| /* |
| * 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_NEDEPTHWISECONVOLUTION_H__ |
| #define __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__ |
| |
| #include "arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h" |
| #include "arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/utils/misc/Macros.h" |
| #include "arm_compute/runtime/IFunction.h" |
| #include "arm_compute/runtime/IMemoryManager.h" |
| #include "arm_compute/runtime/MemoryGroup.h" |
| #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" |
| #include "arm_compute/runtime/NEON/functions/NEPermute.h" |
| #include "arm_compute/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.h" |
| #include "arm_compute/runtime/Tensor.h" |
| |
| namespace arm_compute |
| { |
| // Forward declarations |
| class ITensor; |
| |
| /** Basic function to execute a depthwise convolution for kernel size 3x3xC. This function calls the following NEON kernels: |
| * |
| * -# @ref NEDepthwiseConvolutionLayer3x3 |
| * -# @ref NEFillBorderKernel (if pad_x or pad_y > 0) |
| * |
| */ |
| class NEDepthwiseConvolutionLayer3x3 : public IFunction |
| { |
| public: |
| /** Default constructor */ |
| NEDepthwiseConvolutionLayer3x3(std::shared_ptr<IMemoryManager> memory_manager = nullptr); |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEDepthwiseConvolutionLayer3x3(const NEDepthwiseConvolutionLayer3x3 &) = delete; |
| /** Default move constructor */ |
| NEDepthwiseConvolutionLayer3x3(NEDepthwiseConvolutionLayer3x3 &&) = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEDepthwiseConvolutionLayer3x3 &operator=(const NEDepthwiseConvolutionLayer3x3 &) = delete; |
| /** Default move assignment operator */ |
| NEDepthwiseConvolutionLayer3x3 &operator=(NEDepthwiseConvolutionLayer3x3 &&) = default; |
| /** Initialize the function's source, destination, kernels and border_size. |
| * |
| * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [3, 3, IFM]. Data type supported: Same as @p input. |
| * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. |
| * Data type supported: Same as @p input. |
| * @param[out] output Destination tensor. Data type supported: same as @p input. |
| * @param[in] conv_info Padding and stride information to use for the convolution. |
| * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] act_info (Optional) Activation layer information in case of a fused activation. |
| * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). |
| */ |
| ARM_COMPUTE_DEPRECATED_REL_REPLACE(19.08, NEDepthwiseConvolutionLayerOptimized) |
| void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, |
| unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); |
| |
| /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayer3x3 |
| * |
| * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [3, 3, IFM]. Data type supported: Same as @p input. |
| * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. |
| * Data type supported: Same as @p input. |
| * @param[in] output Destination tensor. Data type supported: same as @p input. |
| * @param[in] conv_info Padding and stride information to use for the convolution. |
| * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] act_info (Optional) Activation layer information in case of a fused activation. |
| * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, |
| unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); |
| |
| // Inherited methods overriden: |
| void run() override; |
| void prepare() override; |
| |
| private: |
| /** Configure the kernels/functions for the generic pipeline. |
| * |
| * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [3, 3, IFM]. Data type supported: Same as @p input. |
| * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. |
| * Data type supported: Same as @p input. |
| * @param[out] output Destination tensor. Data type supported: same as @p input. |
| * @param[in] conv_info Padding and stride information to use for the convolution. |
| * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] act_info Activation layer information in case of a fused activation. |
| * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). |
| * |
| */ |
| void configure_generic(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, |
| unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation = Size2D(1U, 1U)); |
| /** Configure the kernels/functions for the optimized pipeline. |
| * |
| * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [3, 3, IFM]. Data type supported: Same as @p input. |
| * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. |
| * Data type supported: Same as @p input. |
| * @param[out] output Destination tensor. Data type supported: same as @p input. |
| * @param[in] conv_info Padding and stride information to use for the convolution. |
| * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] act_info Activation layer information in case of a fused activation. |
| */ |
| void configure_optimized(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, |
| unsigned int depth_multiplier, const ActivationLayerInfo &act_info); |
| /** Run generic kernel */ |
| void run_generic(); |
| /** Run optimized function */ |
| void run_optimized(); |
| |
| private: |
| MemoryGroup _memory_group; |
| NEDepthwiseConvolutionLayer3x3Kernel _dwc_kernel; |
| NEDepthwiseConvolutionAssemblyDispatch _dwc_optimized_func; |
| NEDirectConvolutionLayerOutputStageKernel _output_stage_kernel; |
| NEFillBorderKernel _border_handler; |
| NEPermute _permute_input; |
| NEPermute _permute_weights; |
| NEPermute _permute_output; |
| NEActivationLayer _activationlayer_function; |
| Tensor _accumulator; |
| Tensor _permuted_input; |
| Tensor _permuted_weights; |
| Tensor _permuted_output; |
| const ITensor *_original_weights; |
| bool _has_bias; |
| bool _is_quantized; |
| bool _is_optimized; |
| bool _is_nchw; |
| bool _permute; |
| bool _is_activationlayer_enabled; |
| bool _is_prepared; |
| }; |
| |
| /** Basic function to execute optimized depthwise convolution routines. This function calls the following NEON kernels: |
| * |
| * @note At the moment 3x3 and 5x5 convolution of stride 1, 2 are supported |
| * |
| * -# @ref NEFillBorderKernel (if pad_x or pad_y > 0) and no assembly kernel implementation is present |
| * -# @ref NEDepthwiseConvolutionLayer3x3Kernel if 3x3 and no assembly kernel implementation is present |
| * -# @ref NEDepthwiseConvolutionAssemblyDispatch if assembly kernel implementation is present |
| * -# @ref NEDirectConvolutionLayerOutputStageKernel if re-quantization of output is required |
| * -# @ref NEActivationLayer if fused activation is required |
| * |
| */ |
| class NEDepthwiseConvolutionLayerOptimized : public IFunction |
| { |
| public: |
| /** Default constructor */ |
| NEDepthwiseConvolutionLayerOptimized(std::shared_ptr<IMemoryManager> memory_manager = nullptr); |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEDepthwiseConvolutionLayerOptimized(const NEDepthwiseConvolutionLayerOptimized &) = delete; |
| /** Default move constructor */ |
| NEDepthwiseConvolutionLayerOptimized(NEDepthwiseConvolutionLayerOptimized &&) = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEDepthwiseConvolutionLayerOptimized &operator=(const NEDepthwiseConvolutionLayerOptimized &) = delete; |
| /** Default move assignment operator */ |
| NEDepthwiseConvolutionLayerOptimized &operator=(NEDepthwiseConvolutionLayerOptimized &&) = default; |
| /** Initialize the function's source, destination, kernels and border_size. |
| * |
| * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [W, H, IFM]. Data type supported: Same as @p input. |
| * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. |
| * Data type supported: Same as @p input. |
| * @param[out] output Destination tensor. Data type supported: same as @p input. |
| * @param[in] conv_info Padding and stride information to use for the convolution. |
| * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] act_info (Optional) Activation layer information in case of a fused activation. |
| * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). |
| */ |
| void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, |
| unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); |
| |
| /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayer3x3 |
| * |
| * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [W, H, IFM]. Data type supported: Same as @p input. |
| * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. |
| * Data type supported: Same as @p input. |
| * @param[in] output Destination tensor. Data type supported: same as @p input. |
| * @param[in] conv_info Padding and stride information to use for the convolution. |
| * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] act_info (Optional) Activation layer information in case of a fused activation. |
| * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, |
| unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); |
| |
| // Inherited methods overriden: |
| void run() override; |
| void prepare() override; |
| |
| private: |
| /** Configure the kernels/functions for the generic pipeline. |
| * |
| * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [W, H, IFM]. Data type supported: Same as @p input. |
| * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. |
| * Data type supported: Same as @p input. |
| * @param[out] output Destination tensor. Data type supported: same as @p input. |
| * @param[in] conv_info Padding and stride information to use for the convolution. |
| * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] act_info Activation layer information in case of a fused activation. |
| * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). |
| * |
| */ |
| void configure_generic(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, |
| unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation = Size2D(1U, 1U)); |
| /** Configure the kernels/functions for the optimized pipeline. |
| * |
| * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [W, H, IFM]. Data type supported: Same as @p input. |
| * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. |
| * Data type supported: Same as @p input. |
| * @param[out] output Destination tensor. Data type supported: same as @p input. |
| * @param[in] conv_info Padding and stride information to use for the convolution. |
| * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] act_info Activation layer information in case of a fused activation. |
| */ |
| void configure_optimized(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, |
| unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation = Size2D(1U, 1U)); |
| /** Run generic kernel */ |
| void run_generic(); |
| /** Run optimized function */ |
| void run_optimized(); |
| |
| private: |
| MemoryGroup _memory_group; |
| NEDepthwiseConvolutionLayer3x3Kernel _dwc_kernel; |
| NEDepthwiseConvolutionAssemblyDispatch _dwc_optimized_func; |
| NEDirectConvolutionLayerOutputStageKernel _output_stage_kernel; |
| NEFillBorderKernel _border_handler; |
| NEPermute _permute_input; |
| NEPermute _permute_weights; |
| NEPermute _permute_output; |
| NEActivationLayer _activationlayer_function; |
| Tensor _accumulator; |
| Tensor _permuted_input; |
| Tensor _permuted_weights; |
| Tensor _permuted_output; |
| const ITensor *_original_weights; |
| bool _has_bias; |
| bool _is_quantized; |
| bool _is_optimized; |
| bool _is_nchw; |
| bool _permute; |
| bool _is_activationlayer_enabled; |
| bool _is_prepared; |
| }; |
| |
| /** Basic function to execute a generic depthwise convolution. This function calls the following NEON kernels: |
| * |
| * -# @ref NEDepthwiseIm2ColKernel |
| * -# @ref NEDepthwiseWeightsReshapeKernel |
| * -# @ref NEGEMMMatrixVectorMultiplyKernel |
| * -# @ref NEFillBorderKernel (if pad_x or pad_y > 0) |
| * |
| */ |
| class NEDepthwiseConvolutionLayer : public IFunction |
| { |
| public: |
| /** Default constructor */ |
| NEDepthwiseConvolutionLayer(); |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEDepthwiseConvolutionLayer(const NEDepthwiseConvolutionLayer &) = delete; |
| /** Default move constructor */ |
| NEDepthwiseConvolutionLayer(NEDepthwiseConvolutionLayer &&) = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEDepthwiseConvolutionLayer &operator=(const NEDepthwiseConvolutionLayer &) = delete; |
| /** Default move assignment operator */ |
| NEDepthwiseConvolutionLayer &operator=(NEDepthwiseConvolutionLayer &&) = default; |
| /** Initialize the function's source, destination, weights and convolution information. |
| * |
| * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). |
| * @param[out] output Destination tensor. Data type supported: same as @p input. |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. |
| * @param[in] biases (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. |
| * Data type supported: Same as @p input, S32 when input is QASYMM8. |
| * @param[in] conv_info Padding and stride information to use for the convolution. |
| * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] act_info (Optional) Activation layer information in case of a fused activation. |
| * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). |
| */ |
| void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, |
| unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); |
| |
| /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayer |
| * |
| * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). |
| * @param[in] output Destination tensor. Data type supported: same as @p input. |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. |
| * @param[in] biases (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. |
| * Data type supported: Same as @p input, S32 when input is QASYMM8. |
| * @param[in] conv_info Padding and stride information to use for the convolution. |
| * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] act_info (Optional) Activation layer information in case of a fused activation. |
| * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, |
| unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); |
| |
| // Inherited methods overriden: |
| void run() override; |
| void prepare() override; |
| |
| private: |
| NEDepthwiseIm2ColKernel _im2col_kernel; |
| NEDepthwiseWeightsReshapeKernel _weights_reshape_kernel; |
| NEGEMMMatrixVectorMultiplyKernel _v2mm_kernel; |
| NEDepthwiseVectorToTensorKernel _vector_to_tensor_kernel; |
| NEDirectConvolutionLayerOutputStageKernel _output_stage_kernel; |
| NEFillBorderKernel _v2mm_input_fill_border; |
| NEFillBorderKernel _v2mm_weights_fill_border; |
| NEPermute _permute_input; |
| NEPermute _permute_weights; |
| NEPermute _permute_output; |
| NEActivationLayer _activationlayer_function; |
| Tensor _input_reshaped; |
| Tensor _weights_reshaped; |
| Tensor _v2mm_output; |
| Tensor _output_reshaped; |
| Tensor _permuted_input; |
| Tensor _permuted_weights; |
| Tensor _permuted_output; |
| bool _is_prepared; |
| bool _is_quantized; |
| bool _is_nhwc; |
| bool _is_activationlayer_enabled; |
| const ITensor *_original_weights; |
| }; |
| } // namespace arm_compute |
| #endif /* __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__ */ |