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Diffstat (limited to 'arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h')
| -rw-r--r-- | arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h | 178 |
1 files changed, 83 insertions, 95 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h index b14650c0e9..885f8430cf 100644 --- a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h +++ b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 ARM Limited. + * Copyright (c) 2017-2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -24,46 +24,20 @@ #ifndef ARM_COMPUTE_NEFULLYCONNECTEDLAYER_H #define ARM_COMPUTE_NEFULLYCONNECTEDLAYER_H +#include "arm_compute/function_info/FullyConnectedLayerInfo.h" #include "arm_compute/runtime/IFunction.h" - -#include "arm_compute/core/NEON/kernels/NEFlattenLayerKernel.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/IMemoryManager.h" +#include "arm_compute/runtime/IWeightsManager.h" +#include "arm_compute/runtime/NEON/functions/NETranspose.h" #include "arm_compute/runtime/Tensor.h" +#include <memory> + 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/QASYMM8_SIGNED/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/QASYMM8_SIGNED/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); -}; - namespace weights_transformations { -/** Basic function to manage the reshape weights generated from @ref NEFullyConnectedLayerReshapeWeights */ +/** Basic function to manage the reshape weights generated from @ref NETranspose */ class NEFullyConnectedLayerReshapeWeightsManaged : public ITransformWeights { public: @@ -95,17 +69,17 @@ public: } private: - static constexpr uint32_t _uid = 0x0; - Tensor _output{}; - NEFullyConnectedLayerReshapeWeights _func{}; + static constexpr uint32_t _uid = 0x0; + Tensor _output{}; + NETranspose _func{}; }; } // namespace weights_transformations -/** 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 NEGEMMMatrixAdditionKernel or @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint (if quantized asymmetric) (if @p biases is not equal to nullptr) +/** Basic function to compute a Fully Connected layer. This function calls the following kernels: + * -# @ref cpu::kernels::CpuIm2ColKernel (called when the input comes from a convolutional layer) + * -# @ref NETranspose (if @p are_weights_reshaped is set to false and transpose_weights is set to true ) (called once) + * -# @ref NEGEMM or @ref NEGEMMLowpMatrixMultiplyCore (if quantized asymmetric) + * -# @ref cpu::kernels::CpuGemmMatrixAdditionKernel or @ref NEGEMMLowpOutputStage (if quantized asymmetric) (if @p biases is not equal to nullptr) * * @note The fully connected layer accepts "weights" tensors only with 2 dimensions. */ @@ -113,77 +87,91 @@ class NEFullyConnectedLayer : public IFunction { public: /** Constructor */ - NEFullyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr, IWeightsManager *weights_manager = nullptr); + NEFullyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr, + IWeightsManager *weights_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 moved (As this class contains pointers) */ + NEFullyConnectedLayer(NEFullyConnectedLayer &&) = delete; /** 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; + /** Prevent instances of this class from being moved (As this class contains pointers) */ + NEFullyConnectedLayer &operator=(NEFullyConnectedLayer &&) = delete; + /** Default destructor */ + ~NEFullyConnectedLayer(); /** Set the input and output tensors. * - * @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/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 weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED. - * @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 + * Valid data layouts: + * - NHWC + * - NCHW + * + * Valid data type configurations: + * |src0 |src1 |src2 |dst | + * |:--------------|:------------------|:------|:--------------| + * |F16 |F16 |F16 |F16 | + * |F32 |F32 |F32 |F32 | + * |QASYMM8 |QASYMM8 |S32 |QASYMM8 | + * |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED | + * + * @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/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 weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED. + * @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 + * @param[in] weights_info (Optional) Stores neccessary compute information when weights are already reshaped */ - void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, - FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo()); + void configure(const ITensor *input, + const ITensor *weights, + const ITensor *biases, + ITensor *output, + FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo(), + const WeightsInfo &weights_info = WeightsInfo()); /** 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/QASYMM8_SIGNED/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. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED. - * @param[in] 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 + * Similar to @ref NEFullyConnectedLayer::configure() * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, - FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo()); + static Status validate(const ITensorInfo *input, + const ITensorInfo *weights, + const ITensorInfo *biases, + const ITensorInfo *output, + FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo(), + const WeightsInfo &weights_info = WeightsInfo()); + + /** Static function that queries whether fixed-format kernel exists for a given problem description + * + * @param[out] expected_weight_format Format in which weights should be for found fixed format kernel + * @param[in] input Source tensor + * @param[in] weights Weights tensor. + * @param[in] biases Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED. + * @param[in] output Destination tensor + * @param[in] fc_info Fully connected layer additional info + * @param[in] weights_info Describes weights shape + * + * @return a status + */ + static Status has_opt_impl(arm_compute::WeightFormat &expected_weight_format, + const ITensorInfo *input, + const ITensorInfo *weights, + const ITensorInfo *biases, + const ITensorInfo *output, + const FullyConnectedLayerInfo &fc_info, + const WeightsInfo &weights_info); //Inherited methods override void run() override; void prepare() override; private: - void configure_fc_fc(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const ActivationLayerInfo &act); - void configure_conv_fc(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const ActivationLayerInfo &act); - void configure_mm(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const ActivationLayerInfo &act); - - MemoryGroup _memory_group; - IWeightsManager *_weights_manager; - NEFlattenLayerKernel _flatten_kernel; - NEConvertFullyConnectedWeights _convert_weights; - weights_transformations::NEConvertFullyConnectedWeightsManaged _convert_weights_managed; - NEFullyConnectedLayerReshapeWeights _reshape_weights_function; - weights_transformations::NEFullyConnectedLayerReshapeWeightsManaged _reshape_weights_managed_function; - NEGEMM _mm_gemm; - NEGEMMLowpMatrixMultiplyCore _mm_gemmlowp; - Tensor _flatten_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 _is_quantized_asymmetric; - bool _is_prepared; + struct Impl; + std::unique_ptr<Impl> _impl; }; } // namespace arm_compute #endif /* ARM_COMPUTE_NEFULLYCONNECTEDLAYER_H */ |