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/*
* Copyright (c) 2017-2021, 2023-2024 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 ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLGEMMCONVOLUTIONLAYER_H
#define ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLGEMMCONVOLUTIONLAYER_H
#include "arm_compute/function_info/ActivationLayerInfo.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/CLTypes.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include "arm_compute/runtime/IWeightsManager.h"
#include <memory>
namespace arm_compute
{
// Forward declarations
class CLCompileContext;
class ICLTensor;
class ITensorInfo;
/** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions:
*
* -# opencl::ClGemmConv2d
*/
class CLGEMMConvolutionLayer : public IFunction
{
public:
/** Constructor
*
* @param[in] memory_manager (Optional) Memory manager.
* @param[in] weights_manager (Optional) Weights manager.
*/
CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr,
IWeightsManager *weights_manager = nullptr);
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMMConvolutionLayer(const CLGEMMConvolutionLayer &) = delete;
/** Default move constructor */
CLGEMMConvolutionLayer(CLGEMMConvolutionLayer &&) = default;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMMConvolutionLayer &operator=(const CLGEMMConvolutionLayer &) = delete;
/** Default move assignment operator */
CLGEMMConvolutionLayer &operator=(CLGEMMConvolutionLayer &&) = default;
/**Default destructor */
~CLGEMMConvolutionLayer();
/** Set the input and output tensors.
*
* 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] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
* while every optional dimension from 4 and above represent a batch of inputs.
* Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
* 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.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
* Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @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
* tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
* @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
*/
void configure(const ICLTensor *input,
const ICLTensor *weights,
const ICLTensor *biases,
ICLTensor *output,
const PadStrideInfo &conv_info,
const WeightsInfo &weights_info = WeightsInfo(),
const Size2D &dilation = Size2D(1U, 1U),
const ActivationLayerInfo &act_info = ActivationLayerInfo(),
unsigned int num_groups = 1);
/** Set the input and output tensors.
*
* @param[in] compile_context The compile context to be used.
* @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
* while every optional dimension from 4 and above represent a batch of inputs.
* Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
* 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.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
* Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @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
* tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
* @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
*/
void configure(const CLCompileContext &compile_context,
const ICLTensor *input,
const ICLTensor *weights,
const ICLTensor *biases,
ICLTensor *output,
const PadStrideInfo &conv_info,
const WeightsInfo &weights_info = WeightsInfo(),
const Size2D &dilation = Size2D(1U, 1U),
const ActivationLayerInfo &act_info = ActivationLayerInfo(),
unsigned int num_groups = 1);
/** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer.
*
* @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
* while every optional dimension from 4 and above represent a batch of inputs.
* Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
* 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.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
* Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @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
* tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
* @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
*
* @return a status
*/
static Status validate(const ITensorInfo *input,
const ITensorInfo *weights,
const ITensorInfo *biases,
const ITensorInfo *output,
const PadStrideInfo &conv_info,
const WeightsInfo &weights_info = WeightsInfo(),
const Size2D &dilation = Size2D(1U, 1U),
const ActivationLayerInfo &act_info = ActivationLayerInfo(),
unsigned int num_groups = 1);
// Inherited methods overridden:
void run() override;
void prepare() override;
private:
struct Impl;
std::unique_ptr<Impl> _impl;
};
} // namespace arm_compute
#endif // ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLGEMMCONVOLUTIONLAYER_H
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