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+/*
+ * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*
+ * Copyright (c) 2017-2019 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.
+ */
+
+#ifndef __ARM_COMPUTE_CLFULLYCONNECTEDLAYEREX_H__
+#define __ARM_COMPUTE_CLFULLYCONNECTEDLAYEREX_H__
+
+#include "arm_compute/runtime/CL/ICLSimpleFunction.h"
+
+#include "arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h"
+#include "arm_compute/core/CL/kernels/CLTransposeKernel.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h"
+#include "arm_compute/runtime/CL/functions/CLFlattenLayer.h"
+#include "arm_compute/runtime/CL/functions/CLGEMM.h"
+#include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h"
+#include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h"
+#include "arm_compute/runtime/IWeightsManager.h"
+#include "arm_compute/runtime/MemoryGroup.h"
+
+namespace arm_compute
+{
+/** Basic function to reshape the weights of Fully Connected layer with OpenCL. This function calls
+ * the following kernels:
+ *
+ * -# @ref CLTransposeKernel
+ *
+ * @note The fully connected layer accepts "weights" tensors only with 2 dimensions.
+ */
+class CLFullyConnectedLayerReshapeWeightsEx : public ICLSimpleFunction
+{
+public:
+ /** Set the input and output tensors.
+ *
+ * @param[in] input Weights tensor. The weights must be 2 dimensional. Data types supported:
+ * QASYMM8/F16/F32.
+ * @param[out] output Destination tensor which stores the transposed input tensor. Data type
+ * supported: Same as @p input.
+ */
+ void configure(const ICLTensor *input, ICLTensor *output);
+ /** Static function to check if given info will lead to a valid configuration of @ref
+ * CLFullyConnectedLayerReshapeWeightsEx
+ *
+ * @param[in] input Weights tensor. The weights must be 2 dimensional. Data types supported:
+ * QASYMM8/F16/F32.
+ * @param[in] output Destination tensor which stores the transposed input tensor. Data type
+ * supported: Same as @p input.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output);
+};
+
+namespace weights_transformations
+{
+/** Basic function to manage the reshape weights generated from @ref
+ * CLFullyConnectedLayerReshapeWeightsEx */
+class CLFullyConnectedLayerReshapeWeightsExManaged : public ITransformWeights
+{
+public:
+ // Inherited method override
+ void run() override
+ {
+ _output.allocator()->allocate();
+ _func.run();
+ _reshape_run = true;
+ }
+
+ // Inherited method override
+ void release() override { _output.allocator()->free(); }
+
+ // Inherited method override
+ ICLTensor *get_weights() override { return &_output; }
+
+ // Inherited method override
+ uint32_t uid() override { return _uid; }
+
+ /** Configures the @ref CLFullyConnectedLayerReshapeWeightsEx function
+ *
+ * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32.
+ */
+ void configure(const ICLTensor *input) { _func.configure(input, &_output); }
+
+private:
+ static constexpr uint32_t _uid = 0x0;
+ CLTensor _output{};
+ CLFullyConnectedLayerReshapeWeightsEx _func{};
+};
+} // namespace weights_transformations
+
+/** Basic function to compute a Fully Connected layer on OpenCL. This function calls the following
+ * OpenCL kernels:
+ *
+ * -# @ref CLIm2ColKernel (called when the input comes from a convolutional layer)
+ * -# @ref CLFullyConnectedLayerReshapeWeightsEx (if @p are_weights_reshaped is set to false and
+ * transpose_weights is set to true ) (called once)
+ * -# @ref CLGEMMMatrixMultiplyKernel or @ref CLGEMMLowpMatrixMultiplyCore (if quantized
+ * asymmetric)
+ * -# @ref CLGEMMMatrixAccumulateBiasesKernel or @ref
+ * CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint (if quantized asymmetric) (if @p biases is
+ * not equal to nullptr)
+ *
+ * @note The fully connected layer accepts "weights" tensors only with 2 dimensions.
+ */
+class CLFullyConnectedLayerEx : public IFunction
+{
+public:
+ /** Constructor */
+ CLFullyConnectedLayerEx(std::shared_ptr<IMemoryManager> memory_manager = nullptr,
+ IWeightsManager *weights_manager = nullptr);
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ CLFullyConnectedLayerEx(const CLFullyConnectedLayerEx &) = delete;
+ /** Default move constructor */
+ CLFullyConnectedLayerEx(CLFullyConnectedLayerEx &&) = default;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ CLFullyConnectedLayerEx &operator=(const CLFullyConnectedLayerEx &) = delete;
+ /** Default move assignment operator */
+ CLFullyConnectedLayerEx &operator=(CLFullyConnectedLayerEx &&) = default;
+ /** Set the input and output tensors.
+ *
+ * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32.
+ * @param[in] weights Weights tensor. The weights must be 2 dimensional.
+ * If this function is called after a Convolution Layer, the (transposed)
+ * weights will have as many rows as the product of the first 3 input's dimensions.
+ * If it is called after another FullyConnected Layer, the (transposed)
+ * weights will have as many rows as the input's first dimension.
+ * Data type supported: Same as @p input.
+ * @param[in] biases Bias tensor. Can be nullptr. Data type supported:Same as @p input.
+ * @param[out] output Destination tensor. Its shape should be equal to the output of a matrix
+ * multiplication between:
+ * - The output of im2col on the input and the (transposed) 2D weights, if the
+ * function is called after a Convolution Layer
+ * - The input tensor and the (transposed) 2D weights, if the function is
+ * called after another FullyConnected Layer.
+ * Data type supported: Same as @p input.
+ * @param[in] fc_info (Optional) Fully connected layer additional info
+ */
+ void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases,
+ ICLTensor *output, FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
+ /** Static function to check if given info will lead to a valid configuration of @ref
+ * CLFullyConnectedLayerEx
+ *
+ * @param[in] input Source tensor info. Data type supported: QASYMM8/F16/F32.
+ * @param[in] weights Weights tensor info. The weights must be 2 dimensional.
+ * If this function is called after a Convolution Layer, the (transposed)
+ * weights will have as many rows as the product of the first 3 input's dimensions.
+ * If it is called after another FullyConnected Layer, the (transposed)
+ * weights will have as many rows as the input's first dimension.
+ * Data type supported: Same as @p input.
+ * @param[in] biases Bias tensor info. Can be nullptr. Data type supported:Same as @p input.
+ * @param[out] output Destination tensor info. Its shape should be equal to the output of a
+ * matrix multiplication between:
+ * - The output of im2col on the input and the (transposed) 2D weights, if the
+ * function is called after a Convolution Layer
+ * - The input tensor and the (transposed) 2D weights, if the function is
+ * called after another FullyConnected Layer.
+ * Data type supported: Same as @p input.
+ * @param[in] fc_info (Optional) Fully connected layer additional info
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *weights,
+ const ITensorInfo *biases, const ITensorInfo *output,
+ FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
+
+ // Inherited methods override
+ void run() override;
+ void prepare() override;
+
+private:
+ void configure_fc_fc(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *bias,
+ ICLTensor *output, const FullyConnectedLayerInfo &fc_info);
+ void configure_conv_fc(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *bias,
+ ICLTensor *output, const FullyConnectedLayerInfo &fc_info);
+ void configure_mm(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *bias,
+ ICLTensor *output, const FullyConnectedLayerInfo &fc_info);
+
+ MemoryGroup _memory_group;
+ IWeightsManager *_weights_manager;
+ CLConvertFullyConnectedWeights _convert_weights;
+ weights_transformations::CLConvertFullyConnectedWeightsManaged _convert_weights_managed;
+ weights_transformations::CLFullyConnectedLayerReshapeWeightsExManaged
+ _reshape_weights_managed_function;
+ CLFlattenLayer _flatten_layer;
+ CLFullyConnectedLayerReshapeWeightsEx _reshape_weights_function;
+ CLGEMM _mm_gemm;
+ CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
+ CLTensor _flatten_output;
+ CLTensor _converted_weights_output;
+ CLTensor _reshape_weights_output;
+ bool _are_weights_converted;
+ bool _are_weights_reshaped;
+ bool _is_fc_after_conv;
+ bool _is_quantized;
+ bool _is_prepared;
+ const ICLTensor *_original_weights;
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_CLFULLYCONNECTEDLAYEREX_H__ */