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

 /*
  * Copyright (c) 2019-2021, 2023 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 "src/core/CL/kernels/CLInstanceNormalizationLayerKernel.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/TensorInfo.h"
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/utils/StringUtils.h"
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "support/StringSupport.h"

 namespace arm_compute
 {
 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const InstanceNormalizationLayerKernelInfo &info)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.epsilon == 0.f, "Epsilon must be different than 0");
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);

     if(output != nullptr && output->total_size() != 0)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(), "Input and output have different number of channels");
     }

     return Status{};
 }

 Status validate_arguments_meanvar(const ITensorInfo *input, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);

     if(output != nullptr && output->total_size() != 0)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(), "Input and output have different number of channels");
     }

     return Status{};
 }
 } // namespace

 CLComputeMeanVariance::CLComputeMeanVariance()
     : _input(nullptr), _output(nullptr)
 {
     _type = CLKernelType::ELEMENTWISE;
 }

 void CLComputeMeanVariance::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, bool use_mixed_precision)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input);
     auto padding_info = get_padding_info({ input, output });

     _input  = input;
     _output = output == nullptr ? input : output;

     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_meanvar(_input->info(), _output->info()));
     const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();

     CLBuildOptions build_opts;
     build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
     build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
     build_opts.add_option("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0)));
     build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1)));
     build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2)));
     build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");
     // Create kernel
     _kernel = create_kernel(compile_context, "compute_mean_var", build_opts.options());

     // We handle the planes manually
     Window             win           = calculate_max_window(*(input->info()), Steps(1));
     const auto         data_layout   = input->info()->data_layout();
     const unsigned int channel_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
     const unsigned int batches_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
     const unsigned int input_channel = input->info()->dimension(channel_idx);
     const unsigned int input_batches = input->info()->dimension(batches_idx);
     const TensorShape  out_shape(input_channel, 2u, input_batches);

     // Output auto initialization if not yet initialized
     if(use_mixed_precision)
     {
         auto_init_if_empty(*_output->info(), out_shape, 1, DataType::F32);
     }
     else
     {
         auto_init_if_empty(*_output->info(), out_shape, 1, input->info()->data_type());
     }
     ICLKernel::configure_internal(win);
     ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
 }

 Status CLComputeMeanVariance::validate(const ITensorInfo *input, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_meanvar(input, output));
     return Status{};
 }

 void CLComputeMeanVariance::run(const Window &window, cl::CommandQueue &queue)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

     Window collapsed_window = window.collapse(window, Window::DimZ);

     // We will process the planes together
     if(_input->info()->data_layout() == DataLayout::NCHW)
     {
         collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1));
         collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
     }
     else
     {
         collapsed_window.set(Window::DimZ, Window::Dimension(0, 1, 1));
         collapsed_window.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(3), 1));
     }
     unsigned int idx = 0;
     add_4D_tensor_argument(idx, _input, collapsed_window);
     add_3D_tensor_argument(idx, _output, collapsed_window);

     enqueue(queue, *this, collapsed_window, lws_hint());
 }

 CLInstanceNormalizationLayerKernel::CLInstanceNormalizationLayerKernel()
     : _input(nullptr), _output(nullptr), _mean(nullptr), _run_in_place(false)
 {
     _type = CLKernelType::ELEMENTWISE;
 }

 void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *mean_var, ICLTensor *output, const InstanceNormalizationLayerKernelInfo &info)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input);
     auto padding_info = get_padding_info({ input, output });

     _input  = input;
     _output = output == nullptr ? input : output;
     _mean   = mean_var;

     _run_in_place = (output == nullptr) || (output == input);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(_input->info(), _output->info(), info));
     const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();

     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
     build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (info.use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
     build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
     build_opts.add_option("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0)));
     build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1)));
     build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2)));
     build_opts.add_option("-DGAMMA=" + float_to_string_with_full_precision(info.gamma));
     build_opts.add_option("-DBETA=" + float_to_string_with_full_precision(info.beta));
     build_opts.add_option("-DEPSILON=" + float_to_string_with_full_precision(info.epsilon));
     build_opts.add_option_if(_run_in_place, "-DIN_PLACE");
     build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");

     // Create kernel
     _kernel = create_kernel(compile_context, "instance_normalization", build_opts.options());

     // Configure kernel window
     Window win = calculate_max_window(*input->info(), Steps(1));
     if(output != nullptr)
     {
         auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type());
     }

     ICLKernel::configure_internal(win);
     ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
 }

 Status CLInstanceNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const InstanceNormalizationLayerKernelInfo &info)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, info));
     return Status{};
 }

 void CLInstanceNormalizationLayerKernel::run(const Window &window, cl::CommandQueue &queue)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

     Window collapsed_window = window.collapse(window, Window::DimZ);

     // We will process the planes together
     if(_input->info()->data_layout() == DataLayout::NCHW)
     {
         collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1));
         collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
     }
     else
     {
         collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
         collapsed_window.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(3), 1));
     }

     unsigned int idx = 0;
     add_4D_tensor_argument(idx, _input, collapsed_window);
     add_3D_tensor_argument(idx, _mean, collapsed_window);

     if(!_run_in_place)
     {
         add_4D_tensor_argument(idx, _output, collapsed_window);
     }

     enqueue(queue, *this, collapsed_window, lws_hint());
 }
 } // namespace arm_compute
	/*
	* Copyright (c) 2019-2021, 2023 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 "src/core/CL/kernels/CLInstanceNormalizationLayerKernel.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/TensorInfo.h"
	#include "arm_compute/core/Utils.h"
	#include "arm_compute/core/utils/StringUtils.h"
	#include "src/core/CL/CLValidate.h"
	#include "src/core/helpers/AutoConfiguration.h"
	#include "src/core/helpers/WindowHelpers.h"
	#include "support/StringSupport.h"

	namespace arm_compute
	{
	namespace
	{
	Status validate_arguments(const ITensorInfo input, const ITensorInfo output, const InstanceNormalizationLayerKernelInfo &info)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.epsilon == 0.f, "Epsilon must be different than 0");
	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);

	if(output != nullptr && output->total_size() != 0)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(), "Input and output have different number of channels");
	}

	return Status{};
	}

	Status validate_arguments_meanvar(const ITensorInfo input, const ITensorInfo output)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);

	if(output != nullptr && output->total_size() != 0)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(), "Input and output have different number of channels");
	}

	return Status{};
	}
	} // namespace

	CLComputeMeanVariance::CLComputeMeanVariance()
	: _input(nullptr), _output(nullptr)
	{
	_type = CLKernelType::ELEMENTWISE;
	}

	void CLComputeMeanVariance::configure(const CLCompileContext &compile_context, ICLTensor input, ICLTensor output, bool use_mixed_precision)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input);
	auto padding_info = get_padding_info({ input, output });

	_input = input;
	_output = output == nullptr ? input : output;

	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_meanvar(_input->info(), _output->info()));
	const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();

	CLBuildOptions build_opts;
	build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
	build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
	build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
	build_opts.add_option("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0)));
	build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1)));
	build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2)));
	build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");
	// Create kernel
	_kernel = create_kernel(compile_context, "compute_mean_var", build_opts.options());

	// We handle the planes manually
	Window win = calculate_max_window(*(input->info()), Steps(1));
	const auto data_layout = input->info()->data_layout();
	const unsigned int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
	const unsigned int batches_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
	const unsigned int input_channel = input->info()->dimension(channel_idx);
	const unsigned int input_batches = input->info()->dimension(batches_idx);
	const TensorShape out_shape(input_channel, 2u, input_batches);

	// Output auto initialization if not yet initialized
	if(use_mixed_precision)
	{
	auto_init_if_empty(*_output->info(), out_shape, 1, DataType::F32);
	}
	else
	{
	auto_init_if_empty(*_output->info(), out_shape, 1, input->info()->data_type());
	}
	ICLKernel::configure_internal(win);
	ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
	}

	Status CLComputeMeanVariance::validate(const ITensorInfo input, const ITensorInfo output)
	{
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_meanvar(input, output));
	return Status{};
	}

	void CLComputeMeanVariance::run(const Window &window, cl::CommandQueue &queue)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

	Window collapsed_window = window.collapse(window, Window::DimZ);

	// We will process the planes together
	if(_input->info()->data_layout() == DataLayout::NCHW)
	{
	collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1));
	collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
	}
	else
	{
	collapsed_window.set(Window::DimZ, Window::Dimension(0, 1, 1));
	collapsed_window.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(3), 1));
	}
	unsigned int idx = 0;
	add_4D_tensor_argument(idx, _input, collapsed_window);
	add_3D_tensor_argument(idx, _output, collapsed_window);

	enqueue(queue, *this, collapsed_window, lws_hint());
	}

	CLInstanceNormalizationLayerKernel::CLInstanceNormalizationLayerKernel()
	: _input(nullptr), _output(nullptr), _mean(nullptr), _run_in_place(false)
	{
	_type = CLKernelType::ELEMENTWISE;
	}

	void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compile_context, ICLTensor input, ICLTensor mean_var, ICLTensor *output, const InstanceNormalizationLayerKernelInfo &info)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input);
	auto padding_info = get_padding_info({ input, output });

	_input = input;
	_output = output == nullptr ? input : output;
	_mean = mean_var;

	_run_in_place = (output == nullptr) \|\| (output == input);
	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(_input->info(), _output->info(), info));
	const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();

	CLBuildOptions build_opts;
	build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
	build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (info.use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
	build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
	build_opts.add_option("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0)));
	build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1)));
	build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2)));
	build_opts.add_option("-DGAMMA=" + float_to_string_with_full_precision(info.gamma));
	build_opts.add_option("-DBETA=" + float_to_string_with_full_precision(info.beta));
	build_opts.add_option("-DEPSILON=" + float_to_string_with_full_precision(info.epsilon));
	build_opts.add_option_if(_run_in_place, "-DIN_PLACE");
	build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");

	// Create kernel
	_kernel = create_kernel(compile_context, "instance_normalization", build_opts.options());

	// Configure kernel window
	Window win = calculate_max_window(*input->info(), Steps(1));
	if(output != nullptr)
	{
	auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type());
	}

	ICLKernel::configure_internal(win);
	ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
	}

	Status CLInstanceNormalizationLayerKernel::validate(const ITensorInfo input, const ITensorInfo output, const InstanceNormalizationLayerKernelInfo &info)
	{
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, info));
	return Status{};
	}

	void CLInstanceNormalizationLayerKernel::run(const Window &window, cl::CommandQueue &queue)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

	Window collapsed_window = window.collapse(window, Window::DimZ);

	// We will process the planes together
	if(_input->info()->data_layout() == DataLayout::NCHW)
	{
	collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1));
	collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
	}
	else
	{
	collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
	collapsed_window.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(3), 1));
	}

	unsigned int idx = 0;
	add_4D_tensor_argument(idx, _input, collapsed_window);
	add_3D_tensor_argument(idx, _mean, collapsed_window);

	if(!_run_in_place)
	{
	add_4D_tensor_argument(idx, _output, collapsed_window);
	}

	enqueue(queue, *this, collapsed_window, lws_hint());
	}
	} // namespace arm_compute