arm_compute v17.03.1
diff --git a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
new file mode 100644
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+++ b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
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+/*
+ * Copyright (c) 2017 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h"
+
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/runtime/CL/CLScheduler.h"
+
+using namespace arm_compute;
+
+CLFullyConnectedLayer::CLFullyConnectedLayer()
+ : _conv_function(), _gemm_function(), _transpose_kernel(), _acc_biases_kernel(), _run_func(), _weights_transpose(), _is_first_run(true), _run_acc_biases(false)
+{
+}
+
+void CLFullyConnectedLayer::configure(ICLTensor *input, ICLTensor *weights, const ICLTensor *biases, ICLTensor *output)
+{
+ ARM_COMPUTE_ERROR_ON((weights->info()->num_dimensions() != 2) && (weights->info()->num_dimensions() != 4));
+
+ // Make sure that in the fully connected layer connected to fully connected layer case, the first dimension of the weights and input are same.
+ ARM_COMPUTE_ERROR_ON((weights->info()->num_dimensions() == 2) && (input->info()->dimension(0) != weights->info()->dimension(0)));
+
+ if(weights->info()->num_dimensions() != 2)
+ {
+ _conv_function.configure(input, weights, biases, output, PadStrideInfo(1, 1, 0, 0, DimensionRoundingType::FLOOR));
+ _run_func = &CLFullyConnectedLayer::run_conv;
+ return;
+ }
+
+ TensorShape shape_trans(weights->info()->dimension(1), weights->info()->dimension(0));
+ _weights_transpose.allocator()->init(TensorInfo(shape_trans, 1, weights->info()->data_type()));
+
+ // Configure kernels
+ _transpose_kernel.configure(weights, &_weights_transpose);
+ _gemm_function.configure(input, &_weights_transpose, nullptr, output, 1.0f, 0.0f);
+ if(biases != nullptr)
+ {
+ _acc_biases_kernel.configure(output, biases);
+ _run_acc_biases = true;
+ }
+
+ _run_func = &CLFullyConnectedLayer::run_fc;
+
+ // Allocate intermediate buffers
+ _weights_transpose.allocator()->allocate();
+}
+
+void CLFullyConnectedLayer::run_conv()
+{
+ _conv_function.run();
+}
+
+void CLFullyConnectedLayer::run_fc()
+{
+ if(_is_first_run)
+ {
+ _is_first_run = false;
+ CLScheduler::get().enqueue(_transpose_kernel);
+ }
+
+ _gemm_function.run();
+
+ if(_run_acc_biases)
+ {
+ CLScheduler::get().enqueue(_acc_biases_kernel);
+ }
+}
+
+void CLFullyConnectedLayer::run()
+{
+ ARM_COMPUTE_ERROR_ON(_run_func == nullptr);
+ (this->*_run_func)();
+}