344 lines
26 KiB
C
344 lines
26 KiB
C
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/*
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* Copyright (c) 2017-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#ifndef ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H
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#define ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H
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#include "arm_compute/core/Types.h"
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#include "arm_compute/runtime/CL/CLTensor.h"
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#include "arm_compute/runtime/CL/functions/CLPermute.h"
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#include "arm_compute/runtime/IFunction.h"
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#include "arm_compute/runtime/MemoryGroup.h"
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namespace arm_compute
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{
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class CLCompileContext;
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class CLFillBorderKernel;
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class CLDepthwiseConvolutionLayerNativeKernel;
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class CLDepthwiseConvolutionLayerReshapeWeightsKernel;
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class ICLDepthwiseConvolutionLayer3x3Kernel;
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class ICLTensor;
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/** Function to execute a depthwise convolution
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*/
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class CLDepthwiseConvolutionLayer : public IFunction
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{
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public:
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/** Default constructor */
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CLDepthwiseConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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CLDepthwiseConvolutionLayer(const CLDepthwiseConvolutionLayer &) = delete;
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/** Default move constructor */
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CLDepthwiseConvolutionLayer(CLDepthwiseConvolutionLayer &&) = default;
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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CLDepthwiseConvolutionLayer &operator=(const CLDepthwiseConvolutionLayer &) = delete;
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/** Default move assignment operator */
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CLDepthwiseConvolutionLayer &operator=(CLDepthwiseConvolutionLayer &&) = default;
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/** Default destructor */
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~CLDepthwiseConvolutionLayer();
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/** Initialize the function's source, destination, weights and convolution information.
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*
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* @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/FP16/FP32. Data layout supported: NHWC, NCHW
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* @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM].
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* Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
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* @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
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* Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.
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* @param[out] output Destination tensor. Data type supported: same as @p input.
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* @param[in] conv_info Padding and stride information to use for the convolution.
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* @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
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* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
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* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
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*/
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void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
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ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
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/** Initialize the function's source, destination, weights and convolution information.
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*
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* @param[in] compile_context The compile context to be used.
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* @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/FP16/FP32. Data layout supported: NHWC, NCHW
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* @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM].
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* Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
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* @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
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* Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.
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* @param[out] output Destination tensor. Data type supported: same as @p input.
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* @param[in] conv_info Padding and stride information to use for the convolution.
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* @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
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* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
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* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
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*/
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void configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
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unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
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/** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer
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*
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* @param[in] input Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/FP16/FP32. Data layout supported: NHWC, NCHW
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* @param[in] weights Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM].
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* Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
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* @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
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* Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.
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* @param[in] output Destination tensor. Data type supported: same as @p input.
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* @param[in] conv_info Padding and stride information to use for the convolution.
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* @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
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* @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.
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* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
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*
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* @return a status
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*/
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static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
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ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
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// Inherited methods overriden:
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void run() override;
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void prepare() override;
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private:
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/** Static function to choose the best depthwise convolution function for @ref CLDepthwiseConvolutionLayer
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*
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* @param[in] input Source tensor info. Data type supported: QASYMM8/FP16/FP32. Data layout supported: NHWC, NCHW
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* @param[in] weights Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM].
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* Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
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* @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
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* Data type supported: Same as @p input, S32 when input is QASYMM8.
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* @param[in] output Destination tensor. Data type supported: same as @p input.
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* @param[in] conv_info Padding and stride information to use for the convolution.
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* @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
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* @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.
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* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
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* @param[in] gpu_target (Optional) GPU target to validate the kernel for. Defaults to midgard.
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*
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* @return a Depthwise Convolution Function
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*/
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static DepthwiseConvolutionFunction get_depthwiseconvolution_function(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output,
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const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
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ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U), GPUTarget gpu_target = GPUTarget::MIDGARD);
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/** 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:
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*
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* -# @ref CLDepthwiseConvolutionLayer3x3NCHWKernel (if data_layout == NCHW)
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* -# @ref CLDepthwiseConvolutionLayer3x3NHWCKernel (if data_layout == NHWC)
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* -# @ref CLDepthwiseConvolutionLayerReshapeWeightsKernel (if data_layout == NHWC)
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* -# @ref CLFillBorderKernel (if pad_x or pad_y > 0)
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*
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*/
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class CLDepthwiseConvolutionLayerInternal3x3 : public IFunction
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{
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public:
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/** Default constructor */
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CLDepthwiseConvolutionLayerInternal3x3(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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CLDepthwiseConvolutionLayerInternal3x3(const CLDepthwiseConvolutionLayerInternal3x3 &) = delete;
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/** Default move constructor */
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CLDepthwiseConvolutionLayerInternal3x3(CLDepthwiseConvolutionLayerInternal3x3 &&) = default;
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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CLDepthwiseConvolutionLayerInternal3x3 &operator=(const CLDepthwiseConvolutionLayerInternal3x3 &) = delete;
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/** Default move assignment operator */
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CLDepthwiseConvolutionLayerInternal3x3 &operator=(CLDepthwiseConvolutionLayerInternal3x3 &&) = default;
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/** Initialize the function's source, destination, conv and border_size.
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*
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* @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
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* @param[in] weights Weights tensor. A 3D tensor with shape [3, 3, IFM].
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* Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
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* @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
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* Data type supported: Same as @p input.
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* @param[out] output Destination tensor. Data type supported: same as @p input.
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* @param[in] conv_info Padding and stride information to use for the convolution.
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* @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
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* @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.
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* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
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*/
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void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
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ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
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/** Initialize the function's source, destination, conv and border_size.
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*
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* @param[in] compile_context The compile context to be used.
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* @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
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* @param[in] weights Weights tensor. A 3D tensor with shape [3, 3, IFM].
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* Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
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* @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
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* Data type supported: Same as @p input.
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* @param[out] output Destination tensor. Data type supported: same as @p input.
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* @param[in] conv_info Padding and stride information to use for the convolution.
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* @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
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* @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.
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* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
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*/
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void configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
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unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
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/** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3
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*
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* @param[in] input Source tensor info. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW.
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* @param[in] weights Weights tensor info. A 3D tensor with shape [3, 3, IFM].
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* Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
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* @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
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* Data type supported: Same as @p input, S32 when input is QASYMM8.
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* @param[in] output Destination tensor. Data type supported: same as @p input.
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* @param[in] conv_info Padding and stride information to use for the convolution.
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* @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
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* @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.
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* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
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*
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* @return a status
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*/
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static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
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ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD, const Size2D &dilation = Size2D(1U, 1U));
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// Inherited methods overriden:
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void run() override;
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void prepare() override;
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void set_memory_group(std::shared_ptr<IMemoryManager> memory_manager)
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{
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_memory_group = MemoryGroup(std::move(memory_manager));
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};
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private:
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MemoryGroup _memory_group;
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std::unique_ptr<ICLDepthwiseConvolutionLayer3x3Kernel> _kernel;
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std::unique_ptr<CLFillBorderKernel> _border_handler;
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CLPermute _permute_input_to_nchw;
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CLPermute _permute_weights_to_nchw;
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CLPermute _permute_output_to_nhwc;
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std::unique_ptr<CLDepthwiseConvolutionLayerReshapeWeightsKernel> _reshape_weights;
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CLTensor _permuted_input;
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CLTensor _permuted_weights;
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CLTensor _permuted_output;
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CLTensor _output_multipliers;
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CLTensor _output_shifts;
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const ITensor *_original_weights;
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const ITensor *_input;
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const ITensor *_output;
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bool _needs_permute;
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bool _needs_weights_reshape;
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bool _is_prepared;
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bool _is_quantized;
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};
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/** Basic function to execute a generic depthwise convolution. This function calls the following OpenCL kernels:
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*
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* -# @ref CLDepthwiseConvolutionLayerNativeKernel
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* -# @ref CLPermute (x 3) if the data layout is NCHW
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*
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*/
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class CLDepthwiseConvolutionLayerGeneric : public IFunction
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{
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public:
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/** Default constructor */
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CLDepthwiseConvolutionLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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CLDepthwiseConvolutionLayerGeneric(const CLDepthwiseConvolutionLayerGeneric &) = delete;
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/** Default move constructor */
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CLDepthwiseConvolutionLayerGeneric(CLDepthwiseConvolutionLayerGeneric &&) = default;
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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CLDepthwiseConvolutionLayerGeneric &operator=(const CLDepthwiseConvolutionLayerGeneric &) = delete;
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/** Default move assignment operator */
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CLDepthwiseConvolutionLayerGeneric &operator=(CLDepthwiseConvolutionLayerGeneric &&) = default;
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/** Initialize the function's source, destination, weights and convolution information.
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*
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* @param[in, out] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F32. (Written to only for border filling).
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* @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<IMemoryManager> memory_manager)
|
||
|
|
{
|
||
|
|
_memory_group = MemoryGroup(std::move(memory_manager));
|
||
|
|
};
|
||
|
|
|
||
|
|
private:
|
||
|
|
MemoryGroup _memory_group;
|
||
|
|
|
||
|
|
std::unique_ptr<CLDepthwiseConvolutionLayerNativeKernel> _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<IMemoryManager> _memory_manager;
|
||
|
|
|
||
|
|
DepthwiseConvolutionFunction _depth_conv_func;
|
||
|
|
CLDepthwiseConvolutionLayerInternal3x3 _func_3x3;
|
||
|
|
CLDepthwiseConvolutionLayerGeneric _func_generic;
|
||
|
|
};
|
||
|
|
} // namespace arm_compute
|
||
|
|
#endif /*ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H */
|