| /* |
| * 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. |
| */ |
| #ifndef __ARM_COMPUTE_NEFULLYCONNECTEDLAYER_H__ |
| #define __ARM_COMPUTE_NEFULLYCONNECTEDLAYER_H__ |
| |
| #include "arm_compute/runtime/IFunction.h" |
| |
| #include "arm_compute/core/NEON/kernels/NEGEMMInterleave4x4Kernel.h" |
| #include "arm_compute/core/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEIm2ColKernel.h" |
| #include "arm_compute/core/NEON/kernels/NETransposeKernel.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 (if @p transpose_weights is set to true) |
| * -# @ref NEGEMMTranspose1xWKernel (if @p is_batched_fc_layer is set to true) |
| * |
| * @note The fully connected layer accepts "weights" tensors only with 2 dimensions. |
| */ |
| class NEFullyConnectedLayerReshapeWeights : public IFunction |
| { |
| public: |
| /** Constructor */ |
| NEFullyConnectedLayerReshapeWeights(); |
| /** Set the input and output tensors. |
| * |
| * @param[in] input Weights tensor. The weights must be 2 dimensional. Data types supported: QS8/QS16/F32. |
| * @param[out] output Destination tensor. Data type supported: Same as @p input. |
| * @param[in] transpose_weights True if the weights must be transposed. Data types supported: Same as @p weights. |
| * @param[in] is_batched_fc_layer True if it is a batched fully connected layer |
| */ |
| void configure(const ITensor *input, ITensor *output, bool transpose_weights, bool is_batched_fc_layer); |
| |
| // Inherited methods overridden: |
| void run() override; |
| |
| private: |
| NETransposeKernel _transpose_kernel; |
| NEGEMMTranspose1xWKernel _transpose1xW_kernel; |
| Tensor _transpose_output; |
| bool _transpose_weights; |
| bool _is_batched_fc_layer; |
| }; |
| |
| /** 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 flag is set to false) (called once) |
| * -# @ref NEGEMMInterleave4x4Kernel (called if we have a multi-batch input) |
| * -# @ref NEGEMMMatrixMultiplyKernel |
| * -# @ref NEGEMMMatrixAccumulateBiasesKernel (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(); |
| /** Set the input and output tensors. |
| * |
| * @param[in] input Source tensor. Data type supported: QS8/QS16/F32. |
| * @param[in] weights Weights tensor. The weights must be 2 dimensional. 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. Data type supported: Same as @p input. |
| * @param[in] transpose_weights (Optional) Transpose the weights tensor if true. Defaults to true. |
| * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false. |
| */ |
| void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, bool transpose_weights = true, bool are_weights_reshaped = false); |
| |
| //Inherited methods override |
| void run() override; |
| |
| private: |
| void configure_fc_fc_wb(const ITensor *input, const ITensor *weights, ITensor *output); |
| void configure_fc_fc_nb(const ITensor *input, const ITensor *weights, ITensor *output); |
| void configure_conv_fc_wb(const ITensor *input, const ITensor *weights, ITensor *output); |
| void configure_conv_fc_nb(const ITensor *input, const ITensor *weights, ITensor *output); |
| |
| NEIm2ColKernel _im2col_kernel; |
| NEFullyConnectedLayerReshapeWeights _reshape_weights_kernel; |
| NEGEMMInterleave4x4Kernel _interleave4x4_kernel; |
| NEGEMMMatrixMultiplyKernel _mm_kernel; |
| NEGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel; |
| Tensor _im2col_output; |
| Tensor _interleave4x4_output; |
| Tensor _reshape_weights_output; |
| bool _are_weights_reshaped; |
| bool _is_fc_after_conv; |
| bool _is_batched_fc_layer; |
| bool _accumulate_biases; |
| }; |
| } |
| #endif /* __ARM_COMPUTE_NEFULLYCONNECTEDLAYER_H__ */ |