/* * 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_CLDEPTHWISECONVOLUTION_H #define ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H #include "arm_compute/core/Types.h" #include "arm_compute/runtime/CL/CLTensor.h" #include "arm_compute/runtime/CL/functions/CLPermute.h" #include "arm_compute/runtime/IFunction.h" #include "arm_compute/runtime/MemoryGroup.h" namespace arm_compute { class CLCompileContext; class CLFillBorderKernel; class CLDepthwiseConvolutionLayerNativeKernel; class CLDepthwiseConvolutionLayer3x3NCHWKernel; class CLDepthwiseConvolutionLayer3x3NHWCKernel; class ICLTensor; /** Function to execute a depthwise convolution */ class CLDepthwiseConvolutionLayer : public IFunction { public: /** Default constructor */ CLDepthwiseConvolutionLayer(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ CLDepthwiseConvolutionLayer(const CLDepthwiseConvolutionLayer &) = delete; /** Default move constructor */ CLDepthwiseConvolutionLayer(CLDepthwiseConvolutionLayer &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ CLDepthwiseConvolutionLayer &operator=(const CLDepthwiseConvolutionLayer &) = delete; /** Default move assignment operator */ CLDepthwiseConvolutionLayer &operator=(CLDepthwiseConvolutionLayer &&) = default; /** Default destructor */ ~CLDepthwiseConvolutionLayer(); /** Initialize the function's source, destination, weights and convolution information. * * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/FP16/FP32. Data layout supported: NHWC, NCHW * @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. * @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(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); /** Initialize the function's source, destination, weights and convolution information. * * @param[in] compile_context The compile context to be used. * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/FP16/FP32. Data layout supported: NHWC, NCHW * @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. * @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(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, 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 CLDepthwiseConvolutionLayer * * @param[in] input Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/FP16/FP32. Data layout supported: NHWC, NCHW * @param[in] weights Weights tensor info. 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. * @param[in] biases Biases tensor info. 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. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. * @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, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); // Inherited methods overriden: void run() override; void prepare() override; private: /** Static function to choose the best depthwise convolution function for @ref CLDepthwiseConvolutionLayer * * @param[in] input Source tensor info. Data type supported: QASYMM8/FP16/FP32. Data layout supported: NHWC, NCHW * @param[in] weights Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. * @param[in] biases Biases tensor info. 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] 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. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * * @return a Depthwise Convolution Function */ static DepthwiseConvolutionFunction get_depthwiseconvolution_function(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); /** Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC). This function calls the following OpenCL kernels: * * -# @ref CLDepthwiseConvolutionLayer3x3NCHWKernel (if data_layout == NCHW) * -# @ref CLDepthwiseConvolutionLayer3x3NHWCKernel (if data_layout == NHWC) * -# @ref CLFillBorderKernel (if pad_x or pad_y > 0) * */ class CLDepthwiseConvolutionLayerInternal3x3 : public IFunction { public: /** Default constructor */ CLDepthwiseConvolutionLayerInternal3x3(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ CLDepthwiseConvolutionLayerInternal3x3(const CLDepthwiseConvolutionLayerInternal3x3 &) = delete; /** Default move constructor */ CLDepthwiseConvolutionLayerInternal3x3(CLDepthwiseConvolutionLayerInternal3x3 &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ CLDepthwiseConvolutionLayerInternal3x3 &operator=(const CLDepthwiseConvolutionLayerInternal3x3 &) = delete; /** Default move assignment operator */ CLDepthwiseConvolutionLayerInternal3x3 &operator=(CLDepthwiseConvolutionLayerInternal3x3 &&) = default; /** Initialize the function's source, destination, conv 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. A 3D tensor with shape [3, 3, IFM]. * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. * @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. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). */ void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); /** Initialize the function's source, destination, conv and border_size. * * @param[in] compile_context The compile context to be used. * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). * @param[in] weights Weights tensor. A 3D tensor with shape [3, 3, IFM]. * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. * @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. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). */ void configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, 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 CLDepthwiseConvolutionLayer3x3 * * @param[in] input Source tensor info. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW. * @param[in] weights Weights tensor info. A 3D tensor with shape [3, 3, IFM]. * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. * @param[in] biases Biases tensor info. 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] 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. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. * @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, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); // Inherited methods overriden: void run() override; void prepare() override; void set_memory_group(std::shared_ptr memory_manager) { _memory_group = MemoryGroup(std::move(memory_manager)); }; private: MemoryGroup _memory_group; std::unique_ptr _kernel_nchw; std::unique_ptr _kernel_nhwc; std::unique_ptr _border_handler; CLPermute _permute_input_to_nchw; CLPermute _permute_weights_to_nchw; CLPermute _permute_output_to_nhwc; CLTensor _permuted_input; CLTensor _permuted_weights; CLTensor _permuted_output; CLTensor _output_multipliers; CLTensor _output_shifts; const ITensor *_original_weights; const ITensor *_input; const ITensor *_output; bool _needs_permute; bool _is_prepared; bool _is_quantized; bool _is_nhwc; }; /** Basic function to execute a generic depthwise convolution. This function calls the following OpenCL kernels: * * -# @ref CLDepthwiseConvolutionLayerNativeKernel * -# @ref CLPermute (x 3) if the data layout is NCHW * */ class CLDepthwiseConvolutionLayerGeneric : public IFunction { public: /** Default constructor */ CLDepthwiseConvolutionLayerGeneric(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ CLDepthwiseConvolutionLayerGeneric(const CLDepthwiseConvolutionLayerGeneric &) = delete; /** Default move constructor */ CLDepthwiseConvolutionLayerGeneric(CLDepthwiseConvolutionLayerGeneric &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ CLDepthwiseConvolutionLayerGeneric &operator=(const CLDepthwiseConvolutionLayerGeneric &) = delete; /** Default move assignment operator */ CLDepthwiseConvolutionLayerGeneric &operator=(CLDepthwiseConvolutionLayerGeneric &&) = default; /** Initialize the function's source, destination, weights and convolution information. * * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/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 or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8. * @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(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); /** Initialize the function's source, destination, weights and convolution information. * * @param[in] compile_context The compile context to be used. * @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/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 or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8. * @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(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *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 CLDepthwiseConvolutionLayerGeneric * * @param[in] input Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/F32. * @param[in] weights Weights tensor info. 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. * @param[in] biases Biases tensor info. 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; void set_memory_group(std::shared_ptr memory_manager) { _memory_group = MemoryGroup(std::move(memory_manager)); }; private: MemoryGroup _memory_group; std::unique_ptr _dwc_native_kernel; CLPermute _permute_input_to_nhwc; CLPermute _permute_weights_to_nhwc; CLPermute _permute_output_to_nchw; CLTensor _permuted_input; CLTensor _permuted_weights; CLTensor _permuted_output; CLTensor _output_multipliers; CLTensor _output_shifts; const ITensor *_original_weights; const ITensor *_input; const ITensor *_output; bool _needs_permute; bool _is_prepared; bool _is_quantized; }; std::shared_ptr _memory_manager; DepthwiseConvolutionFunction _depth_conv_func; CLDepthwiseConvolutionLayerInternal3x3 _func_3x3; CLDepthwiseConvolutionLayerGeneric _func_generic; }; } // namespace arm_compute #endif /*ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H */