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Diffstat (limited to 'compute/ARMComputeEx/arm_compute/runtime/NEON/functions/NEFullyConnectedHybridLayer.h')
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diff --git a/compute/ARMComputeEx/arm_compute/runtime/NEON/functions/NEFullyConnectedHybridLayer.h b/compute/ARMComputeEx/arm_compute/runtime/NEON/functions/NEFullyConnectedHybridLayer.h new file mode 100644 index 000000000..42a786821 --- /dev/null +++ b/compute/ARMComputeEx/arm_compute/runtime/NEON/functions/NEFullyConnectedHybridLayer.h @@ -0,0 +1,164 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved + * 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_NEFULLYCONNECTEDHYBRIDLAYER_H__ +#define __ARM_COMPUTE_NEFULLYCONNECTEDHYBRIDLAYER_H__ + +#include "arm_compute/core/NEON/kernels/NEQuantizationSymmetricKernel.h" +#include "arm_compute/core/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.h" +#include "arm_compute/core/NEON/kernels/NEMuliplyScaleFactorKernel.h" +#include "arm_compute/core/NEON/kernels/NETransposeKernel.h" +#include "arm_compute/runtime/MemoryGroup.h" +#include "arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCoreEx.h" +#include "arm_compute/runtime/NEON/INESimpleFunctionNoBorder.h" +#include "arm_compute/runtime/Tensor.h" + +namespace arm_compute +{ +/** Basic function to reshape the weights of Fully Connected layer with NEON. This function calls + * the following kernels: + * + * -# @ref NETransposeKernel + * + * @note The fully connected layer accepts "weights" tensors only with 2 dimensions. + */ +class NEFullyConnectedHybridLayerReshapeWeights : public INESimpleFunctionNoBorder +{ +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. Data type supported: Same as @p input. + */ + void configure(const ITensor *input, ITensor *output); + /** Static function to check if given info will lead to a valid configuration of @ref + * NEFullyConnectedHybridLayerReshapeWeights + * + * @param[in] input Weights tensor info. The weights must be 2 dimensional. Data types supported: + * QASYMM8/F16/F32. + * @param[in] output Destination tensor info. 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 NEON. This function calls the following + * NEON kernels: + * -# @ref NEIm2ColKernel (called when the input comes from a convolutional layer) + * -# @ref NEFullyConnectedHybridLayerReshapeWeights (if @p are_weights_reshaped is set to false + * and transpose_weights is set to true ) (called once) + * -# @ref NEGEMMMatrixMultiplyKernel or @ref NEGEMMLowpMatrixMultiplyCore (if quantized + * asymmetric) + * -# @ref NEGEMMMatrixAccumulateBiasesKernel or @ref + * NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint (if quantized asymmetric) (if @p biases is + * not equal to nullptr) + * + * @note The fully connected layer accepts "weights" tensors only with 2 dimensions. + */ +class NEFullyConnectedHybridLayer : public IFunction +{ +public: + /** Constructor */ + NEFullyConnectedHybridLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEFullyConnectedHybridLayer(const NEFullyConnectedHybridLayer &) = delete; + /** Default move constructor */ + NEFullyConnectedHybridLayer(NEFullyConnectedHybridLayer &&) = default; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + NEFullyConnectedHybridLayer &operator=(const NEFullyConnectedHybridLayer &) = delete; + /** Default move assignment operator */ + NEFullyConnectedHybridLayer &operator=(NEFullyConnectedHybridLayer &&) = 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 ITensor *input, const ITensor *weights, const ITensor *biases, + ITensor *output, FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo()); + /** Static function to check if given info will lead to a valid configuration of @ref + * NEFullyConnectedHybridLayer + * + * @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 ITensor *input, const ITensor *weights, ITensor *output); + + MemoryGroup _memory_group; + NEFullyConnectedHybridLayerReshapeWeights _reshape_weights_function; + NEQuantizationSymmetricKernel _quant_input_kernel; + NEGEMMLowpMatrixMultiplyCoreEx _mm_gemmlowp; + NEMultiplyScaleFactorKernel _multiply_scale_kernel; + NEGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel; + Tensor _reshape_weights_output; + Tensor _quantized_input; + Tensor _scale_factor; + Tensor _gemmlowp_output; + const ITensor *_original_weights; + bool _are_weights_reshaped; + bool _accumulate_biases; + bool _is_prepared; +}; +} // namespace arm_compute +#endif /* __ARM_COMPUTE_NEFULLYCONNECTEDHYBRIDLAYER_H__ */ |