src/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.cpp - ml/ComputeLibrary - Gitiles

 /*
  * 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.
  */
 #include "arm_compute/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.h"

 #include "arm_compute/core/AccessWindowStatic.h"
 #include "arm_compute/core/GLES_COMPUTE/GCHelpers.h"
 #include "arm_compute/core/GLES_COMPUTE/GCKernelLibrary.h"
 #include "arm_compute/core/GLES_COMPUTE/IGCTensor.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/Validate.h"
 #include "arm_compute/core/Window.h"

 #include "support/StringSupport.h"

 using namespace arm_compute;

 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output,
                           const ITensorInfo *mean, const ITensorInfo *var,
                           const ITensorInfo *beta, const ITensorInfo *gamma,
                           float epsilon, ActivationLayerInfo act_info)
 {
     ARM_COMPUTE_UNUSED(epsilon);
     ARM_COMPUTE_UNUSED(var);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);

     ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(mean, var);

     if(output->total_size() != 0)
     {
         ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
         ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
     }

     if(beta != nullptr)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, beta);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, beta);
     }
     if(gamma != nullptr)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, gamma);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, gamma);
     }
     if(act_info.enabled())
     {
         ARM_COMPUTE_ERROR_ON(input->data_type() != DataType::F32 && input->data_type() != DataType::F16);
         ARM_COMPUTE_ERROR_ON(act_info.activation() != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::RELU
                              && act_info.activation() != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::BOUNDED_RELU
                              && act_info.activation() != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU);
         ARM_COMPUTE_ERROR_ON(act_info.b() > act_info.a());
     }
     return Status{};
 }

 std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output,
                                                         ITensorInfo *mean, ITensorInfo *var,
                                                         ITensorInfo *beta, ITensorInfo *gamma)
 {
     // Output tensor auto initialization if not yet initialized
     auto_init_if_empty(*output, input->tensor_shape(), 1, input->data_type());

     unsigned int num_elems_processed_per_iteration = 1;
     if(input->data_type() == DataType::F16)
     {
         num_elems_processed_per_iteration = 4;
     }

     // Configure kernel window
     Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));

     AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
     AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
     AccessWindowStatic     mean_access(mean, 0, 0, mean->dimension(0) + 3, mean->dimension(1));
     AccessWindowStatic     var_access(var, 0, 0, var->dimension(0) + 3, var->dimension(1));

     bool window_changed = false;
     if(beta != nullptr)
     {
         AccessWindowStatic beta_access(beta, 0, 0, beta->dimension(0) + 3, beta->dimension(1));
         if(gamma != nullptr)
         {
             AccessWindowStatic gamma_access(gamma, 0, 0, gamma->dimension(0) + 3, gamma->dimension(1));
             window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access, beta_access, gamma_access);
         }
         else
         {
             window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access, beta_access);
         }
     }
     else
     {
         if(gamma != nullptr)
         {
             AccessWindowStatic gamma_access(gamma, 0, 0, gamma->dimension(0) + 3, gamma->dimension(1));
             window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access, gamma_access);
         }
         else
         {
             window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access);
         }
     }
     output_access.set_valid_region(win, input->valid_region());

     Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
     return std::make_pair(err, win);
 }
 } // namespace

 GCBatchNormalizationLayerKernel::GCBatchNormalizationLayerKernel()
     : _input(nullptr), _output(nullptr), _mean(nullptr), _var(nullptr), _beta(nullptr), _gamma(nullptr), _epsilon(0.0f)
 {
 }

 void GCBatchNormalizationLayerKernel::configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *var, const IGCTensor *beta, const IGCTensor *gamma,
                                                 float epsilon, ActivationLayerInfo act_info)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, var);

     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mean->info(), var->info(),
                                                   (beta != nullptr) ? beta->info() : nullptr, (gamma != nullptr) ? gamma->info() : nullptr,
                                                   epsilon, act_info));

     _input   = input;
     _output  = output;
     _mean    = mean;
     _var     = var;
     _beta    = beta;
     _gamma   = gamma;
     _epsilon = epsilon;

     // Set build options
     std::set<std::string> build_opts;
     std::string           dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
     build_opts.emplace(("#define " + dt_name));
     build_opts.emplace(("#define ESPILON " + float_to_string_with_full_precision(_epsilon)));
     build_opts.emplace(("#define LOCAL_SIZE_X " + support::cpp11::to_string(1)));
     build_opts.emplace(("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1)));
     build_opts.emplace(("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1)));
     if(beta == nullptr)
     {
         build_opts.emplace("#define USE_DEFAULT_BETA");
     }
     if(gamma == nullptr)
     {
         build_opts.emplace("#define USE_DEFAULT_GAMMA");
     }

     if(act_info.enabled())
     {
         build_opts.emplace("#define " + string_from_activation_func(act_info.activation()));
         build_opts.emplace("#define A_VAL " + float_to_string_with_full_precision(act_info.a()));
         build_opts.emplace("#define B_VAL " + float_to_string_with_full_precision(act_info.b()));
     }

     // Create kernel
     _kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("batchnormalization_layer", build_opts));

     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info(), mean->info(), var->info(),
                                                     (beta != nullptr) ? beta->info() : nullptr, (gamma != nullptr) ? gamma->info() : nullptr);
     ARM_COMPUTE_ERROR_THROW_ON(win_config.first);

     IGCKernel::configure(win_config.second);
 }

 Status GCBatchNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output,
                                                  const ITensorInfo *mean, const ITensorInfo *var,
                                                  const ITensorInfo *beta, const ITensorInfo *gamma,
                                                  float epsilon, ActivationLayerInfo act_info)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mean, var, beta, gamma, epsilon, act_info));
     ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(),
                                                               mean->clone().get(), var->clone().get(),
                                                               beta->clone().get(), gamma->clone().get())
                                 .first);

     return Status{};
 }

 void GCBatchNormalizationLayerKernel::run(const Window &window)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

     _kernel.use();

     _output->set_needs_shifting(true);

     Window slice    = window.first_slice_window_3D();
     Window slice_in = window.first_slice_window_3D();

     Window vector_slice = window.first_slice_window_1D();
     vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0));

     unsigned int idx           = 2 * num_arguments_per_3D_tensor();
     unsigned int binding_point = 3;
     add_1D_tensor_argument(idx, _mean, binding_point, vector_slice);
     add_1D_tensor_argument(idx, _var, ++binding_point, vector_slice);
     if(_beta != nullptr)
     {
         add_1D_tensor_argument(idx, _beta, ++binding_point, vector_slice);
     }
     if(_gamma != nullptr)
     {
         add_1D_tensor_argument(idx, _gamma, ++binding_point, vector_slice);
     }

     slice.shift(Window::DimX, -(_output->info()->padding()).left);

     do
     {
         idx = 0;
         add_3D_tensor_argument(idx, _input, 1, slice_in);
         add_3D_tensor_argument(idx, _output, 2, slice);

         _kernel.update_shader_params();
         enqueue(*this, slice);
     }
     while(window.slide_window_slice_3D(slice) && window.slide_window_slice_3D(slice_in));
 }
	/*
	* 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.
	*/
	#include "arm_compute/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.h"

	#include "arm_compute/core/AccessWindowStatic.h"
	#include "arm_compute/core/GLES_COMPUTE/GCHelpers.h"
	#include "arm_compute/core/GLES_COMPUTE/GCKernelLibrary.h"
	#include "arm_compute/core/GLES_COMPUTE/IGCTensor.h"
	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/Utils.h"
	#include "arm_compute/core/Validate.h"
	#include "arm_compute/core/Window.h"

	#include "support/StringSupport.h"

	using namespace arm_compute;

	namespace
	{
	Status validate_arguments(const ITensorInfo input, const ITensorInfo output,
	const ITensorInfo mean, const ITensorInfo var,
	const ITensorInfo beta, const ITensorInfo gamma,
	float epsilon, ActivationLayerInfo act_info)
	{
	ARM_COMPUTE_UNUSED(epsilon);
	ARM_COMPUTE_UNUSED(var);
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);

	ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(mean, var);

	if(output->total_size() != 0)
	{
	ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	}

	if(beta != nullptr)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, beta);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, beta);
	}
	if(gamma != nullptr)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, gamma);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, gamma);
	}
	if(act_info.enabled())
	{
	ARM_COMPUTE_ERROR_ON(input->data_type() != DataType::F32 && input->data_type() != DataType::F16);
	ARM_COMPUTE_ERROR_ON(act_info.activation() != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::RELU
	&& act_info.activation() != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::BOUNDED_RELU
	&& act_info.activation() != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU);
	ARM_COMPUTE_ERROR_ON(act_info.b() > act_info.a());
	}
	return Status{};
	}

	std::pair<Status, Window> validate_and_configure_window(ITensorInfo input, ITensorInfo output,
	ITensorInfo mean, ITensorInfo var,
	ITensorInfo beta, ITensorInfo gamma)
	{
	// Output tensor auto initialization if not yet initialized
	auto_init_if_empty(*output, input->tensor_shape(), 1, input->data_type());

	unsigned int num_elems_processed_per_iteration = 1;
	if(input->data_type() == DataType::F16)
	{
	num_elems_processed_per_iteration = 4;
	}

	// Configure kernel window
	Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));

	AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
	AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
	AccessWindowStatic mean_access(mean, 0, 0, mean->dimension(0) + 3, mean->dimension(1));
	AccessWindowStatic var_access(var, 0, 0, var->dimension(0) + 3, var->dimension(1));

	bool window_changed = false;
	if(beta != nullptr)
	{
	AccessWindowStatic beta_access(beta, 0, 0, beta->dimension(0) + 3, beta->dimension(1));
	if(gamma != nullptr)
	{
	AccessWindowStatic gamma_access(gamma, 0, 0, gamma->dimension(0) + 3, gamma->dimension(1));
	window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access, beta_access, gamma_access);
	}
	else
	{
	window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access, beta_access);
	}
	}
	else
	{
	if(gamma != nullptr)
	{
	AccessWindowStatic gamma_access(gamma, 0, 0, gamma->dimension(0) + 3, gamma->dimension(1));
	window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access, gamma_access);
	}
	else
	{
	window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access);
	}
	}
	output_access.set_valid_region(win, input->valid_region());

	Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
	return std::make_pair(err, win);
	}
	} // namespace

	GCBatchNormalizationLayerKernel::GCBatchNormalizationLayerKernel()
	: _input(nullptr), _output(nullptr), _mean(nullptr), _var(nullptr), _beta(nullptr), _gamma(nullptr), _epsilon(0.0f)
	{
	}

	void GCBatchNormalizationLayerKernel::configure(const IGCTensor input, IGCTensor output, const IGCTensor mean, const IGCTensor var, const IGCTensor beta, const IGCTensor gamma,
	float epsilon, ActivationLayerInfo act_info)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, var);

	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mean->info(), var->info(),
	(beta != nullptr) ? beta->info() : nullptr, (gamma != nullptr) ? gamma->info() : nullptr,
	epsilon, act_info));

	_input = input;
	_output = output;
	_mean = mean;
	_var = var;
	_beta = beta;
	_gamma = gamma;
	_epsilon = epsilon;

	// Set build options
	std::set<std::string> build_opts;
	std::string dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
	build_opts.emplace(("#define " + dt_name));
	build_opts.emplace(("#define ESPILON " + float_to_string_with_full_precision(_epsilon)));
	build_opts.emplace(("#define LOCAL_SIZE_X " + support::cpp11::to_string(1)));
	build_opts.emplace(("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1)));
	build_opts.emplace(("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1)));
	if(beta == nullptr)
	{
	build_opts.emplace("#define USE_DEFAULT_BETA");
	}
	if(gamma == nullptr)
	{
	build_opts.emplace("#define USE_DEFAULT_GAMMA");
	}

	if(act_info.enabled())
	{
	build_opts.emplace("#define " + string_from_activation_func(act_info.activation()));
	build_opts.emplace("#define A_VAL " + float_to_string_with_full_precision(act_info.a()));
	build_opts.emplace("#define B_VAL " + float_to_string_with_full_precision(act_info.b()));
	}

	// Create kernel
	_kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("batchnormalization_layer", build_opts));

	// Configure kernel window
	auto win_config = validate_and_configure_window(input->info(), output->info(), mean->info(), var->info(),
	(beta != nullptr) ? beta->info() : nullptr, (gamma != nullptr) ? gamma->info() : nullptr);
	ARM_COMPUTE_ERROR_THROW_ON(win_config.first);

	IGCKernel::configure(win_config.second);
	}

	Status GCBatchNormalizationLayerKernel::validate(const ITensorInfo input, const ITensorInfo output,
	const ITensorInfo mean, const ITensorInfo var,
	const ITensorInfo beta, const ITensorInfo gamma,
	float epsilon, ActivationLayerInfo act_info)
	{
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mean, var, beta, gamma, epsilon, act_info));
	ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(),
	mean->clone().get(), var->clone().get(),
	beta->clone().get(), gamma->clone().get())
	.first);

	return Status{};
	}

	void GCBatchNormalizationLayerKernel::run(const Window &window)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

	_kernel.use();

	_output->set_needs_shifting(true);

	Window slice = window.first_slice_window_3D();
	Window slice_in = window.first_slice_window_3D();

	Window vector_slice = window.first_slice_window_1D();
	vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0));

	unsigned int idx = 2 * num_arguments_per_3D_tensor();
	unsigned int binding_point = 3;
	add_1D_tensor_argument(idx, _mean, binding_point, vector_slice);
	add_1D_tensor_argument(idx, _var, ++binding_point, vector_slice);
	if(_beta != nullptr)
	{
	add_1D_tensor_argument(idx, _beta, ++binding_point, vector_slice);
	}
	if(_gamma != nullptr)
	{
	add_1D_tensor_argument(idx, _gamma, ++binding_point, vector_slice);
	}

	slice.shift(Window::DimX, -(_output->info()->padding()).left);

	do
	{
	idx = 0;
	add_3D_tensor_argument(idx, _input, 1, slice_in);
	add_3D_tensor_argument(idx, _output, 2, slice);

	_kernel.update_shader_params();
	enqueue(*this, slice);
	}
	while(window.slide_window_slice_3D(slice) && window.slide_window_slice_3D(slice_in));
	}