src/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.cpp - ml/ComputeLibrary - Gitiles

 /*
  * Copyright (c) 2019-2020 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.
  */
 #include "arm_compute/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.h"

 #include "arm_compute/core/CL/CLHelpers.h"
 #include "arm_compute/core/CL/CLKernelLibrary.h"
 #include "arm_compute/core/CL/ICLTensor.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/Validate.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
 #include "support/StringSupport.h"

 namespace arm_compute
 {
 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const ITensorInfo *input_info, const ITensorInfo *weights_info,
                           const PadStrideInfo &deconv_info)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output, input_info, weights_info);
     const DataLayout data_layout = input_info->data_layout();

     const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
     const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
     const size_t idx_b = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);

     const bool is_qasymm = is_data_type_quantized_asymmetric(input_info->data_type());

     ARM_COMPUTE_RETURN_ERROR_ON(weights_info->dimension(idx_w) != deconv_info.stride().first);
     ARM_COMPUTE_RETURN_ERROR_ON(weights_info->dimension(idx_h) != deconv_info.stride().second);

     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S32);
     if(!is_qasymm)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, input_info, weights_info);
     }
     ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) != weights_info->dimension(idx_w) * weights_info->dimension(idx_h) * weights_info->dimension(idx_b));
     ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) != input_info->dimension(idx_w));
     ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != input_info->dimension(idx_h));
     ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(3) != input_info->dimension(idx_b));

     if(bias != nullptr)
     {
         if(is_qasymm)
         {
             ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bias, 1, DataType::S32);
         }
         else
         {
             ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(bias, input);
         }
         ARM_COMPUTE_RETURN_ERROR_ON(bias->dimension(0) != weights_info->dimension(idx_b));
     }

     if(output->total_size() != 0)
     {
         const PadStrideInfo stride_info(deconv_info.stride().first, deconv_info.stride().second);
         auto                out_dims = deconvolution_output_dimensions(input_info->dimension(idx_w), input_info->dimension(idx_h), weights_info->dimension(idx_w), weights_info->dimension(idx_h), stride_info);

         const TensorShape output_shape = misc::shape_calculator::compute_deconvolution_output_shape(out_dims, *input_info, *weights_info);

         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
     }
     return Status{};
 }

 std::pair<Status, Window> validate_and_configure_window(const ITensorInfo *input, ITensorInfo *output, const ITensorInfo *input_info, const ITensorInfo *weights_info, const PadStrideInfo &deconv_info)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);

     const DataLayout    data_layout = input_info->data_layout();
     const size_t        idx_w       = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
     const size_t        idx_h       = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
     const PadStrideInfo stride_info(deconv_info.stride().first, deconv_info.stride().second);

     auto out_dims = deconvolution_output_dimensions(input_info->dimension(idx_w), input_info->dimension(idx_h), weights_info->dimension(idx_w), weights_info->dimension(idx_h), stride_info);

     const TensorShape output_shape = misc::shape_calculator::compute_deconvolution_output_shape(out_dims, *input_info, *weights_info);

     auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape).set_data_layout(data_layout).set_quantization_info(input->quantization_info()));

     Window win = calculate_max_window(*input);

     return std::make_pair(Status{}, win);
 }
 } // namespace

 CLDeconvolutionReshapeOutputKernel::CLDeconvolutionReshapeOutputKernel()
     : _add_bias(false),
       _bias(nullptr)
 {
 }

 void CLDeconvolutionReshapeOutputKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const ITensorInfo *input_info, const ITensorInfo *weights_info,
                                                    const PadStrideInfo &deconv_info)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, input_info, weights_info);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info(), input_info, weights_info, deconv_info));

     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info(), input_info, weights_info, deconv_info);
     ARM_COMPUTE_ERROR_THROW_ON(win_config.first);

     const DataLayout data_layout = input_info->data_layout();
     const size_t     idx_w       = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
     const size_t     idx_h       = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
     const size_t     idx_b       = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);

     _input    = input;
     _output   = output;
     _add_bias = (bias != nullptr);
     _bias     = bias;

     const int filter_w = weights_info->dimension(idx_w);
     const int filter_h = weights_info->dimension(idx_h);
     const int filter_b = weights_info->dimension(idx_b);
     const int img_w    = input_info->dimension(idx_w);
     const int img_h    = input_info->dimension(idx_h);

     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
     build_opts.add_option("-DFILTER_WIDTH=" + support::cpp11::to_string(filter_w));
     build_opts.add_option("-DFILTER_HEIGHT=" + support::cpp11::to_string(filter_h));
     build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(img_w));
     build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(img_h));
     build_opts.add_option_if(data_layout == DataLayout::NCHW, "-DNUM_FILTERS=" + support::cpp11::to_string(filter_b));
     build_opts.add_option_if(_add_bias, "-DADD_BIAS");

     _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("deconvolution_reshape", build_opts.options()));
     ICLKernel::configure_internal(win_config.second);

     // Set config_id for enabling LWS tuning
     _config_id = "deconvolution_reshape_output_";
     _config_id += lower_string(string_from_data_type(input->info()->data_type()));
     _config_id += "_";
     _config_id += lower_string(string_from_data_layout(input->info()->data_layout()));
     _config_id += "_";
     _config_id += support::cpp11::to_string(input->info()->dimension(0));
     _config_id += "_";
     _config_id += support::cpp11::to_string(input->info()->dimension(1));
     _config_id += "_";
     _config_id += support::cpp11::to_string(output->info()->dimension(0));
     _config_id += "_";
     _config_id += support::cpp11::to_string(output->info()->dimension(1));
 }

 Status CLDeconvolutionReshapeOutputKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const ITensorInfo *input_info, const ITensorInfo *weights_info,
                                                     const PadStrideInfo &deconv_info)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output, input_info, weights_info, deconv_info));
     return Status{};
 }

 void CLDeconvolutionReshapeOutputKernel::run(const Window &window, cl::CommandQueue &queue)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
     Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);

     unsigned int idx = 0;
     add_3D_tensor_argument(idx, _input, collapsed);
     add_3D_tensor_argument(idx, _output, collapsed);
     if(_add_bias)
     {
         add_1D_tensor_argument(idx, _bias, collapsed);
     }
     enqueue(queue, *this, collapsed, lws_hint());
 }
 } // namespace arm_compute
	/*
	* Copyright (c) 2019-2020 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.
	*/
	#include "arm_compute/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.h"

	#include "arm_compute/core/CL/CLHelpers.h"
	#include "arm_compute/core/CL/CLKernelLibrary.h"
	#include "arm_compute/core/CL/ICLTensor.h"
	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/Utils.h"
	#include "arm_compute/core/Validate.h"
	#include "arm_compute/core/utils/misc/ShapeCalculator.h"
	#include "support/StringSupport.h"

	namespace arm_compute
	{
	namespace
	{
	Status validate_arguments(const ITensorInfo input, const ITensorInfo bias, const ITensorInfo output, const ITensorInfo input_info, const ITensorInfo *weights_info,
	const PadStrideInfo &deconv_info)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output, input_info, weights_info);
	const DataLayout data_layout = input_info->data_layout();

	const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
	const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
	const size_t idx_b = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);

	const bool is_qasymm = is_data_type_quantized_asymmetric(input_info->data_type());

	ARM_COMPUTE_RETURN_ERROR_ON(weights_info->dimension(idx_w) != deconv_info.stride().first);
	ARM_COMPUTE_RETURN_ERROR_ON(weights_info->dimension(idx_h) != deconv_info.stride().second);

	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S32);
	if(!is_qasymm)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, input_info, weights_info);
	}
	ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) != weights_info->dimension(idx_w) * weights_info->dimension(idx_h) * weights_info->dimension(idx_b));
	ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) != input_info->dimension(idx_w));
	ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != input_info->dimension(idx_h));
	ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(3) != input_info->dimension(idx_b));

	if(bias != nullptr)
	{
	if(is_qasymm)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bias, 1, DataType::S32);
	}
	else
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(bias, input);
	}
	ARM_COMPUTE_RETURN_ERROR_ON(bias->dimension(0) != weights_info->dimension(idx_b));
	}

	if(output->total_size() != 0)
	{
	const PadStrideInfo stride_info(deconv_info.stride().first, deconv_info.stride().second);
	auto out_dims = deconvolution_output_dimensions(input_info->dimension(idx_w), input_info->dimension(idx_h), weights_info->dimension(idx_w), weights_info->dimension(idx_h), stride_info);

	const TensorShape output_shape = misc::shape_calculator::compute_deconvolution_output_shape(out_dims, input_info, weights_info);

	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
	}
	return Status{};
	}

	std::pair<Status, Window> validate_and_configure_window(const ITensorInfo input, ITensorInfo output, const ITensorInfo input_info, const ITensorInfo weights_info, const PadStrideInfo &deconv_info)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);

	const DataLayout data_layout = input_info->data_layout();
	const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
	const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
	const PadStrideInfo stride_info(deconv_info.stride().first, deconv_info.stride().second);

	auto out_dims = deconvolution_output_dimensions(input_info->dimension(idx_w), input_info->dimension(idx_h), weights_info->dimension(idx_w), weights_info->dimension(idx_h), stride_info);

	const TensorShape output_shape = misc::shape_calculator::compute_deconvolution_output_shape(out_dims, input_info, weights_info);

	auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape).set_data_layout(data_layout).set_quantization_info(input->quantization_info()));

	Window win = calculate_max_window(*input);

	return std::make_pair(Status{}, win);
	}
	} // namespace

	CLDeconvolutionReshapeOutputKernel::CLDeconvolutionReshapeOutputKernel()
	: _add_bias(false),
	_bias(nullptr)
	{
	}

	void CLDeconvolutionReshapeOutputKernel::configure(const ICLTensor input, const ICLTensor bias, ICLTensor output, const ITensorInfo input_info, const ITensorInfo *weights_info,
	const PadStrideInfo &deconv_info)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, input_info, weights_info);
	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info(), input_info, weights_info, deconv_info));

	// Configure kernel window
	auto win_config = validate_and_configure_window(input->info(), output->info(), input_info, weights_info, deconv_info);
	ARM_COMPUTE_ERROR_THROW_ON(win_config.first);

	const DataLayout data_layout = input_info->data_layout();
	const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
	const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
	const size_t idx_b = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);

	_input = input;
	_output = output;
	_add_bias = (bias != nullptr);
	_bias = bias;

	const int filter_w = weights_info->dimension(idx_w);
	const int filter_h = weights_info->dimension(idx_h);
	const int filter_b = weights_info->dimension(idx_b);
	const int img_w = input_info->dimension(idx_w);
	const int img_h = input_info->dimension(idx_h);

	CLBuildOptions build_opts;
	build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
	build_opts.add_option("-DFILTER_WIDTH=" + support::cpp11::to_string(filter_w));
	build_opts.add_option("-DFILTER_HEIGHT=" + support::cpp11::to_string(filter_h));
	build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(img_w));
	build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(img_h));
	build_opts.add_option_if(data_layout == DataLayout::NCHW, "-DNUM_FILTERS=" + support::cpp11::to_string(filter_b));
	build_opts.add_option_if(_add_bias, "-DADD_BIAS");

	_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("deconvolution_reshape", build_opts.options()));
	ICLKernel::configure_internal(win_config.second);

	// Set config_id for enabling LWS tuning
	_config_id = "deconvolution_reshape_output_";
	_config_id += lower_string(string_from_data_type(input->info()->data_type()));
	_config_id += "_";
	_config_id += lower_string(string_from_data_layout(input->info()->data_layout()));
	_config_id += "_";
	_config_id += support::cpp11::to_string(input->info()->dimension(0));
	_config_id += "_";
	_config_id += support::cpp11::to_string(input->info()->dimension(1));
	_config_id += "_";
	_config_id += support::cpp11::to_string(output->info()->dimension(0));
	_config_id += "_";
	_config_id += support::cpp11::to_string(output->info()->dimension(1));
	}

	Status CLDeconvolutionReshapeOutputKernel::validate(const ITensorInfo input, const ITensorInfo bias, const ITensorInfo output, const ITensorInfo input_info, const ITensorInfo *weights_info,
	const PadStrideInfo &deconv_info)
	{
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output, input_info, weights_info, deconv_info));
	return Status{};
	}

	void CLDeconvolutionReshapeOutputKernel::run(const Window &window, cl::CommandQueue &queue)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
	Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);

	unsigned int idx = 0;
	add_3D_tensor_argument(idx, _input, collapsed);
	add_3D_tensor_argument(idx, _output, collapsed);
	if(_add_bias)
	{
	add_1D_tensor_argument(idx, _bias, collapsed);
	}
	enqueue(queue, *this, collapsed, lws_hint());
	}
	} // namespace arm_compute