| /* |
| * Copyright (c) 2017-2018 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_NEFULLYCONNECTEDLAYER_H__ |
| #define __ARM_COMPUTE_NEFULLYCONNECTEDLAYER_H__ |
| |
| #include "arm_compute/runtime/IFunction.h" |
| |
| #include "arm_compute/core/NEON/kernels/NEFlattenLayerKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.h" |
| #include "arm_compute/core/NEON/kernels/NETransposeKernel.h" |
| #include "arm_compute/runtime/MemoryGroup.h" |
| #include "arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h" |
| #include "arm_compute/runtime/NEON/functions/NEGEMM.h" |
| #include "arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h" |
| #include "arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.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 NEFullyConnectedLayerReshapeWeights : 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 NEFullyConnectedLayerReshapeWeights |
| * |
| * @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 NEFullyConnectedLayerReshapeWeights (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 NEFullyConnectedLayer : public IFunction |
| { |
| public: |
| /** Constructor */ |
| NEFullyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEFullyConnectedLayer(const NEFullyConnectedLayer &) = delete; |
| /** Default move constructor */ |
| NEFullyConnectedLayer(NEFullyConnectedLayer &&) = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEFullyConnectedLayer &operator=(const NEFullyConnectedLayer &) = delete; |
| /** Default move assignment operator */ |
| NEFullyConnectedLayer &operator=(NEFullyConnectedLayer &&) = 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 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 NEFullyConnectedLayer |
| * |
| * @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 ITensor *input, const ITensor *weights, ITensor *output); |
| void configure_conv_fc(const ITensor *input, const ITensor *weights, ITensor *output); |
| void configure_mm(const ITensor *input, const ITensor *weights, ITensor *output); |
| |
| MemoryGroup _memory_group; |
| NEFlattenLayerKernel _flatten_kernel; |
| NEConvertFullyConnectedWeights _convert_weights; |
| NEFullyConnectedLayerReshapeWeights _reshape_weights_function; |
| NEGEMM _mm_gemm; |
| NEGEMMLowpMatrixMultiplyCore _mm_gemmlowp; |
| NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage; |
| NEGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel; |
| Tensor _flatten_output; |
| Tensor _gemmlowp_output; |
| Tensor _converted_weights_output; |
| Tensor _reshape_weights_output; |
| const ITensor *_original_weights; |
| bool _are_weights_converted; |
| bool _are_weights_reshaped; |
| bool _is_fc_after_conv; |
| bool _accumulate_biases; |
| bool _is_quantized; |
| bool _is_prepared; |
| }; |
| } // namespace arm_compute |
| #endif /* __ARM_COMPUTE_NEFULLYCONNECTEDLAYER_H__ */ |