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/*
* Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/*
* Copyright (c) 2017-2020 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_CLTRANSPOSECONVLAYER_H__
#define __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__
#include "arm_compute/runtime/CL/functions/CLDirectTransposeConvLayer.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 CLDirectTransposeConvLayer
*/
class CLTransposeConvLayer : public IFunction
{
public:
/** Default constructor */
CLTransposeConvLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Set the input, weights, biases and output tensors.
*
* @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.
* @param[in] bias (Optional) The biases have one dimension. Data type supported: Same
* as @p input.
* @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] invalid_right The number of zeros added to right edge of the output.
* @param[in] invalid_bottom The number of zeros added to bottom edge of the output.
* @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer,
* specifies if the weights tensor has been reshaped with @ref CLWeightsReshapeKernel.
*
*/
void configure(ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output,
const PadStrideInfo &deconv_info, unsigned int invalid_right,
unsigned int invalid_bottom, 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.
* @param[in] bias (Optional) The biases have one dimension. Data type supported:
* Same as @p input.
* @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] invalid_right The number of zeros added to right edge of the output.
* @param[in] invalid_bottom The number of zeros added to bottom edge of the output.
* @param[in] weights_info (Optional) Weights information needed for @ref
* CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref
* CLWeightsReshapeKernel.
*
*/
void configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *weights,
const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &deconv_info,
unsigned int invalid_right, unsigned int invalid_bottom,
const WeightsInfo &weights_info = WeightsInfo());
/** Static function to check if given info will lead to a valid configuration of @ref
* CLTransposeConvLayer
*
* @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.
* @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as
* @p input.
* @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] invalid_right The number of zeros added to right edge of the output.
* @param[in] invalid_bottom The number of zeros added to bottom edge of the output.
* @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer,
* specifies if the weights tensor has been reshaped with @ref CLWeightsReshapeKernel.
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *weights,
const ITensorInfo *bias, ITensorInfo *output,
const PadStrideInfo &deconv_info, unsigned int invalid_right,
unsigned int invalid_bottom,
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, unsigned int invalid_right,
unsigned int invalid_bottom, 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;
};
} // namespace arm_compute
#endif /* __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__ */
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