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/*
* Copyright (c) 2017-2022, 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_CLDECONVOLUTIONLAYER_H
#define ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLDECONVOLUTIONLAYER_H
#include "arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h"
#include "arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include <memory>
namespace arm_compute
{
/** Basic function to compute the deconvolution layer. This function calls the following OpenCL kernels/functions:
*
* -# @ref CLGEMMDeconvolutionLayer
* -# @ref CLDirectDeconvolutionLayer
*/
class CLDeconvolutionLayer : public IFunction
{
public:
/** Default constructor */
CLDeconvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
~CLDeconvolutionLayer();
/** Set the input, weights, biases 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,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
* @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
* @param[in] bias (Optional) The biases have one dimension. Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
* @param[out] output Output tensor. The output has the same number of dimensions as the @p input.
* @param[in] deconv_info Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo.
* @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with opencl::kernels::ClWeightsReshapeKernel.
*
*/
void configure(ICLTensor *input,
ICLTensor *weights,
const ICLTensor *bias,
ICLTensor *output,
const PadStrideInfo &deconv_info,
const WeightsInfo &weights_info = WeightsInfo());
/** Set the input, weights, biases and output tensors.
*
* @param[in] compile_context The compile context to be used.
* @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
* @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
* @param[in] bias (Optional) The biases have one dimension. Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
* @param[out] output Output tensor. The output has the same number of dimensions as the @p input.
* @param[in] deconv_info Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo.
* @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with opencl::kernels::ClWeightsReshapeKernel.
*
*/
void configure(const CLCompileContext &compile_context,
ICLTensor *input,
ICLTensor *weights,
const ICLTensor *bias,
ICLTensor *output,
const PadStrideInfo &deconv_info,
const WeightsInfo &weights_info = WeightsInfo());
/** Static function to check if given info will lead to a valid configuration of @ref CLDeconvolutionLayer
*
* @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
* @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
* @param[in] bias (Optional) The biases have one dimension. Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
* @param[in] output Output tensor info. The output has the same number of dimensions as the @p input.
* @param[in] deconv_info Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo.
* @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with opencl::kernels::ClWeightsReshapeKernel.
*
* @return a status
*/
static Status validate(const ITensorInfo *input,
const ITensorInfo *weights,
const ITensorInfo *bias,
ITensorInfo *output,
const PadStrideInfo &deconv_info,
const WeightsInfo &weights_info = WeightsInfo());
static DeconvolutionMethod get_deconvolution_method(const ITensorInfo *input,
const ITensorInfo *weights,
const ITensorInfo *bias,
ITensorInfo *output,
const PadStrideInfo &deconv_info,
const WeightsInfo &weights_info);
// Inherited methods overridden:
void run() override;
void prepare() override;
private:
std::shared_ptr<IMemoryManager> _memory_manager;
std::unique_ptr<IFunction> _function;
struct Impl;
std::unique_ptr<Impl> _impl;
};
} // namespace arm_compute
#endif // ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLDECONVOLUTIONLAYER_H
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