/* * Copyright (c) 2017-2021 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/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 namespace arm_compute { // Forward declarations class ITensor; class NEDepthwiseConvolutionLayerNativeKernel; /** Function to execute a depthwise convolution. */ class NEDepthwiseConvolutionLayer : public IFunction { public: /** Default constructor */ NEDepthwiseConvolutionLayer(std::shared_ptr memory_manager = nullptr); /** 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; /** Default destructor */ ~NEDepthwiseConvolutionLayer(); /** Initialize the function's source, destination, weights and convolution information. * * 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 |QSYMM8_PER_CHANNEL |S32 |QASYMM8 | * |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED | * |QASYMM8_SIGNED |QSYMM8_PER_CHANNEL |S32 |QASYMM8_SIGNED | * * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32 * @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 or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED. * @param[in] biases 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/QASYMM8_SIGNED. * @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/QASYMM8_SIGNED/F16/F32 * @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 or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED. * @param[in] biases 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/QASYMM8_SIGNED. * @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: /** Basic function to execute optimized depthwise convolution routines. This function calls the following 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 cpu::CpuDepthwiseConvolutionAssemblyDispatch if assembly kernel implementation is present * -# @ref NEDirectConvolutionLayerOutputStageKernel if re-quantization of output is required * -# @ref NEActivationLayer if fused activation is required * */ class NEDepthwiseConvolutionLayerOptimizedInternal : public IFunction { public: /** Default constructor */ NEDepthwiseConvolutionLayerOptimizedInternal(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ NEDepthwiseConvolutionLayerOptimizedInternal(const NEDepthwiseConvolutionLayerOptimizedInternal &) = delete; /** Default move constructor */ NEDepthwiseConvolutionLayerOptimizedInternal(NEDepthwiseConvolutionLayerOptimizedInternal &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ NEDepthwiseConvolutionLayerOptimizedInternal &operator=(const NEDepthwiseConvolutionLayerOptimizedInternal &) = delete; /** Default move assignment operator */ NEDepthwiseConvolutionLayerOptimizedInternal &operator=(NEDepthwiseConvolutionLayerOptimizedInternal &&) = default; /** Default destructor */ ~NEDepthwiseConvolutionLayerOptimizedInternal() = default; /** Initialize the function's source, destination, kernels and border_size. * * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. (Written to only for border filling). * @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 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/QASYMM8_SIGNED. * @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/QASYMM8_SIGNED/F16/F32. (Written to only for border filling). * @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 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/QASYMM8_SIGNED. * @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: MemoryGroup _memory_group; struct Impl; std::unique_ptr _impl; }; /** Basic function to execute a generic depthwise convolution. This function calls the following kernel: * * -# @ref NEDepthwiseConvolutionLayerNativeKernel * */ class NEDepthwiseConvolutionLayerGeneric : public IFunction { public: /** Default constructor */ NEDepthwiseConvolutionLayerGeneric(); /** Prevent instances of this class from being copied (As this class contains pointers) */ NEDepthwiseConvolutionLayerGeneric(const NEDepthwiseConvolutionLayerGeneric &) = delete; /** Default move constructor */ NEDepthwiseConvolutionLayerGeneric(NEDepthwiseConvolutionLayerGeneric &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ NEDepthwiseConvolutionLayerGeneric &operator=(const NEDepthwiseConvolutionLayerGeneric &) = delete; /** Default move assignment operator */ NEDepthwiseConvolutionLayerGeneric &operator=(NEDepthwiseConvolutionLayerGeneric &&) = default; /** Default destructor */ ~NEDepthwiseConvolutionLayerGeneric() = default; /** Initialize the function's source, destination, weights and convolution information. * * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/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 or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED. * @param[in] biases 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/QASYMM8_SIGNED. * @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 NEDepthwiseConvolutionLayerGeneric * * @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/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 or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED. * @param[in] biases 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/QASYMM8_SIGNED. * @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; private: struct Impl; std::unique_ptr _impl; }; MemoryGroup _memory_group; struct Impl; std::unique_ptr _impl; }; } // namespace arm_compute #endif /* ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H */