src/core/CL/kernels/CLSoftmaxLayerKernel.cpp - platform/external/ComputeLibrary - Git at Google

 /*
  * Copyright (c) 2017 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/CLSoftmaxLayerKernel.h"

 #include "arm_compute/core/AccessWindowStatic.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/CL/OpenCL.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/Validate.h"
 #include "arm_compute/core/Window.h"

 #include <set>
 #include <string>

 using namespace arm_compute;

 void CLLogits1DMaxKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);

     _input  = input;
     _output = output;

     // The kernel loops over all elements in steps of 16
     const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 16);

     // Set build options
     std::set<std::string> build_opts{ "-DUSE_" + string_from_data_type(input->info()->data_type()) };

     // Tell the kernel that the width is not a multiple of 16
     if((input->info()->dimension(0) % max_cl_vector_width) != 0)
     {
         build_opts.emplace("-DNON_MULTIPLE_OF_16");
     }

     // Create kernel
     _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("softmax_layer_max", build_opts));

     // Set fixed arguments
     unsigned int idx = 2 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
     _kernel.setArg<cl_uint>(idx++, input->info()->dimension(0));

     // Configure kernel window
     constexpr unsigned int num_elems_written_per_iteration = 1;

     Window                 win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
     AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
     AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration);

     update_window_and_padding(win, input_access, output_access);

     output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape()));

     ICLKernel::configure(win);
 }

 CLLogits1DShiftExpSumKernel::CLLogits1DShiftExpSumKernel()
     : _input(nullptr), _max(nullptr), _output(nullptr), _sum(nullptr)
 {
 }

 void CLLogits1DShiftExpSumKernel::configure(const ICLTensor *input, const ICLTensor *max, ICLTensor *output, ICLTensor *sum)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(max, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(sum, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, max, sum);

     _input  = input;
     _max    = max;
     _output = output;
     _sum    = sum;

     // The kernel loops over all elements in steps of 16
     const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 16);

     // Set build options
     std::set<std::string> build_opts{ "-DUSE_" + string_from_data_type(input->info()->data_type()) };

     // Tell the kernel that the width is not a multiple of 16
     if((input->info()->dimension(0) % max_cl_vector_width) != 0)
     {
         build_opts.emplace("-DNON_MULTIPLE_OF_16");
     }

     // Create kernel
     _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("softmax_layer_shift_exp_sum", build_opts));

     // Set fixed arguments
     unsigned int idx = 4 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
     _kernel.setArg<cl_uint>(idx++, input->info()->dimension(0));

     // Configure window
     Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));

     AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
     AccessWindowHorizontal max_access(max->info(), 0, 1);
     AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
     AccessWindowHorizontal sum_access(sum->info(), 0, 1);

     update_window_and_padding(win, input_access, max_access, output_access, sum_access);

     output_access.set_valid_region(win, input->info()->valid_region());
     sum_access.set_valid_region(win, ValidRegion(Coordinates(), sum->info()->tensor_shape()));

     ICLKernel::configure(win);
 }

 void CLLogits1DShiftExpSumKernel::run(const Window &window, cl::CommandQueue &queue)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

     Window slice = window.first_slice_window_2D();

     do
     {
         unsigned int idx = 0;
         // Set inputs
         add_2D_tensor_argument(idx, _input, slice);
         add_2D_tensor_argument(idx, _max, slice);
         add_2D_tensor_argument(idx, _output, slice);
         add_2D_tensor_argument(idx, _sum, slice);
         enqueue(queue, *this, slice);
     }
     while(window.slide_window_slice_2D(slice));
 }

 CLLogits1DNormKernel::CLLogits1DNormKernel()
     : _input(nullptr), _sum(nullptr), _output(nullptr)
 {
 }

 void CLLogits1DNormKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(sum, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, sum);

     _input  = input;
     _sum    = sum;
     _output = output;

     // Set build options
     std::set<std::string> build_opts;
     build_opts.emplace(("-DUSE_" + string_from_data_type(input->info()->data_type())));

     // Create kernel
     _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("softmax_layer_norm", build_opts));

     // Configure window
     constexpr unsigned int num_elems_processed_per_iteration = 16;

     Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));

     AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
     AccessWindowStatic     sum_access(sum->info(), 0, 0, 1, sum->info()->dimension(1));
     AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);

     update_window_and_padding(win, input_access, sum_access, output_access);

     output_access.set_valid_region(win, input->info()->valid_region());

     ICLKernel::configure(win);
 }

 void CLLogits1DNormKernel::run(const Window &window, cl::CommandQueue &queue)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

     Window slice = window.first_slice_window_2D();

     do
     {
         Window sum_slice = slice;
         sum_slice.set(Window::DimX, Window::Dimension(0, 1, 1));

         unsigned int idx = 0;
         // Set inputs
         add_2D_tensor_argument(idx, _input, slice);
         add_2D_tensor_argument(idx, _sum, sum_slice);
         add_2D_tensor_argument(idx, _output, slice);
         enqueue(queue, *this, slice);
     }
     while(window.slide_window_slice_2D(slice));
 }
	/*
	* Copyright (c) 2017 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/CLSoftmaxLayerKernel.h"

	#include "arm_compute/core/AccessWindowStatic.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/CL/OpenCL.h"
	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/TensorInfo.h"
	#include "arm_compute/core/Utils.h"
	#include "arm_compute/core/Validate.h"
	#include "arm_compute/core/Window.h"

	#include <set>
	#include <string>

	using namespace arm_compute;

	void CLLogits1DMaxKernel::configure(const ICLTensor input, ICLTensor output)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);

	_input = input;
	_output = output;

	// The kernel loops over all elements in steps of 16
	const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 16);

	// Set build options
	std::set<std::string> build_opts{ "-DUSE_" + string_from_data_type(input->info()->data_type()) };

	// Tell the kernel that the width is not a multiple of 16
	if((input->info()->dimension(0) % max_cl_vector_width) != 0)
	{
	build_opts.emplace("-DNON_MULTIPLE_OF_16");
	}

	// Create kernel
	_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("softmax_layer_max", build_opts));

	// Set fixed arguments
	unsigned int idx = 2 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
	_kernel.setArg<cl_uint>(idx++, input->info()->dimension(0));

	// Configure kernel window
	constexpr unsigned int num_elems_written_per_iteration = 1;

	Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
	AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
	AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration);

	update_window_and_padding(win, input_access, output_access);

	output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape()));

	ICLKernel::configure(win);
	}

	CLLogits1DShiftExpSumKernel::CLLogits1DShiftExpSumKernel()
	: _input(nullptr), _max(nullptr), _output(nullptr), _sum(nullptr)
	{
	}

	void CLLogits1DShiftExpSumKernel::configure(const ICLTensor input, const ICLTensor max, ICLTensor output, ICLTensor sum)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(max, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(sum, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, max, sum);

	_input = input;
	_max = max;
	_output = output;
	_sum = sum;

	// The kernel loops over all elements in steps of 16
	const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 16);

	// Set build options
	std::set<std::string> build_opts{ "-DUSE_" + string_from_data_type(input->info()->data_type()) };

	// Tell the kernel that the width is not a multiple of 16
	if((input->info()->dimension(0) % max_cl_vector_width) != 0)
	{
	build_opts.emplace("-DNON_MULTIPLE_OF_16");
	}

	// Create kernel
	_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("softmax_layer_shift_exp_sum", build_opts));

	// Set fixed arguments
	unsigned int idx = 4 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
	_kernel.setArg<cl_uint>(idx++, input->info()->dimension(0));

	// Configure window
	Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));

	AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
	AccessWindowHorizontal max_access(max->info(), 0, 1);
	AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
	AccessWindowHorizontal sum_access(sum->info(), 0, 1);

	update_window_and_padding(win, input_access, max_access, output_access, sum_access);

	output_access.set_valid_region(win, input->info()->valid_region());
	sum_access.set_valid_region(win, ValidRegion(Coordinates(), sum->info()->tensor_shape()));

	ICLKernel::configure(win);
	}

	void CLLogits1DShiftExpSumKernel::run(const Window &window, cl::CommandQueue &queue)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

	Window slice = window.first_slice_window_2D();

	do
	{
	unsigned int idx = 0;
	// Set inputs
	add_2D_tensor_argument(idx, _input, slice);
	add_2D_tensor_argument(idx, _max, slice);
	add_2D_tensor_argument(idx, _output, slice);
	add_2D_tensor_argument(idx, _sum, slice);
	enqueue(queue, *this, slice);
	}
	while(window.slide_window_slice_2D(slice));
	}

	CLLogits1DNormKernel::CLLogits1DNormKernel()
	: _input(nullptr), _sum(nullptr), _output(nullptr)
	{
	}

	void CLLogits1DNormKernel::configure(const ICLTensor input, const ICLTensor sum, ICLTensor *output)
	{
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(sum, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, sum);

	_input = input;
	_sum = sum;
	_output = output;

	// Set build options
	std::set<std::string> build_opts;
	build_opts.emplace(("-DUSE_" + string_from_data_type(input->info()->data_type())));

	// Create kernel
	_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("softmax_layer_norm", build_opts));

	// Configure window
	constexpr unsigned int num_elems_processed_per_iteration = 16;

	Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));

	AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
	AccessWindowStatic sum_access(sum->info(), 0, 0, 1, sum->info()->dimension(1));
	AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);

	update_window_and_padding(win, input_access, sum_access, output_access);

	output_access.set_valid_region(win, input->info()->valid_region());

	ICLKernel::configure(win);
	}

	void CLLogits1DNormKernel::run(const Window &window, cl::CommandQueue &queue)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);

	Window slice = window.first_slice_window_2D();

	do
	{
	Window sum_slice = slice;
	sum_slice.set(Window::DimX, Window::Dimension(0, 1, 1));

	unsigned int idx = 0;
	// Set inputs
	add_2D_tensor_argument(idx, _input, slice);
	add_2D_tensor_argument(idx, _sum, sum_slice);
	add_2D_tensor_argument(idx, _output, slice);
	enqueue(queue, *this, slice);
	}
	while(window.slide_window_slice_2D(slice));
	}