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Diffstat (limited to 'compute/ARMComputeEx/arm_compute/runtime/CL/functions/CLFullyConnectedHybridLayer.h')
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diff --git a/compute/ARMComputeEx/arm_compute/runtime/CL/functions/CLFullyConnectedHybridLayer.h b/compute/ARMComputeEx/arm_compute/runtime/CL/functions/CLFullyConnectedHybridLayer.h new file mode 100644 index 000000000..1a0284a3e --- /dev/null +++ b/compute/ARMComputeEx/arm_compute/runtime/CL/functions/CLFullyConnectedHybridLayer.h @@ -0,0 +1,186 @@ +/* + * Copyright (c) 2019 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_CLFULLYCONNECTEDHYBRIDLAYER_H__ +#define __ARM_COMPUTE_CLFULLYCONNECTEDHYBRIDLAYER_H__ + +#include "arm_compute/runtime/CL/ICLSimpleFunction.h" + +#include "arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h" +#include "arm_compute/core/CL/kernels/CLMultiplyScaleFactorKernel.h" +#include "arm_compute/core/CL/kernels/CLQuantizationSymmetricKernel.h" +#include "arm_compute/core/CL/kernels/CLScaleFactorSymm8Kernel.h" +#include "arm_compute/core/CL/kernels/CLTransposeKernel.h" +#include "arm_compute/runtime/MemoryGroup.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCoreEx.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 CLFullyConnectedHybridLayerReshapeWeights : public ICLSimpleFunction +{ +public: + /** Set the input and output tensors. + * + * @param[in] input Weights tensor. The weights must be 2 dimensional. Data types supported: + * S8. + * @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 + * CLFullyConnectedHybridLayerReshapeWeights + * + * @param[in] input Weights tensor. The weights must be 2 dimensional. Data types supported: + * S8. + * @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); +}; + +/** 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 CLFullyConnectedHybridLayerReshapeWeights (if @p are_weights_reshaped is set to false + * and transpose_weights is set to true ) (called once) + * -# @ref CLGEMMLowpMatrixMultiplyCore (if quantized symmetric) + * -# @ref CLGEMMMatrixAccumulateBiasesKernel (if @p biases is not equal to nullptr) + * + * @note The fully connected layer accepts "weights" tensors only with 2 dimensions. + */ +class CLFullyConnectedHybridLayer : public IFunction +{ +public: + /** Constructor */ + CLFullyConnectedHybridLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLFullyConnectedHybridLayer(const CLFullyConnectedHybridLayer &) = delete; + /** Default move constructor */ + CLFullyConnectedHybridLayer(CLFullyConnectedHybridLayer &&) = default; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLFullyConnectedHybridLayer &operator=(const CLFullyConnectedHybridLayer &) = delete; + /** Default move assignment operator */ + CLFullyConnectedHybridLayer &operator=(CLFullyConnectedHybridLayer &&) = default; + /** Set the input and output tensors. + * + * @param[in] input Source tensor. Data type supported: 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: S8. + * @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 + * CLFullyConnectedHybridLayer + * + * @param[in] input Source tensor info. Data type supported: 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: S8. + * @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_mm(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output, + bool retain_internal_weights); + + MemoryGroup _memory_group; + CLFullyConnectedHybridLayerReshapeWeights _reshape_weights_kernel; + CLScaleFactorSymm8Kernel _scale_factor_kernel; + CLQuantizationSymmetricKernel _quant_input_kernel; + CLGEMMLowpMatrixMultiplyCoreEx _mm_gemmlowp; + CLMultiplyScaleFactorKernel _multiply_scale_kernel; + CLGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel; // TODO(COMPMID-1889): Use CLGEMM to + // add bias in + // CLFullyConnectedHybridLayer + CLTensor _reshape_weights_output; + CLTensor _quantized_input; + CLTensor _scale_factor; + CLTensor _gemmlowp_output; + bool _are_weights_reshaped; + bool _accumulate_biases; + bool _is_prepared; + const ICLTensor *_original_weights; +}; +} +#endif /* __ARM_COMPUTE_CLFULLYCONNECTEDHYBRIDLAYER_H__ */ |