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161 lines
11 KiB
161 lines
11 KiB
/*
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* Copyright (c) 2017-2021 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_CLGEMMCONVOLUTIONLAYER_H
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#define ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H
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#include "arm_compute/core/experimental/IPostOp.h"
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#include "arm_compute/runtime/CL/CLTensor.h"
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#include "arm_compute/runtime/CL/CLTypes.h"
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#include "arm_compute/runtime/IFunction.h"
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#include "arm_compute/runtime/IMemoryManager.h"
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#include "arm_compute/runtime/IWeightsManager.h"
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#include <memory>
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namespace arm_compute
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{
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// Forward declarations
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class CLCompileContext;
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class ICLTensor;
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class ITensorInfo;
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/** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions:
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*
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* -# @ref opencl::ClGemmConv2d
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*/
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class CLGEMMConvolutionLayer : public IFunction
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{
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public:
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/** Constructor
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*
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* @param[in] memory_manager (Optional) Memory manager.
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* @param[in] weights_manager (Optional) Weights manager.
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*/
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CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr, IWeightsManager *weights_manager = nullptr);
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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CLGEMMConvolutionLayer(const CLGEMMConvolutionLayer &) = delete;
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/** Default move constructor */
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CLGEMMConvolutionLayer(CLGEMMConvolutionLayer &&) = default;
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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CLGEMMConvolutionLayer &operator=(const CLGEMMConvolutionLayer &) = delete;
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/** Default move assignment operator */
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CLGEMMConvolutionLayer &operator=(CLGEMMConvolutionLayer &&) = default;
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/**Default destructor */
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~CLGEMMConvolutionLayer();
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/** Set the input and output tensors.
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*
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* Valid data layouts:
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* - NHWC
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* - NCHW
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*
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* Valid data type configurations:
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* |src0 |src1 |src2 |dst |
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* |:--------------|:------------------|:--------|:--------------|
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* |F16 |F16 |F16 |F16 |
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* |F32 |F32 |F32 |F32 |
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* |QASYMM8 |QASYMM8 |S32 |QASYMM8 |
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* |QASYMM8 |QSYMM8_PER_CHANNEL |S32 |QASYMM8 |
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* |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED |
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* |QASYMM8_SIGNED |QSYMM8_PER_CHANNEL |S32 |QASYMM8_SIGNED |
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*
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* @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
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* while every optional dimension from 4 and above represent a batch of inputs.
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* Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
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* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
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* Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
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* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
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* Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
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* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
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* Data types supported: Same as @p input.
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* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
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* @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
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* tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
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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] act_info (Optional) Activation layer information in case of a fused activation.
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* @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
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* @param[in] post_ops (Optional) A sequence of post operations that are performed after the main operation.
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*/
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void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo(),
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const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1,
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const experimental::PostOpList<ICLTensor *> &post_ops = experimental::PostOpList<ICLTensor *> {});
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/** Set the input and output tensors.
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*
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* @param[in] compile_context The compile context to be used.
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* @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
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* while every optional dimension from 4 and above represent a batch of inputs.
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* Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
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* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
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* Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
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* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
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* Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
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* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
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* Data types supported: Same as @p input.
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* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
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* @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
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* tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
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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] act_info (Optional) Activation layer information in case of a fused activation.
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* @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
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* @param[in] post_ops (Optional) A sequence of post operations that are performed after the main operation.
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*/
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void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
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const WeightsInfo &weights_info = WeightsInfo(),
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const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1,
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const experimental::PostOpList<ICLTensor *> &post_ops = experimental::PostOpList<ICLTensor *> {});
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/** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer.
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*
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* @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
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* while every optional dimension from 4 and above represent a batch of inputs.
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* Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
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* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
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* Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
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* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
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* Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
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* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
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* Data types supported: Same as @p input.
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* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
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* @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
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* tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
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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] act_info (Optional) Activation layer information in case of a fused activation.
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* @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
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* @param[in] post_ops (Optional) A sequence of post operations that are performed after the main operation.
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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,
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const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1,
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const experimental::PostOpList<ITensorInfo *> &post_ops = experimental::PostOpList<ITensorInfo *> {});
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// Inherited methods overridden:
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void run() override;
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void prepare() override;
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private:
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struct Impl;
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std::unique_ptr<Impl> _impl;
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};
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} // namespace arm_compute
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#endif /* ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H */
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