors_1_1pixel__wise__multiplication__visitor.xhtml" target="_self">pixel_wise_multiplication_visitor</a></td><td class="desc"></td></tr>
-<tr id="row_128_13_" style="display:none;"><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_1test_1_1validation_1_1tensor__visitors_1_1pooling__layer__visitor.xhtml" target="_self">pooling_layer_visitor</a></td><td class="desc"></td></tr>
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-<tr id="row_129_"><td class="entry"><span style="width:16px;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_tensor.xhtml" target="_self">Tensor< T ></a></td><td class="desc"></td></tr>
-<tr id="row_130_" 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_tensor3_d.xhtml" target="_self">Tensor3D</a></td><td class="desc">Structure to hold 3D tensor information </td></tr>
-<tr id="row_131_"><td class="entry"><span style="width:16px;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_132_" 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="classarm__compute_1_1test_1_1validation_1_1_tensor_factory.xhtml" target="_self">TensorFactory</a></td><td class="desc"></td></tr>
-<tr id="row_133_"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml" target="_self">TensorLibrary</a></td><td class="desc">Factory class to create and fill tensors </td></tr>
-<tr id="row_134_" 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="classarm__compute_1_1test_1_1_threshold_data_object.xhtml" target="_self">ThresholdDataObject</a></td><td class="desc"></td></tr>
-<tr id="row_135_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_135_" class="arrow" onclick="toggleFolder('135_')">►</span><span class="icona"><span class="icon">C</span></span><b>true_</b></td><td class="desc"></td></tr>
-<tr id="row_135_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_activation_functions_01_4.xhtml" target="_self">is_dataset< arm_compute::test::ActivationFunctions ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_1_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_ale353bc52507aa43f06dbf95e757937ea3.xhtml" target="_self">is_dataset< arm_compute::test::AlexNetConvolutionLayerDataset ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_2_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_ale08494eac301fe59801c94a1e49323f42.xhtml" target="_self">is_dataset< arm_compute::test::AlexNetFullyConnectedLayerDataset ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_3_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_all_data_types_01_4.xhtml" target="_self">is_dataset< arm_compute::test::AllDataTypes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_4_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_border_modes_01_4.xhtml" target="_self">is_dataset< arm_compute::test::BorderModes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_5_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_c_n_n_data_types_01_4.xhtml" target="_self">is_dataset< arm_compute::test::CNNDataTypes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_6_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_c_n_n_fixed_point_data_types_01_4.xhtml" target="_self">is_dataset< arm_compute::test::CNNFixedPointDataTypes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_7_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_c_n_n_float_data_types_01_4.xhtml" target="_self">is_dataset< arm_compute::test::CNNFloatDataTypes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_8_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_convert_policies_01_4.xhtml" target="_self">is_dataset< arm_compute::test::ConvertPolicies ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_9_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_direct_convolution_shapes_01_4.xhtml" target="_self">is_dataset< arm_compute::test::DirectConvolutionShapes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_10_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_fixed_point_data_types_01_4.xhtml" target="_self">is_dataset< arm_compute::test::FixedPointDataTypes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_11_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_float_data_types_01_4.xhtml" target="_self">is_dataset< arm_compute::test::FloatDataTypes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_12_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_interpolation_policies_01_4.xhtml" target="_self">is_dataset< arm_compute::test::InterpolationPolicies ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_13_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_larb321d1e758b5a8ba2357d45c9fb79214.xhtml" target="_self">is_dataset< arm_compute::test::LargeFullyConnectedLayerDataset ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_14_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_large_g_e_m_m_dataset_01_4.xhtml" target="_self">is_dataset< arm_compute::test::LargeGEMMDataset ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_15_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_large_images_01_4.xhtml" target="_self">is_dataset< arm_compute::test::LargeImages ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_16_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_large_shapes_01_4.xhtml" target="_self">is_dataset< arm_compute::test::LargeShapes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_17_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_normalization_types_01_4.xhtml" target="_self">is_dataset< arm_compute::test::NormalizationTypes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_18_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_ran0c09af4ee7a64edb9be5e86462d7cfee.xhtml" target="_self">is_dataset< arm_compute::test::RandomBatchNormalizationLayerDataset ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_19_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_random_pooling_layer_dataset_01_4.xhtml" target="_self">is_dataset< arm_compute::test::RandomPoolingLayerDataset ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_20_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_rounding_policies_01_4.xhtml" target="_self">is_dataset< arm_compute::test::RoundingPolicies ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_21_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_signed_data_types_01_4.xhtml" target="_self">is_dataset< arm_compute::test::SignedDataTypes ></a></td><td class="desc"></td></tr>
-<tr id="row_135_22_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_small1_d_shape_01_4.xhtml" target="_self">is_dataset< arm_compute::test::Small1DShape ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_23_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_sma37aa36c611469959a5228d982ba942dd.xhtml" target="_self">is_dataset< arm_compute::test::SmallConvolutionLayerDataset ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_24_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_sma7e005b651d0eb6b1236ae8f2d63b33e2.xhtml" target="_self">is_dataset< arm_compute::test::SmallFullyConnectedLayerDataset ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_25_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_small_g_e_m_m_dataset_01_4.xhtml" target="_self">is_dataset< arm_compute::test::SmallGEMMDataset ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_26_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_small_images_01_4.xhtml" target="_self">is_dataset< arm_compute::test::SmallImages ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_27_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_small_shapes_01_4.xhtml" target="_self">is_dataset< arm_compute::test::SmallShapes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_28_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_threshold_dataset_01_4.xhtml" target="_self">is_dataset< arm_compute::test::ThresholdDataset ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_135_29_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structboost_1_1unit__test_1_1data_1_1monomorphic_1_1is__dataset_3_01arm__compute_1_1test_1_1_unsigned_data_types_01_4.xhtml" target="_self">is_dataset< arm_compute::test::UnsignedDataTypes ></a></td><td class="desc">Register the data set with Boost </td></tr>
-<tr id="row_136_" class="even"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_136_" class="arrow" onclick="toggleFolder('136_')">►</span><span class="icona"><span class="icon">C</span></span><b>true_type</b></td><td class="desc"></td></tr>
-<tr id="row_136_0_" style="display:none;"><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_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>
-<tr id="row_137_"><td class="entry"><span style="width:0px;display:inline-block;"> </span><span id="arr_137_" class="arrow" onclick="toggleFolder('137_')">►</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1_user_configuration.xhtml" target="_self">UserConfiguration</a></td><td class="desc">Container providing easy access to runtime options provided by the user </td></tr>
-<tr id="row_137_0_" class="even" style="display:none;"><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_1test_1_1performance_1_1_performance_user_configuration.xhtml" target="_self">PerformanceUserConfiguration</a></td><td class="desc">Specialisation of <a class="el" href="structarm__compute_1_1test_1_1_user_configuration.xhtml">UserConfiguration</a> to provide performance specific configuration options </td></tr>
-<tr id="row_138_" 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="structarm__compute_1_1_valid_region.xhtml" target="_self">ValidRegion</a></td><td class="desc"></td></tr>
-<tr id="row_139_"><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_vector.xhtml" target="_self">Vector</a></td><td class="desc">Structure to hold <a class="el" href="struct_vector.xhtml" title="Structure to hold Vector information. ">Vector</a> information </td></tr>
-<tr id="row_140_" 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="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_141_"><td class="entry"><span style="width:16px;display:inline-block;"> </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_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1support_1_1cpp14_1_1___unique__if.xhtml" target="_self">_Unique_if< T ></a></td><td class="desc">Make_unqiue is missing in CPP11 </td></tr>
+<tr id="row_1_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1support_1_1cpp14_1_1___unique__if_3_01_t[]_4.xhtml" target="_self">_Unique_if< T[]></a></td><td class="desc"></td></tr>
+<tr id="row_2_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1support_1_1cpp14_1_1___unique__if_3_01_t[_n]_4.xhtml" target="_self">_Unique_if< T[N]></a></td><td class="desc"></td></tr>
+<tr id="row_3_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_absolute_tolerance.xhtml" target="_self">AbsoluteTolerance< T ></a></td><td class="desc">Class reprensenting an absolute tolerance value </td></tr>
+<tr id="row_4_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_absolute_tolerance.xhtml" target="_self">AbsoluteTolerance< U ></a></td><td class="desc"></td></tr>
+<tr id="row_5_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_6_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_alex_net_network.xhtml" target="_self">AlexNetNetwork< ITensorType, TensorType, SubTensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, FullyConnectedLayerFunction, NormalizationLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction ></a></td><td class="desc">AlexNet model object </td></tr>
+<tr id="row_7_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_alex_net_network.xhtml" target="_self">AlexNetNetwork< ITensorType, TensorType, SubTensorType, arm_compute::test::Accessor, ActivationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, FullyConnectedLayerFunction, NormalizationLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction ></a></td><td class="desc"></td></tr>
+<tr id="row_8_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_9_"><td class="entry"><img id="arr_9_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('9_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_batch_normalization_layer_dataset.xhtml" target="_self">BatchNormalizationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_9_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_batch_normalization_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV4BatchNormalizationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_9_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_random_batch_normalization_layer_dataset.xhtml" target="_self">RandomBatchNormalizationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_9_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_batch_normalization_layer_dataset.xhtml" target="_self">YOLOV2BatchNormalizationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_10_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_11_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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>
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+<tr id="row_13_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_14_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_15_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_16_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_symbols.xhtml" target="_self">CLSymbols</a></td><td class="desc"></td></tr>
+<tr id="row_17_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_18_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1common__promoted__signed__type.xhtml" target="_self">common_promoted_signed_type< T ></a></td><td class="desc">Find the signed promoted common type </td></tr>
+<tr id="row_19_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare.xhtml" target="_self">compare< T ></a></td><td class="desc"></td></tr>
+<tr id="row_20_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare__base.xhtml" target="_self">compare_base< T ></a></td><td class="desc"></td></tr>
+<tr id="row_21_"><td class="entry"><img id="arr_21_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('21_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare__base.xhtml" target="_self">compare_base< AbsoluteTolerance< U > ></a></td><td class="desc"></td></tr>
+<tr id="row_21_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_22_" class="even"><td class="entry"><img id="arr_22_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('22_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare__base.xhtml" target="_self">compare_base< RelativeTolerance< U > ></a></td><td class="desc"></td></tr>
+<tr id="row_22_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_23_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1detail_1_1compare__dimension.xhtml" target="_self">compare_dimension< T ></a></td><td class="desc">Functor to compare two <a class="el" href="classarm__compute_1_1_dimensions.xhtml">Dimensions</a> objects and throw an error on mismatch </td></tr>
+<tr id="row_24_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_1_1constant__expr.xhtml" target="_self">constant_expr< T ></a></td><td class="desc"></td></tr>
+<tr id="row_25_"><td class="entry"><img id="arr_25_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('25_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset.xhtml" target="_self">ConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_convolution_layer_dataset.xhtml" target="_self">AlexNetConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_direct_convolution_layer_dataset.xhtml" target="_self">AlexNetDirectConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_direct_convolution_layer_dataset.xhtml" target="_self">DirectConvolutionLayerDataset</a></td><td class="desc">Stripped down version of AlexNet as not all kernel sizes and strides are supported </td></tr>
+<tr id="row_25_3_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_convolution_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV1ConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_4_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_direct_convolution_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV1DirectConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_5_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_convolution_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV4ConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_6_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_direct_convolution_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV4DirectConvolutionLayerDataset</a></td><td class="desc">A subset of GoogLeNetInceptionV4 convolution layers with filter dimensions supported by DirectConvolution kernel </td></tr>
+<tr id="row_25_7_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_large_convolution_layer_dataset.xhtml" target="_self">LargeConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_8_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_convolution_layer_dataset.xhtml" target="_self">LeNet5ConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_9_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_convolution_layer_dataset.xhtml" target="_self">SmallConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_10_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml" target="_self">SqueezeNetConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_11_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml" target="_self">VGG16ConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_12_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_direct_convolution_layer_dataset.xhtml" target="_self">VGG16DirectConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_25_13_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_convolution_layer_dataset.xhtml" target="_self">YOLOV2ConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_26_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="struct_coordinates2_d.xhtml" target="_self">Coordinates2D</a></td><td class="desc">2D Coordinates structure </td></tr>
+<tr id="row_27_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_28_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_29_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1_counter_mapping.xhtml" target="_self">CounterMapping</a></td><td class="desc"></td></tr>
+<tr id="row_30_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1_c_p_u_info.xhtml" target="_self">CPUInfo</a></td><td class="desc"></td></tr>
+<tr id="row_31_"><td class="entry"><img id="arr_31_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_dataset.xhtml" target="_self">Dataset</a></td><td class="desc">Abstract dataset base class </td></tr>
+<tr id="row_31_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_cartesian_product_dataset.xhtml" target="_self">CartesianProductDataset< T, U ></a></td><td class="desc">Implementation of a dataset representing all combinations of values of the input datasets </td></tr>
+<tr id="row_31_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_join_dataset.xhtml" target="_self">JoinDataset< T, U ></a></td><td class="desc">Implementation of a dataset representing the concatenation of the input datasets </td></tr>
+<tr id="row_31_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_named_dataset.xhtml" target="_self">NamedDataset</a></td><td class="desc">Abstract implementation of a named dataset </td></tr>
+<tr id="row_31_2_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_0_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_0_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml" target="_self">ContainerDataset< T ></a></td><td class="desc">Implementation of a dataset created from a container </td></tr>
+<tr id="row_31_2_0_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_depth_concatenate_shapes.xhtml" target="_self">DepthConcatenateShapes</a></td><td class="desc">Data set containing 2D tensor shapes for DepthConcatenate </td></tr>
+<tr id="row_31_2_0_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_global_pooling_shapes.xhtml" target="_self">GlobalPoolingShapes</a></td><td class="desc">Data set containing global pooling tensor shapes </td></tr>
+<tr id="row_31_2_0_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_large2_d_shapes.xhtml" target="_self">Large2DShapes</a></td><td class="desc">Data set containing large 2D tensor shapes </td></tr>
+<tr id="row_31_2_0_3_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_large3_d_shapes.xhtml" target="_self">Large3DShapes</a></td><td class="desc">Data set containing large 3D tensor shapes </td></tr>
+<tr id="row_31_2_0_4_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_large4_d_shapes.xhtml" target="_self">Large4DShapes</a></td><td class="desc">Data set containing large 4D tensor shapes </td></tr>
+<tr id="row_31_2_0_5_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_large_shapes.xhtml" target="_self">LargeShapes</a></td><td class="desc">Data set containing large tensor shapes </td></tr>
+<tr id="row_31_2_0_6_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_medium_shapes.xhtml" target="_self">MediumShapes</a></td><td class="desc">Data set containing medium tensor shapes </td></tr>
+<tr id="row_31_2_0_7_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small2_d_shapes.xhtml" target="_self">Small2DShapes</a></td><td class="desc">Data set containing small 2D tensor shapes </td></tr>
+<tr id="row_31_2_0_8_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small3_d_shapes.xhtml" target="_self">Small3DShapes</a></td><td class="desc">Data set containing small 3D tensor shapes </td></tr>
+<tr id="row_31_2_0_9_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small4_d_shapes.xhtml" target="_self">Small4DShapes</a></td><td class="desc">Data set containing small 4D tensor shapes </td></tr>
+<tr id="row_31_2_0_10_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_direct_convolution_shapes.xhtml" target="_self">SmallDirectConvolutionShapes</a></td><td class="desc">Data set containing small tensor shapes for direct convolution </td></tr>
+<tr id="row_31_2_0_11_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_shapes.xhtml" target="_self">SmallShapes</a></td><td class="desc">Data set containing small tensor shapes </td></tr>
+<tr id="row_31_2_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_initializer_list_dataset.xhtml" target="_self">InitializerListDataset< T ></a></td><td class="desc">Implementation of a dataset created from an initializer list </td></tr>
+<tr id="row_31_2_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_range_dataset.xhtml" target="_self">RangeDataset< T ></a></td><td class="desc">Implementation of a dataset created from a range of values </td></tr>
+<tr id="row_31_2_3_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset.xhtml" target="_self">SingletonDataset< T ></a></td><td class="desc">Implementation of a dataset holding a single value </td></tr>
+<tr id="row_31_2_4_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_4_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_4_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml" target="_self">ContainerDataset< std::vector< ActivationLayerInfo::ActivationFunction > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_4_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_activation_functions.xhtml" target="_self">ActivationFunctions</a></td><td class="desc"></td></tr>
+<tr id="row_31_2_5_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_5_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_5_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml" target="_self">ContainerDataset< std::vector< BorderMode > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_5_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_border_modes.xhtml" target="_self">BorderModes</a></td><td class="desc"></td></tr>
+<tr id="row_31_2_6_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_6_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_6_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml" target="_self">ContainerDataset< std::vector< ConvertPolicy > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_6_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_convert_policies.xhtml" target="_self">ConvertPolicies</a></td><td class="desc"></td></tr>
+<tr id="row_31_2_7_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_7_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_7_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml" target="_self">ContainerDataset< std::vector< InterpolationPolicy > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_7_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_interpolation_policies.xhtml" target="_self">InterpolationPolicies</a></td><td class="desc"></td></tr>
+<tr id="row_31_2_8_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_8_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_8_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml" target="_self">ContainerDataset< std::vector< MatrixPattern > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_8_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_matrix_patterns.xhtml" target="_self">MatrixPatterns</a></td><td class="desc"></td></tr>
+<tr id="row_31_2_9_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_9_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_9_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml" target="_self">ContainerDataset< std::vector< NonLinearFilterFunction > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_9_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_non_linear_filter_functions.xhtml" target="_self">NonLinearFilterFunctions</a></td><td class="desc"></td></tr>
+<tr id="row_31_2_10_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_10_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_10_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml" target="_self">ContainerDataset< std::vector< NormType > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_10_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_normalization_types.xhtml" target="_self">NormalizationTypes</a></td><td class="desc"></td></tr>
+<tr id="row_31_2_11_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_11_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_11_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml" target="_self">ContainerDataset< std::vector< PoolingType > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_11_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_pooling_types.xhtml" target="_self">PoolingTypes</a></td><td class="desc"></td></tr>
+<tr id="row_31_2_12_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_12_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_2_12_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset.xhtml" target="_self">ContainerDataset< std::vector< ReductionOperation > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_12_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_reduction_operations.xhtml" target="_self">ReductionOperations</a></td><td class="desc"></td></tr>
+<tr id="row_31_2_13_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_initializer_list_dataset.xhtml" target="_self">InitializerListDataset< TensorShape ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_14_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset.xhtml" target="_self">SingletonDataset< ActivationLayerInfo ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_15_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset.xhtml" target="_self">SingletonDataset< NormalizationLayerInfo ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_16_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_2_16_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('31_2_16_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset.xhtml" target="_self">SingletonDataset< TensorShape ></a></td><td class="desc"></td></tr>
+<tr id="row_31_2_16_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small1_d_shape.xhtml" target="_self">Small1DShape</a></td><td class="desc">Data set containing 1D tensor shapes </td></tr>
+<tr id="row_31_3_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_zip_dataset.xhtml" target="_self">ZipDataset< T, U ></a></td><td class="desc">Implementation of a dataset representing pairs of values of the input datasets </td></tr>
+<tr id="row_31_4_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_4_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_4_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_cartesian_product_dataset.xhtml" target="_self">CartesianProductDataset< framework::dataset::InitializerListDataset< TensorShape >, framework::dataset::SingletonDataset< ActivationLayerInfo > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_4_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_activation_layer_dataset.xhtml" target="_self">AlexNetActivationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_31_4_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_activation_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV1ActivationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_31_4_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_activation_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV4ActivationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_31_4_3_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_activation_layer_dataset.xhtml" target="_self">SqueezeNetActivationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_31_4_4_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_activation_layer_dataset.xhtml" target="_self">VGG16ActivationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_31_4_5_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_activation_layer_l_i_n_e_a_r_dataset.xhtml" target="_self">YOLOV2ActivationLayerLINEARDataset</a></td><td class="desc"></td></tr>
+<tr id="row_31_4_6_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_activation_layer_r_e_l_u_dataset.xhtml" target="_self">YOLOV2ActivationLayerRELUDataset</a></td><td class="desc"></td></tr>
+<tr id="row_31_5_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_5_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_5_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_cartesian_product_dataset.xhtml" target="_self">CartesianProductDataset< framework::dataset::InitializerListDataset< TensorShape >, framework::dataset::SingletonDataset< NormalizationLayerInfo > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_5_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_normalization_layer_dataset.xhtml" target="_self">AlexNetNormalizationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_31_5_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_normalization_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV1NormalizationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_31_6_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_6_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('31_6_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_cartesian_product_dataset.xhtml" target="_self">CartesianProductDataset< framework::dataset::SingletonDataset< TensorShape >, framework::dataset::SingletonDataset< ActivationLayerInfo > ></a></td><td class="desc"></td></tr>
+<tr id="row_31_6_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_activation_layer_dataset.xhtml" target="_self">LeNet5ActivationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_31_7_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_31_7_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('31_7_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_join_dataset.xhtml" target="_self">JoinDataset< YOLOV2ActivationLayerRELUDataset, YOLOV2ActivationLayerLINEARDataset ></a></td><td class="desc"></td></tr>
+<tr id="row_31_7_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_activation_layer_dataset.xhtml" target="_self">YOLOV2ActivationLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_32_" class="even"><td class="entry"><img id="arr_32_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('32_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_depthwise_convolution_dataset.xhtml" target="_self">DepthwiseConvolutionDataset</a></td><td class="desc"></td></tr>
+<tr id="row_32_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_large_depthwise_convolution_dataset.xhtml" target="_self">LargeDepthwiseConvolutionDataset</a></td><td class="desc"></td></tr>
+<tr id="row_32_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_large_depthwise_convolution_dataset3x3.xhtml" target="_self">LargeDepthwiseConvolutionDataset3x3</a></td><td class="desc"></td></tr>
+<tr id="row_32_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_mobile_net_depthwise_convolution_dataset.xhtml" target="_self">MobileNetDepthwiseConvolutionDataset</a></td><td class="desc"></td></tr>
+<tr id="row_32_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_depthwise_convolution_dataset.xhtml" target="_self">SmallDepthwiseConvolutionDataset</a></td><td class="desc"></td></tr>
+<tr id="row_32_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_depthwise_convolution_dataset3x3.xhtml" target="_self">SmallDepthwiseConvolutionDataset3x3</a></td><td class="desc"></td></tr>
+<tr id="row_33_"><td class="entry"><img id="arr_33_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('33_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_depthwise_separable_convolution_layer_dataset.xhtml" target="_self">DepthwiseSeparableConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_33_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_mobile_net_depthwise_separable_convolution_layer_dataset.xhtml" target="_self">MobileNetDepthwiseSeparableConvolutionLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_34_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="struct_detection_window.xhtml" target="_self">DetectionWindow</a></td><td class="desc">Detection window struct </td></tr>
+<tr id="row_35_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_36_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_window_1_1_dimension.xhtml" target="_self">Window::Dimension</a></td><td class="desc">Describe one of the image's dimensions with a start, end and step </td></tr>
+<tr id="row_37_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_dimensions.xhtml" target="_self">Dimensions< T ></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_38_" class="even"><td class="entry"><img id="arr_38_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('38_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_dimensions.xhtml" target="_self">Dimensions< int ></a></td><td class="desc"></td></tr>
+<tr id="row_38_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_39_"><td class="entry"><img id="arr_39_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('39_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_dimensions.xhtml" target="_self">Dimensions< size_t ></a></td><td class="desc"></td></tr>
+<tr id="row_39_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_39_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_40_" class="even"><td class="entry"><img id="arr_40_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('40_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_dimensions.xhtml" target="_self">Dimensions< unsigned int ></a></td><td class="desc"></td></tr>
+<tr id="row_40_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_41_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1enable__bitwise__ops.xhtml" target="_self">enable_bitwise_ops< T ></a></td><td class="desc"></td></tr>
+<tr id="row_42_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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 operation operations on GPUTarget enumerations </td></tr>
+<tr id="row_43_"><td class="entry"><img id="arr_43_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('43_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><b>false_type</b></td><td class="desc"></td></tr>
+<tr id="row_43_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1is__container.xhtml" target="_self">is_container< T ></a></td><td class="desc">Base case </td></tr>
+<tr id="row_43_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_44_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1fixed__point__arithmetic_1_1fixed__point.xhtml" target="_self">fixed_point< T ></a></td><td class="desc">Arbitrary fixed-point arithmetic class </td></tr>
+<tr id="row_45_"><td class="entry"><img id="arr_45_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_45_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_activation_layer_fixture.xhtml" target="_self">ActivationLayerFixture< TensorType, Function, Accessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_alex_net_fixture.xhtml" target="_self">AlexNetFixture< ITensorType, TensorType, SubTensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, FullyConnectedLayerFunction, NormalizationLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction ></a></td><td class="desc"></td></tr>
+<tr id="row_45_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_batch_normalization_layer_fixture.xhtml" target="_self">BatchNormalizationLayerFixture< TensorType, Function, Accessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_3_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml" target="_self">ConvolutionLayerFixture< TensorType, Function, Accessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_4_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_depthwise_convolution_fixture.xhtml" target="_self">DepthwiseConvolutionFixture< TensorType, Function, Accessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_5_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_depthwise_separable_convolution_layer_fixture.xhtml" target="_self">DepthwiseSeparableConvolutionLayerFixture< TensorType, Function, Accessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_6_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_floor_fixture.xhtml" target="_self">FloorFixture< TensorType, Function, Accessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_7_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_fully_connected_layer_fixture.xhtml" target="_self">FullyConnectedLayerFixture< TensorType, Function, Accessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_8_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_g_e_m_m_fixture.xhtml" target="_self">GEMMFixture< TensorType, Function, Accessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_9_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_le_net5_fixture.xhtml" target="_self">LeNet5Fixture< TensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction ></a></td><td class="desc"></td></tr>
+<tr id="row_45_10_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_normalization_layer_fixture.xhtml" target="_self">NormalizationLayerFixture< TensorType, Function, Accessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_11_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_pooling_layer_fixture.xhtml" target="_self">PoolingLayerFixture< TensorType, Function, Accessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_12_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_r_o_i_pooling_layer_fixture.xhtml" target="_self">ROIPoolingLayerFixture< TensorType, Function, Accessor, Array_T, ArrayAccessor ></a></td><td class="desc">Fixture that can be used for NEON and CL </td></tr>
+<tr id="row_45_13_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_13_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_13_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_activation_validation_fixed_point_fixture.xhtml" target="_self">ActivationValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_13_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_activation_validation_fixture.xhtml" target="_self">ActivationValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_14_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_14_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_14_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_arithmetic_addition_validation_fixed_point_fixture.xhtml" target="_self">ArithmeticAdditionValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_14_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_arithmetic_addition_validation_fixture.xhtml" target="_self">ArithmeticAdditionValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_15_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_15_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_15_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_arithmetic_subtraction_validation_fixed_point_fixture.xhtml" target="_self">ArithmeticSubtractionValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_15_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_arithmetic_subtraction_validation_fixture.xhtml" target="_self">ArithmeticSubtractionValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_16_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_16_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_16_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_batch_normalization_layer_validation_fixed_point_fixture.xhtml" target="_self">BatchNormalizationLayerValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_16_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_batch_normalization_layer_validation_fixture.xhtml" target="_self">BatchNormalizationLayerValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_17_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_bitwise_and_validation_fixture.xhtml" target="_self">BitwiseAndValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_18_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_bitwise_not_validation_fixture.xhtml" target="_self">BitwiseNotValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_19_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_bitwise_or_validation_fixture.xhtml" target="_self">BitwiseOrValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_20_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_bitwise_xor_validation_fixture.xhtml" target="_self">BitwiseXorValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_21_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_box3x3_validation_fixture.xhtml" target="_self">Box3x3ValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_22_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_22_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_22_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_convolution_validation_fixed_point_fixture.xhtml" target="_self">ConvolutionValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_22_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_convolution_validation_fixture.xhtml" target="_self">ConvolutionValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_23_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_depth_concatenate_validation_fixture.xhtml" target="_self">DepthConcatenateValidationFixture< TensorType, ITensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_24_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_24_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_24_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_depth_convert_validation_fixed_point_fixture.xhtml" target="_self">DepthConvertValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T1, T2 ></a></td><td class="desc"></td></tr>
+<tr id="row_45_24_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_depth_convert_validation_fixture.xhtml" target="_self">DepthConvertValidationFixture< TensorType, AccessorType, FunctionType, T1, T2 ></a></td><td class="desc"></td></tr>
+<tr id="row_45_24_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_depth_convert_validation_fractional_bits_fixture.xhtml" target="_self">DepthConvertValidationFractionalBitsFixture< TensorType, AccessorType, FunctionType, T1, T2 ></a></td><td class="desc"></td></tr>
+<tr id="row_45_25_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_depthwise_convolution_validation_fixture.xhtml" target="_self">DepthwiseConvolutionValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_26_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_depthwise_separable_convolution_validation_fixture.xhtml" target="_self">DepthwiseSeparableConvolutionValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_27_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_27_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_27_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_dequantization_validation_fixed_point_fixture.xhtml" target="_self">DequantizationValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_27_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_dequantization_validation_fixture.xhtml" target="_self">DequantizationValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_28_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_28_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_28_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_direct_convolution_validation_fixed_point_fixture.xhtml" target="_self">DirectConvolutionValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_28_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_direct_convolution_validation_fixture.xhtml" target="_self">DirectConvolutionValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_29_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_flatten_layer_validation_fixture.xhtml" target="_self">FlattenLayerValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_30_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_floor_validation_fixture.xhtml" target="_self">FloorValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_31_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_31_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_31_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_fully_connected_layer_validation_fixed_point_fixture.xhtml" target="_self">FullyConnectedLayerValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T, run_interleave ></a></td><td class="desc"></td></tr>
+<tr id="row_45_31_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_fully_connected_layer_validation_fixture.xhtml" target="_self">FullyConnectedLayerValidationFixture< TensorType, AccessorType, FunctionType, T, run_interleave ></a></td><td class="desc"></td></tr>
+<tr id="row_45_32_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_gaussian3x3_validation_fixture.xhtml" target="_self">Gaussian3x3ValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_33_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_gaussian5x5_validation_fixture.xhtml" target="_self">Gaussian5x5ValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_34_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_34_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_34_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_g_e_m_m_validation_fixed_point_fixture.xhtml" target="_self">GEMMValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_34_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_g_e_m_m_validation_fixture.xhtml" target="_self">GEMMValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_35_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_harris_corners_validation_fixture.xhtml" target="_self">HarrisCornersValidationFixture< TensorType, AccessorType, ArrayType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_36_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_integral_image_validation_fixture.xhtml" target="_self">IntegralImageValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_37_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_l2_normalize_validation_fixture.xhtml" target="_self">L2NormalizeValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_38_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_mean_std_dev_validation_fixture.xhtml" target="_self">MeanStdDevValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_39_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_min_max_location_validation_fixture.xhtml" target="_self">MinMaxLocationValidationFixture< TensorType, AccessorType, ArrayType, ArrayAccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_40_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_non_linear_filter_validation_fixture.xhtml" target="_self">NonLinearFilterValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_41_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_41_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_41_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_normalization_validation_fixed_point_fixture.xhtml" target="_self">NormalizationValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_41_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_normalization_validation_fixture.xhtml" target="_self">NormalizationValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_42_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_42_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_42_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_pooling_layer_validation_fixed_point_fixture.xhtml" target="_self">PoolingLayerValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_42_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_global_pooling_layer_validation_fixture.xhtml" target="_self">GlobalPoolingLayerValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_42_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_pooling_layer_validation_fixture.xhtml" target="_self">PoolingLayerValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_43_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_43_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_43_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_quantization_validation_fixed_point_fixture.xhtml" target="_self">QuantizationValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_43_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_quantization_validation_fixture.xhtml" target="_self">QuantizationValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_44_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_reduction_operation_validation_fixture.xhtml" target="_self">ReductionOperationValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_45_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_reshape_layer_validation_fixture.xhtml" target="_self">ReshapeLayerValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_46_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_scale_validation_fixture.xhtml" target="_self">ScaleValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_47_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_sobel_validation_fixture.xhtml" target="_self">SobelValidationFixture< TensorType, AccessorType, FunctionType, T, U ></a></td><td class="desc"></td></tr>
+<tr id="row_45_48_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_45_48_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('45_48_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_softmax_validation_fixed_point_fixture.xhtml" target="_self">SoftmaxValidationFixedPointFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_48_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_softmax_validation_fixture.xhtml" target="_self">SoftmaxValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_49_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_table_lookup_validation_fixture.xhtml" target="_self">TableLookupValidationFixture< TensorType, AccessorType, FunctionType, LutAccessorType, LutType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_45_50_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_threshold_validation_fixture.xhtml" target="_self">ThresholdValidationFixture< TensorType, AccessorType, FunctionType, T ></a></td><td class="desc"></td></tr>
+<tr id="row_46_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_47_"><td class="entry"><img id="arr_47_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('47_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_fully_connected_layer_dataset.xhtml" target="_self">FullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_47_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_fully_connected_layer_dataset.xhtml" target="_self">AlexNetFullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_47_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_fully_connected_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV1FullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_47_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_fully_connected_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV4FullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_47_3_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_large_fully_connected_layer_dataset.xhtml" target="_self">LargeFullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_47_4_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_fully_connected_layer_dataset.xhtml" target="_self">LeNet5FullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_47_5_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_fully_connected_layer_dataset.xhtml" target="_self">SmallFullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_47_6_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_fully_connected_layer_dataset.xhtml" target="_self">VGG16FullyConnectedLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_48_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_49_"><td class="entry"><img id="arr_49_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('49_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="class_gemm_common.xhtml" target="_self">GemmCommon< To, Tr ></a></td><td class="desc"></td></tr>
+<tr id="row_49_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="class_gemm_interleaved.xhtml" target="_self">GemmInterleaved< strategy, To, Tr ></a></td><td class="desc"></td></tr>
+<tr id="row_50_" class="even"><td class="entry"><img id="arr_50_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('50_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_g_e_m_m_dataset.xhtml" target="_self">GEMMDataset</a></td><td class="desc"></td></tr>
+<tr id="row_50_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_google_net_g_e_m_m_dataset.xhtml" target="_self">GoogleNetGEMMDataset</a></td><td class="desc"></td></tr>
+<tr id="row_50_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_g_e_m_m_dataset.xhtml" target="_self">GoogLeNetInceptionV1GEMMDataset</a></td><td class="desc"></td></tr>
+<tr id="row_50_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_large_g_e_m_m_dataset.xhtml" target="_self">LargeGEMMDataset</a></td><td class="desc"></td></tr>
+<tr id="row_50_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_matrix_multiply_g_e_m_m_dataset.xhtml" target="_self">MatrixMultiplyGEMMDataset</a></td><td class="desc"></td></tr>
+<tr id="row_50_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_g_e_m_m_dataset.xhtml" target="_self">SmallGEMMDataset</a></td><td class="desc"></td></tr>
+<tr id="row_51_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1gpu__props.xhtml" target="_self">gpu_props</a></td><td class="desc"></td></tr>
+<tr id="row_52_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1gpu__raw__gpu__props.xhtml" target="_self">gpu_raw_gpu_props</a></td><td class="desc"></td></tr>
+<tr id="row_53_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_54_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_55_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_56_" class="even"><td class="entry"><img id="arr_56_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('56_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_56_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_56_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_56_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" target="_self">SimpleTensor< T ></a></td><td class="desc">Simple tensor object that stores elements in a consecutive chunk of memory </td></tr>
+<tr id="row_56_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" target="_self">SimpleTensor< float ></a></td><td class="desc"></td></tr>
+<tr id="row_56_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" target="_self">SimpleTensor< T2 ></a></td><td class="desc"></td></tr>
+<tr id="row_56_5_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" target="_self">SimpleTensor< uint32_t ></a></td><td class="desc"></td></tr>
+<tr id="row_56_6_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_56_6_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('56_6_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" target="_self">SimpleTensor< uint8_t ></a></td><td class="desc"></td></tr>
+<tr id="row_56_6_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_57_"><td class="entry"><img id="arr_57_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('57_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_57_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_access_window_auto_padding.xhtml" target="_self">AccessWindowAutoPadding</a></td><td class="desc">Dummy access window </td></tr>
+<tr id="row_57_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_57_1_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('57_1_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_access_window_rectangle.xhtml" target="_self">AccessWindowRectangle</a></td><td class="desc">Implementation of a rectangular access pattern </td></tr>
+<tr id="row_57_1_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_access_window_horizontal.xhtml" target="_self">AccessWindowHorizontal</a></td><td class="desc">Implementation of a row access pattern </td></tr>
+<tr id="row_57_1_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_access_window_transpose.xhtml" target="_self">AccessWindowTranspose</a></td><td class="desc">Implementation of a XY-transpose access pattern </td></tr>
+<tr id="row_57_1_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_access_window_vertical.xhtml" target="_self">AccessWindowVertical</a></td><td class="desc">Implementation of a column access pattern </td></tr>
+<tr id="row_57_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_access_window_static.xhtml" target="_self">AccessWindowStatic</a></td><td class="desc">Implementation of a static rectangular access pattern </td></tr>
+<tr id="row_58_" class="even"><td class="entry"><img id="arr_58_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('58_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_58_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_58_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_59_"><td class="entry"><img id="arr_59_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('59_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_i_array.xhtml" target="_self">IArray< T ></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_59_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_array.xhtml" target="_self">Array< T ></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_59_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_59_1_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('59_1_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml" target="_self">ICLArray< T ></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_59_1_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_array.xhtml" target="_self">CLArray< T ></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_60_" class="even"><td class="entry"><img id="arr_60_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('60_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_i_array.xhtml" target="_self">IArray< NELKInternalKeypoint ></a></td><td class="desc"></td></tr>
+<tr id="row_60_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_array.xhtml" target="_self">Array< NELKInternalKeypoint ></a></td><td class="desc"></td></tr>
+<tr id="row_61_"><td class="entry"><img id="arr_61_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('61_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_i_array_accessor.xhtml" target="_self">IArrayAccessor< T ></a></td><td class="desc">Common interface to provide information and access to array like structures </td></tr>
+<tr id="row_61_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_array_accessor.xhtml" target="_self">ArrayAccessor< T ></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_61_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_c_l_array_accessor.xhtml" target="_self">CLArrayAccessor< T ></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_62_" class="even"><td class="entry"><img id="arr_62_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('62_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_62_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_63_"><td class="entry"><img id="arr_63_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('63_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_63_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_63_0_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('63_0_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_63_0_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_63_0_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_63_0_1_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('63_0_1_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_63_0_1_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_" class="even"><td class="entry"><img id="arr_64_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('64_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_convolution_square.xhtml" target="_self">CLConvolutionSquare< matrix_size ></a></td><td class="desc">Basic function to execute square convolution.Currently it supports 5x5, 7x7, 9x9 </td></tr>
+<tr id="row_64_5_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_depth_concatenate.xhtml" target="_self">CLDepthConcatenate</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
+<tr id="row_64_6_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution.xhtml" target="_self">CLDepthwiseConvolution</a></td><td class="desc">Basic function to execute a generic depthwise convolution </td></tr>
+<tr id="row_64_7_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution3x3.xhtml" target="_self">CLDepthwiseConvolution3x3</a></td><td class="desc">Basic function to execute a depthwise convolution for kernel size 3x3xC </td></tr>
+<tr id="row_64_8_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_9_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_10_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_11_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_12_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_13_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_14_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_15_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_64_15_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('64_15_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_15_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_15_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_16_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_17_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp.xhtml" target="_self">CLGEMMLowp</a></td><td class="desc">Basic function to execute GEMMLowp on OpenCL </td></tr>
+<tr id="row_64_18_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_19_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_20_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_21_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_22_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_23_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_24_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_25_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_l2_normalize.xhtml" target="_self">CLL2Normalize</a></td><td class="desc">Perform reduction operation </td></tr>
+<tr id="row_64_26_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_27_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_28_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_29_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_30_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_31_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_normalization_layer.xhtml" target="_self">CLNormalizationLayer</a></td><td class="desc">Basic function to simulate a normalization layer </td></tr>
+<tr id="row_64_32_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_33_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_34_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_35_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_36_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_37_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_38_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1graph_1_1_c_l_map.xhtml" target="_self">CLMap</a></td><td class="desc">OpenCL map function </td></tr>
+<tr id="row_64_39_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1graph_1_1_c_l_unmap.xhtml" target="_self">CLUnmap</a></td><td class="desc">OpenCL un-map function </td></tr>
+<tr id="row_64_40_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_64_40_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('64_40_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_5_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_6_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_7_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_8_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_9_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_10_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_11_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_12_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_13_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_14_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_15_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_16_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_17_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_depth_convert.xhtml" target="_self">CLDepthConvert</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_depth_convert_kernel.xhtml">CLDepthConvertKernel</a> </td></tr>
+<tr id="row_64_40_18_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_19_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_20_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_21_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_22_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_23_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_24_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_25_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_26_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_27_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_28_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_29_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_30_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_31_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_32_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_33_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_34_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_35_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_36_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_37_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_38_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_39_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_40_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_41_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_42_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_43_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_44_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_40_45_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_64_41_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('64_41_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_5_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_6_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_7_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_8_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_9_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_10_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_11_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_12_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_13_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_14_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_15_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_16_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_17_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_depth_convert.xhtml" target="_self">NEDepthConvert</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_depth_convert_kernel.xhtml">NEDepthConvertKernel</a> </td></tr>
+<tr id="row_64_41_18_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_19_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_20_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_21_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_22_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_23_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_24_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_25_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_26_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_27_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_28_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_29_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_30_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_31_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_32_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_33_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_34_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_35_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_36_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_37_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_38_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_39_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_40_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_41_41_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_42_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_43_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_44_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_45_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_46_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_convolution_square.xhtml" target="_self">NEConvolutionSquare< matrix_size ></a></td><td class="desc">Basic function to execute convolution of size 5x5, 7x7, 9x9 </td></tr>
+<tr id="row_64_47_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_depth_concatenate.xhtml" target="_self">NEDepthConcatenate</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
+<tr id="row_64_48_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_49_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_50_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_51_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_52_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_53_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_54_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_55_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_56_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_57_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_64_57_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('64_57_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_57_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_57_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_58_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_59_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp.xhtml" target="_self">NEGEMMLowp</a></td><td class="desc">Basic function to execute GEMMLowp on NEON </td></tr>
+<tr id="row_64_60_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_61_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_62_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_63_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_64_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_65_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_l2_normalize.xhtml" target="_self">NEL2Normalize</a></td><td class="desc">Basic function to perform a L2 normalization on a given axis </td></tr>
+<tr id="row_64_66_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_67_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_68_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_69_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_70_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_71_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_normalization_layer.xhtml" target="_self">NENormalizationLayer</a></td><td class="desc">Basic function to simulate a normalization layer </td></tr>
+<tr id="row_64_72_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_73_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_74_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_75_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_76_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_77_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_78_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_64_79_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_65_"><td class="entry"><img id="arr_65_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('65_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_65_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_65_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_65_1_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('65_1_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_65_1_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_" class="even"><td class="entry"><img id="arr_66_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_66_0_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_0_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_5_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_6_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_7_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_8_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_9_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_10_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_11_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_12_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_13_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_14_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_depth_concatenate_kernel.xhtml" target="_self">CLDepthConcatenateKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
+<tr id="row_66_0_15_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution3x3_kernel.xhtml" target="_self">CLDepthwiseConvolution3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor </td></tr>
+<tr id="row_66_0_16_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_17_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_18_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_19_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_20_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_21_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_22_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_23_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_24_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_25_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_26_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_27_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_28_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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 compute low precision matrix multiplication kernel </td></tr>
+<tr id="row_66_0_29_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_30_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_31_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_32_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_33_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_34_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_35_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_36_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_37_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_38_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_39_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_40_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_41_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_42_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_l2_normalize_kernel.xhtml" target="_self">CLL2NormalizeKernel</a></td><td class="desc">Interface for the reduction operation kernel </td></tr>
+<tr id="row_66_0_43_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_44_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_45_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_46_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_47_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_48_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_49_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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 the logits values around the max value and exponentiating the result </td></tr>
+<tr id="row_66_0_50_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_51_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_52_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_53_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_54_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_55_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_56_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_57_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_58_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_59_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_60_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_61_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_62_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_63_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_64_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_65_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_66_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_67_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_68_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_69_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_weights_reshape_kernel.xhtml" target="_self">CLWeightsReshapeKernel</a></td><td class="desc"></td></tr>
+<tr id="row_66_0_70_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_66_0_70_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('66_0_70_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_66_0_70_2_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('66_0_70_2_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_5_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_convolution_kernel.xhtml" target="_self">CLConvolutionKernel< matrix_size ></a></td><td class="desc">Interface for the kernel to run an arbitrary size convolution on a tensor </td></tr>
+<tr id="row_66_0_70_2_6_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_depth_convert_kernel.xhtml" target="_self">CLDepthConvertKernel</a></td><td class="desc">Interface for the depth conversion kernel </td></tr>
+<tr id="row_66_0_70_2_7_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_8_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_9_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_10_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_11_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_12_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_13_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_14_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_15_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_16_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_66_0_70_2_16_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_0_70_2_16_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_separable_convolution_hor_kernel.xhtml" target="_self">CLSeparableConvolutionHorKernel< matrix_size ></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_66_0_70_2_16_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_17_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_66_0_70_2_17_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_0_70_2_17_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_c_l_separable_convolution_vert_kernel.xhtml" target="_self">CLSeparableConvolutionVertKernel< matrix_size ></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_66_0_70_2_17_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_18_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_19_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_20_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_21_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_22_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_23_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_66_0_70_2_23_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('66_0_70_2_23_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_0_70_2_23_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_66_1_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('66_1_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_66_1_3_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_1_3_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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 NEON kernels having 1 tensor input and 1 tensor output </td></tr>
+<tr id="row_66_1_3_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_66_1_3_2_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_1_3_2_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_2_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_accumulate_weighted_f_p16_kernel.xhtml" target="_self">NEAccumulateWeightedFP16Kernel</a></td><td class="desc">Interface for the accumulate weighted kernel using F16 </td></tr>
+<tr id="row_66_1_3_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_66_1_3_3_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_1_3_3_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_3_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_box3x3_f_p16_kernel.xhtml" target="_self">NEBox3x3FP16Kernel</a></td><td class="desc">NEON kernel to perform a Box 3x3 filter using F16 simd </td></tr>
+<tr id="row_66_1_3_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_5_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_convolution_kernel.xhtml" target="_self">NEConvolutionKernel< matrix_size ></a></td><td class="desc">Interface for the kernel to run an arbitrary size convolution on a tensor </td></tr>
+<tr id="row_66_1_3_6_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_7_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_8_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_9_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_10_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_11_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_12_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_13_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_14_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_15_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_16_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_17_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_18_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_19_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_20_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_3_21_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_separable_convolution_hor_kernel.xhtml" target="_self">NESeparableConvolutionHorKernel< matrix_size ></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_66_1_3_22_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_separable_convolution_vert_kernel.xhtml" target="_self">NESeparableConvolutionVertKernel< matrix_size ></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_66_1_3_23_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_66_1_4_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_1_4_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_4_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_harris_score_f_p16_kernel.xhtml" target="_self">NEHarrisScoreFP16Kernel< block_size ></a></td><td class="desc">Interface for the accumulate Weighted kernel using F16 </td></tr>
+<tr id="row_66_1_4_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_harris_score_kernel.xhtml" target="_self">NEHarrisScoreKernel< block_size ></a></td><td class="desc">Template NEON kernel to perform Harris Score </td></tr>
+<tr id="row_66_1_5_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_66_1_5_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_1_5_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_5_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_warp_affine_kernel.xhtml" target="_self">NEWarpAffineKernel< interpolation ></a></td><td class="desc">Template interface for the kernel to compute warp affine </td></tr>
+<tr id="row_66_1_5_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_warp_perspective_kernel.xhtml" target="_self">NEWarpPerspectiveKernel< interpolation ></a></td><td class="desc">Template interface for the kernel to compute warp perspective </td></tr>
+<tr id="row_66_1_6_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_7_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_8_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_9_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_10_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_11_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_12_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_13_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_14_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_15_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_16_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_17_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_18_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_19_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_20_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_depth_concatenate_kernel.xhtml" target="_self">NEDepthConcatenateKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
+<tr id="row_66_1_21_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_depth_convert_kernel.xhtml" target="_self">NEDepthConvertKernel</a></td><td class="desc">Depth conversion kernel </td></tr>
+<tr id="row_66_1_22_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_23_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_24_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_bias_accumulate_kernel.xhtml" target="_self">NEDirectConvolutionLayerBiasAccumulateKernel</a></td><td class="desc">NEON kernel to accumulate the biases to each element of the input tensor </td></tr>
+<tr id="row_66_1_25_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_26_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_27_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_28_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_29_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_30_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_31_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_32_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_66_1_32_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_1_32_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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">AssemblyBase/armv7a NEON kernel to multiply two input matrices "A" and "B" </td></tr>
+<tr id="row_66_1_32_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_a_arch32_kernel.xhtml" target="_self">NEGEMMAArch32Kernel</a></td><td class="desc">AArch32/armv7a NEON kernel to multiply two input matrices "A" and "B" </td></tr>
+<tr id="row_66_1_32_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_a_arch64_kernel.xhtml" target="_self">NEGEMMAArch64Kernel</a></td><td class="desc">AArch64 NEON kernel to multiply two input matrices "A" and "B" </td></tr>
+<tr id="row_66_1_33_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_34_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_35_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_36_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_66_1_36_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_1_36_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_36_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_gradient_f_p16_kernel.xhtml" target="_self">NEGradientFP16Kernel</a></td><td class="desc">NEON kernel to perform Gradient computation </td></tr>
+<tr id="row_66_1_37_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_38_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_39_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_40_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_41_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_42_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_l2_normalize_kernel.xhtml" target="_self">NEL2NormalizeKernel</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_66_1_43_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_44_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_45_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_logits1_d_norm_kernel.xhtml" target="_self">NELogits1DNormKernel</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_66_1_46_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_logits1_d_shift_exp_sum_kernel.xhtml" target="_self">NELogits1DShiftExpSumKernel</a></td><td class="desc">Interface for shifting the logits values around the max value and exponentiating the result </td></tr>
+<tr id="row_66_1_47_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_f_p16_kernel.xhtml" target="_self">NEMagnitudePhaseFP16Kernel< mag_type, phase_type ></a></td><td class="desc">Template interface for the kernel to compute magnitude and phase </td></tr>
+<tr id="row_66_1_48_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_kernel.xhtml" target="_self">NEMagnitudePhaseKernel< mag_type, phase_type ></a></td><td class="desc">Template interface for the kernel to compute magnitude and phase </td></tr>
+<tr id="row_66_1_49_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_50_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_51_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_52_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_53_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_54_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img id="arr_66_1_54_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('66_1_54_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_54_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_n_e_non_maxima_suppression3x3_f_p16_kernel.xhtml" target="_self">NENonMaximaSuppression3x3FP16Kernel</a></td><td class="desc">NEON kernel to perform Non-Maxima suppression 3x3 with intermediate results in F16 if the input data type is F32 </td></tr>
+<tr id="row_66_1_55_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_56_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_57_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_58_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_59_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_60_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_61_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_62_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_63_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_64_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_65_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_66_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_67_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_68_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_69_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_70_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_66_1_71_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_67_"><td class="entry"><img id="arr_67_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('67_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_67_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_blob_lifetime_manager.xhtml" target="_self">BlobLifetimeManager</a></td><td class="desc">Class that tracks the lifetime of registered tensors and calculates the systems memory requirements in terms of blobs </td></tr>
+<tr id="row_68_" class="even"><td class="entry"><img id="arr_68_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('68_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_68_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_68_0_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('68_0_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_68_0_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_68_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_69_"><td class="entry"><img id="arr_69_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('69_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_i_lut_accessor.xhtml" target="_self">ILutAccessor< T ></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_69_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_c_l_lut_accessor.xhtml" target="_self">CLLutAccessor< T ></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_69_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_lut_accessor.xhtml" target="_self">LutAccessor< T ></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_69_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1_raw_lut_accessor.xhtml" target="_self">RawLutAccessor< T ></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_70_" class="even"><td class="entry"><img id="arr_70_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('70_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_70_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_70_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_71_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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>
+<tr id="row_72_" class="even"><td class="entry"><img id="arr_72_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('72_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_i_measurement.xhtml" target="_self">IMeasurement</a></td><td class="desc">Abstract measurement </td></tr>
+<tr id="row_72_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_typed_measurement.xhtml" target="_self">TypedMeasurement< T ></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 double. ">Measurement</a> of a specific type </td></tr>
+<tr id="row_72_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_72_1_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('72_1_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_typed_measurement.xhtml" target="_self">TypedMeasurement< double ></a></td><td class="desc"></td></tr>
+<tr id="row_72_1_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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 double </td></tr>
+<tr id="row_73_"><td class="entry"><img id="arr_73_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('73_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_i_memory_group.xhtml" target="_self">IMemoryGroup</a></td><td class="desc">Memory group interface </td></tr>
+<tr id="row_73_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_memory_group_base.xhtml" target="_self">MemoryGroupBase< typename ></a></td><td class="desc">Memory group </td></tr>
+<tr id="row_73_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_memory_group_base.xhtml" target="_self">MemoryGroupBase< CLTensor ></a></td><td class="desc"></td></tr>
+<tr id="row_73_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_memory_group_base.xhtml" target="_self">MemoryGroupBase< Tensor ></a></td><td class="desc"></td></tr>
+<tr id="row_74_" class="even"><td class="entry"><img id="arr_74_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('74_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml" target="_self">IMemoryManager</a></td><td class="desc">Memory manager interface to handle allocations of backing memory </td></tr>
+<tr id="row_74_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_75_"><td class="entry"><img id="arr_75_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('75_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_i_memory_pool.xhtml" target="_self">IMemoryPool</a></td><td class="desc">Memory Pool Inteface </td></tr>
+<tr id="row_75_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_76_" class="even"><td class="entry"><img id="arr_76_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('76_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_76_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_76_0_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('76_0_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_76_0_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_76_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_77_"><td class="entry"><img id="arr_77_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('77_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_77_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_77_0_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('77_0_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_77_0_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_77_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_78_" class="even"><td class="entry"><img id="arr_78_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('78_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_78_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1graph_1_1_activation_layer.xhtml" target="_self">ActivationLayer</a></td><td class="desc">Activation Layer node </td></tr>
+<tr id="row_78_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1graph_1_1_convolution_layer.xhtml" target="_self">ConvolutionLayer</a></td><td class="desc">Convolution layer node </td></tr>
+<tr id="row_78_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1graph_1_1_fully_connected_layer.xhtml" target="_self">FullyConnectedLayer</a></td><td class="desc">Fully connected layer node </td></tr>
+<tr id="row_78_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1graph_1_1_pooling_layer.xhtml" target="_self">PoolingLayer</a></td><td class="desc">Pooling layer node </td></tr>
+<tr id="row_78_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1graph_1_1_softmax_layer.xhtml" target="_self">SoftmaxLayer</a></td><td class="desc">Softmax layer node </td></tr>
+<tr id="row_79_"><td class="entry"><img id="arr_79_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('79_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_79_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_79_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_79_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_80_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="struct_internal_keypoint.xhtml" target="_self">InternalKeypoint</a></td><td class="desc"></td></tr>
+<tr id="row_81_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_82_" class="even"><td class="entry"><img id="arr_82_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('82_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_i_pool_manager.xhtml" target="_self">IPoolManager</a></td><td class="desc">Memory pool manager interface </td></tr>
+<tr id="row_82_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1_pool_manager.xhtml" target="_self">PoolManager</a></td><td class="desc">Memory pool manager </td></tr>
+<tr id="row_83_"><td class="entry"><img id="arr_83_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('83_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_83_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_83_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_84_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1traits_1_1is__contained.xhtml" target="_self">is_contained< T, Tuple ></a></td><td class="desc">Check if a type T is contained in a tuple Tuple of types </td></tr>
+<tr id="row_85_"><td class="entry"><img id="arr_85_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('85_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1traits_1_1is__contained.xhtml" target="_self">is_contained< T, std::tuple< Ts...> ></a></td><td class="desc"></td></tr>
+<tr id="row_85_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1traits_1_1is__contained_3_01_t_00_01std_1_1tuple_3_01_u_00_01_ts_8_8_8_4_01_4.xhtml" target="_self">is_contained< T, std::tuple< U, Ts...> ></a></td><td class="desc"></td></tr>
+<tr id="row_86_" class="even"><td class="entry"><img id="arr_86_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('86_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><b>is_floating_point</b></td><td class="desc"></td></tr>
+<tr id="row_86_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1validation_1_1is__floating__point.xhtml" target="_self">is_floating_point< T ></a></td><td class="desc"></td></tr>
+<tr id="row_87_"><td class="entry"><img id="arr_87_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('87_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_87_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_87_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_87_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_88_" class="even"><td class="entry"><img id="arr_88_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('88_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_88_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_88_0_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('88_0_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_88_0_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_88_0_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_88_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_88_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_89_"><td class="entry"><img id="arr_89_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('89_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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 class. ">Tensor</a> accessor interface </td></tr>
+<tr id="row_89_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_89_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_89_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_90_" class="even"><td class="entry"><img id="arr_90_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('90_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_90_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_90_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_91_"><td class="entry"><img id="arr_91_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('91_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_91_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_91_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_92_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1datasets_1_1_fully_connected_layer_dataset_1_1iterator.xhtml" target="_self">FullyConnectedLayerDataset::iterator</a></td><td class="desc"></td></tr>
+<tr id="row_93_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_94_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1datasets_1_1_g_e_m_m_dataset_1_1iterator.xhtml" target="_self">GEMMDataset::iterator</a></td><td class="desc"></td></tr>
+<tr id="row_95_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1datasets_1_1_batch_normalization_layer_dataset_1_1iterator.xhtml" target="_self">BatchNormalizationLayerDataset::iterator</a></td><td class="desc"></td></tr>
+<tr id="row_96_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1datasets_1_1_convolution_layer_dataset_1_1iterator.xhtml" target="_self">ConvolutionLayerDataset::iterator</a></td><td class="desc"></td></tr>
+<tr id="row_97_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1datasets_1_1_depthwise_convolution_dataset_1_1iterator.xhtml" target="_self">DepthwiseConvolutionDataset::iterator</a></td><td class="desc"></td></tr>
+<tr id="row_98_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1datasets_1_1_depthwise_separable_convolution_layer_dataset_1_1iterator.xhtml" target="_self">DepthwiseSeparableConvolutionLayerDataset::iterator</a></td><td class="desc"></td></tr>
+<tr id="row_99_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1datasets_1_1_pooling_layer_dataset_1_1iterator.xhtml" target="_self">PoolingLayerDataset::iterator</a></td><td class="desc"></td></tr>
+<tr id="row_100_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1datasets_1_1_reshape_layer_dataset_1_1iterator.xhtml" target="_self">ReshapeLayerDataset::iterator</a></td><td class="desc"></td></tr>
+<tr id="row_101_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1datasets_1_1_r_o_i_pooling_layer_dataset_1_1iterator.xhtml" target="_self">ROIPoolingLayerDataset::iterator</a></td><td class="desc"></td></tr>
+<tr id="row_102_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1datasets_1_1_threshold_dataset_1_1iterator.xhtml" target="_self">ThresholdDataset::iterator</a></td><td class="desc"></td></tr>
+<tr id="row_103_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_container_dataset_1_1iterator.xhtml" target="_self">ContainerDataset< T >::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> for the dataset </td></tr>
+<tr id="row_104_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_initializer_list_dataset_1_1iterator.xhtml" target="_self">InitializerListDataset< T >::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> for the dataset </td></tr>
+<tr id="row_105_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_join_dataset_1_1iterator.xhtml" target="_self">JoinDataset< T, U >::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> for the dataset </td></tr>
+<tr id="row_106_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_range_dataset_1_1iterator.xhtml" target="_self">RangeDataset< T >::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> for the dataset </td></tr>
+<tr id="row_107_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset_1_1iterator.xhtml" target="_self">SingletonDataset< T >::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> for the dataset </td></tr>
+<tr id="row_108_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_zip_dataset_1_1iterator.xhtml" target="_self">ZipDataset< T, U >::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> for the dataset </td></tr>
+<tr id="row_109_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_cartesian_product_dataset_1_1iterator.xhtml" target="_self">CartesianProductDataset< T, U >::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> for the dataset </td></tr>
+<tr id="row_110_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1kbase__hwcnt__reader__metadata.xhtml" target="_self">kbase_hwcnt_reader_metadata</a></td><td class="desc"></td></tr>
+<tr id="row_111_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1kbase__uk__gpuprops.xhtml" target="_self">kbase_uk_gpuprops</a></td><td class="desc"></td></tr>
+<tr id="row_112_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_113_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="struct_keypoint.xhtml" target="_self">Keypoint</a></td><td class="desc"></td></tr>
+<tr id="row_114_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_115_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_le_net5_network.xhtml" target="_self">LeNet5Network< TensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction ></a></td><td class="desc">Lenet5 model object </td></tr>
+<tr id="row_116_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_le_net5_network.xhtml" target="_self">LeNet5Network< TensorType, arm_compute::test::Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction ></a></td><td class="desc"></td></tr>
+<tr id="row_117_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1mali__base__gpu__coherent__group.xhtml" target="_self">mali_base_gpu_coherent_group</a></td><td class="desc"></td></tr>
+<tr id="row_118_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1mali__base__gpu__coherent__group__info.xhtml" target="_self">mali_base_gpu_coherent_group_info</a></td><td class="desc"></td></tr>
+<tr id="row_119_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1mali__base__gpu__core__props.xhtml" target="_self">mali_base_gpu_core_props</a></td><td class="desc"></td></tr>
+<tr id="row_120_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1mali__base__gpu__l2__cache__props.xhtml" target="_self">mali_base_gpu_l2_cache_props</a></td><td class="desc"></td></tr>
+<tr id="row_121_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1mali__base__gpu__props.xhtml" target="_self">mali_base_gpu_props</a></td><td class="desc"></td></tr>
+<tr id="row_122_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1mali__base__gpu__thread__props.xhtml" target="_self">mali_base_gpu_thread_props</a></td><td class="desc"></td></tr>
+<tr id="row_123_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structmali__userspace_1_1mali__base__gpu__tiler__props.xhtml" target="_self">mali_base_gpu_tiler_props</a></td><td class="desc"></td></tr>
+<tr id="row_124_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1_min_max_location_values.xhtml" target="_self">MinMaxLocationValues< MinMaxType ></a></td><td class="desc"></td></tr>
+<tr id="row_125_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1_min_max_location_values.xhtml" target="_self">MinMaxLocationValues< T ></a></td><td class="desc"></td></tr>
+<tr id="row_126_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1_min_max_location_values.xhtml" target="_self">MinMaxLocationValues< target_type ></a></td><td class="desc"></td></tr>
+<tr id="row_127_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_128_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_129_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_130_" class="even"><td class="entry"><img id="arr_130_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('130_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_130_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_enum_list_option.xhtml" target="_self">EnumListOption< T ></a></td><td class="desc">Implementation of an option that accepts any number of values from a fixed set </td></tr>
+<tr id="row_130_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_list_option.xhtml" target="_self">ListOption< T ></a></td><td class="desc">Implementation of an option that accepts any number of values </td></tr>
+<tr id="row_130_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_130_2_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('130_2_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_simple_option.xhtml" target="_self">SimpleOption< T ></a></td><td class="desc">Implementation of an option that accepts a single value </td></tr>
+<tr id="row_130_2_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_enum_option.xhtml" target="_self">EnumOption< T ></a></td><td class="desc">Implementation of a simple option that accepts a value from a fixed set </td></tr>
+<tr id="row_130_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img id="arr_130_3_" src="ftv2plastnode.png" alt="\" width="16" height="22" onclick="toggleFolder('130_3_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_simple_option.xhtml" target="_self">SimpleOption< bool ></a></td><td class="desc"></td></tr>
+<tr id="row_130_3_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2blank.png" alt=" " width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_131_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_132_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_133_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_134_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_135_"><td class="entry"><img id="arr_135_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('135_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_pooling_layer_dataset.xhtml" target="_self">PoolingLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_135_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_pooling_layer_dataset.xhtml" target="_self">AlexNetPoolingLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_135_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_pooling_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV1PoolingLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_135_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_pooling_layer_dataset.xhtml" target="_self">GoogLeNetInceptionV4PoolingLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_135_3_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_pooling_layer_dataset.xhtml" target="_self">LeNet5PoolingLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_135_4_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_pooling_layer_dataset.xhtml" target="_self">SqueezeNetPoolingLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_135_5_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_pooling_layer_dataset.xhtml" target="_self">VGG16PoolingLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_135_6_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_pooling_layer_dataset.xhtml" target="_self">YOLOV2PoolingLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_136_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_137_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_138_" class="even"><td class="entry"><img id="arr_138_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('138_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_138_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_138_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_139_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classprofiler.xhtml" target="_self">profiler</a></td><td class="desc"></td></tr>
+<tr id="row_140_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_141_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_142_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote.xhtml" target="_self">promote< T ></a></td><td class="desc"></td></tr>
+<tr id="row_143_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote.xhtml" target="_self">promote< T ></a></td><td class="desc"></td></tr>
+<tr id="row_144_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_145_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_146_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_147_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_148_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_149_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_150_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01int64__t_01_4.xhtml" target="_self">promote< int64_t ></a></td><td class="desc"></td></tr>
+<tr id="row_151_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_152_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_153_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_154_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_155_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_156_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_157_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01uint64__t_01_4.xhtml" target="_self">promote< uint64_t ></a></td><td class="desc"></td></tr>
+<tr id="row_158_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_159_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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"></td></tr>
+<tr id="row_160_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_161_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_162_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_relative_tolerance.xhtml" target="_self">RelativeTolerance< T ></a></td><td class="desc">Class reprensenting a relative tolerance value </td></tr>
+<tr id="row_163_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_relative_tolerance.xhtml" target="_self">RelativeTolerance< U ></a></td><td class="desc"></td></tr>
+<tr id="row_164_" class="even"><td class="entry"><img id="arr_164_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('164_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_reshape_layer_dataset.xhtml" target="_self">ReshapeLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_164_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_reshape_layer_dataset.xhtml" target="_self">SmallReshapeLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_165_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_166_" class="even"><td class="entry"><img id="arr_166_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('166_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_r_o_i_pooling_layer_dataset.xhtml" target="_self">ROIPoolingLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_166_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_r_o_i_pooling_layer_dataset.xhtml" target="_self">SmallROIPoolingLayerDataset</a></td><td class="desc"></td></tr>
+<tr id="row_167_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_168_" class="even"><td class="entry"><img id="arr_168_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('168_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><b>runtime_error</b></td><td class="desc"></td></tr>
+<tr id="row_168_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_168_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_169_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_170_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_171_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_172_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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 class. ">Tensor</a> class </td></tr>
+<tr id="row_173_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="struct_tensor3_d.xhtml" target="_self">Tensor3D</a></td><td class="desc">Structure to hold 3D tensor information </td></tr>
+<tr id="row_174_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="struct_tensor4_d.xhtml" target="_self">Tensor4D</a></td><td class="desc">Structure to hold 4D tensor information </td></tr>
+<tr id="row_175_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_176_" class="even"><td class="entry"><img id="arr_176_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('176_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_176_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< T ></a></td><td class="desc"></td></tr>
+<tr id="row_176_1_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetActivationLayerDataset(), data_types), framework::dataset::make("Batches", 1)))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_2_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetActivationLayerDataset(), data_types), framework::dataset::make("Batches",{4, 8})))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_3_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ActivationLayerDataset(), data_types), framework::dataset::make("Batches", 1)))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_4_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ActivationLayerDataset(), data_types), framework::dataset::make("Batches",{4, 8})))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_5_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ActivationLayerDataset(), data_types), framework::dataset::make("Batches", 1)))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_6_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ActivationLayerDataset(), data_types), framework::dataset::make("Batches",{4, 8})))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_7_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ActivationLayerDataset(), data_types), framework::dataset::make("Batches", 1)))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_8_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ActivationLayerDataset(), data_types), framework::dataset::make("Batches",{4, 8})))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_9_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetActivationLayerDataset(), data_types), framework::dataset::make("Batches", 1)))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_10_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetActivationLayerDataset(), data_types), framework::dataset::make("Batches",{4, 8})))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_11_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ActivationLayerDataset(), data_types), framework::dataset::make("Batches", 1)))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_12_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ActivationLayerDataset(), data_types), framework::dataset::make("Batches",{4, 8})))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_13_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ActivationLayerDataset(), data_types), framework::dataset::make("Batches", 1)))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_176_14_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase< decltype(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ActivationLayerDataset(), data_types), framework::dataset::make("Batches",{4, 8})))::type ></a></td><td class="desc"></td></tr>
+<tr id="row_177_"><td class="entry"><img id="arr_177_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('177_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_177_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case_factory.xhtml" target="_self">DataTestCaseFactory< T, D ></a></td><td class="desc"></td></tr>
+<tr id="row_177_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_simple_test_case_factory.xhtml" target="_self">SimpleTestCaseFactory< T ></a></td><td class="desc">Implementation of a test case factory to create non-data test cases </td></tr>
+<tr id="row_178_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1framework_1_1detail_1_1_test_case_registrar.xhtml" target="_self">TestCaseRegistrar< T ></a></td><td class="desc">Helper class to statically register a test case </td></tr>
+<tr id="row_179_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_180_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_181_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_182_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_183_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1_thread_info.xhtml" target="_self">ThreadInfo</a></td><td class="desc"></td></tr>
+<tr id="row_184_" class="even"><td class="entry"><img id="arr_184_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('184_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_threshold_dataset.xhtml" target="_self">ThresholdDataset</a></td><td class="desc"></td></tr>
+<tr id="row_184_0_" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_mixed_threshold_dataset.xhtml" target="_self">MixedThresholdDataset</a></td><td class="desc"></td></tr>
+<tr id="row_185_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="struct_transform_impl.xhtml" target="_self">TransformImpl< IntBy, BlockBy, Transposed, TOutSize, TInSize ></a></td><td class="desc"></td></tr>
+<tr id="row_186_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="struct_transpose_interleave_common.xhtml" target="_self">TransposeInterleaveCommon< IntBy, TIn, TOut ></a></td><td class="desc"></td></tr>
+<tr id="row_187_"><td class="entry"><img id="arr_187_" src="ftv2pnode.png" alt="o" width="16" height="22" onclick="toggleFolder('187_')"/><img src="ftv2cl.png" alt="C" width="24" height="22" /><b>true_type</b></td><td class="desc"></td></tr>
+<tr id="row_187_0_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1is__container_3_01std_1_1vector_3_01_v_00_01_a_01_4_01_4.xhtml" target="_self">is_container< std::vector< V, A > ></a></td><td class="desc"><a class="el" href="struct_vector.xhtml" title="Structure to hold Vector information. ">Vector</a> is considered a container </td></tr>
+<tr id="row_187_1_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_187_2_" class="even" style="display:none;"><td class="entry"><img src="ftv2vertline.png" alt="|" width="16" height="22" /><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_4_01_4.xhtml" target="_self">is_contained< T, std::tuple< T, Ts...> ></a></td><td class="desc"></td></tr>
+<tr id="row_188_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="unionmali__userspace_1_1uk__header.xhtml" target="_self">uk_header</a></td><td class="desc"></td></tr>
+<tr id="row_189_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="structarm__compute_1_1_valid_region.xhtml" target="_self">ValidRegion</a></td><td class="desc"></td></tr>
+<tr id="row_190_" class="even"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><a class="el" href="struct_vector.xhtml" target="_self">Vector</a></td><td class="desc">Structure to hold <a class="el" href="struct_vector.xhtml" title="Structure to hold Vector information. ">Vector</a> information </td></tr>
+<tr id="row_191_"><td class="entry"><img src="ftv2node.png" alt="o" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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_192_" class="even"><td class="entry"><img src="ftv2lastnode.png" alt="\" width="16" height="22" /><img src="ftv2cl.png" alt="C" width="24" height="22" /><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>
</table>
</div><!-- directory -->
</div><!-- contents -->
@@ -762,9 +992,9 @@
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- <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.11 </li>
+ <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 </li>
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