src/core/NEON/kernels/NEStridedSliceKernel.cpp - ml/ComputeLibrary - Gitiles

 /*
  * Copyright (c) 2018-2021, 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/NEON/kernels/NEStridedSliceKernel.h"

 #include "arm_compute/core/ITensor.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/core/utils/helpers/tensor_transform.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
 #include "arm_compute/core/Window.h"

 #include "src/core/CPP/Validate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "src/core/utils/helpers/bit_ops.h"

 namespace arm_compute
 {
 namespace
 {
 Status validate_arguments(const ITensorInfo *input,
                           const ITensorInfo *output,
                           const Coordinates &starts,
                           const Coordinates &ends,
                           const BiStrides   &strides,
                           int32_t            begin_mask,
                           int32_t            end_mask,
                           int32_t            shrink_axis_mask)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);

     ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape().num_dimensions() > 4);
     ARM_COMPUTE_RETURN_ERROR_ON(starts.num_dimensions() > input->num_dimensions());
     ARM_COMPUTE_RETURN_ERROR_ON(ends.num_dimensions() > input->num_dimensions());
     ARM_COMPUTE_RETURN_ERROR_ON(strides.num_dimensions() > input->num_dimensions());
     ARM_COMPUTE_RETURN_ERROR_ON(
         std::any_of(strides.cbegin(), strides.cbegin() + strides.num_dimensions(), [](int i) { return i == 0; }));

     // Get expected output shape
     const TensorShape exp_output_shape = arm_compute::misc::shape_calculator::compute_strided_slice_shape(
         *input, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask);
     ARM_COMPUTE_RETURN_ERROR_ON(exp_output_shape.total_size() == 0);

     // Checks output if configured
     if (output->total_size() != 0)
     {
         const TensorInfo exp_output_info = output->clone()->set_tensor_shape(exp_output_shape);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &exp_output_info);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
     }

     return Status{};
 }

 std::pair<Status, Window> validate_and_configure_window(const ITensorInfo *input,
                                                         ITensorInfo       *output,
                                                         const Coordinates &starts,
                                                         const Coordinates &ends,
                                                         const BiStrides   &strides,
                                                         int32_t            begin_mask,
                                                         int32_t            end_mask,
                                                         int32_t            shrink_axis_mask)
 {
     // Output tensor auto initialization if not yet initialized
     const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_strided_slice_shape(
         *input, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask);
     auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape));

     // Create window
     Window win = calculate_max_window(*output, Steps());

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

 NEStridedSliceKernel::NEStridedSliceKernel() : _starts_abs(), _final_strides(), _shrink_mask()
 {
 }

 void NEStridedSliceKernel::configure(const ITensorInfo *input,
                                      ITensorInfo       *output,
                                      const Coordinates &starts,
                                      const Coordinates &ends,
                                      const BiStrides   &strides,
                                      int32_t            begin_mask,
                                      int32_t            end_mask,
                                      int32_t            shrink_axis_mask)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(
         validate_arguments(input, output, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask));
     _shrink_mask                   = shrink_axis_mask;
     const TensorShape &input_shape = input->tensor_shape();
     Coordinates        ends_abs;
     std::tie(_starts_abs, ends_abs, _final_strides) =
         arm_compute::helpers::tensor_transform::calculate_strided_slice_coords(input_shape, starts, ends, strides,
                                                                                begin_mask, end_mask, shrink_axis_mask);
     // Configure kernel window
     auto win_config =
         validate_and_configure_window(input, output, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask);
     ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
     INEKernel::configure(win_config.second);
 }

 Status NEStridedSliceKernel::validate(const ITensorInfo *input,
                                       const ITensorInfo *output,
                                       const Coordinates &starts,
                                       const Coordinates &ends,
                                       const BiStrides   &strides,
                                       int32_t            begin_mask,
                                       int32_t            end_mask,
                                       int32_t            shrink_axis_mask)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(
         validate_arguments(input, output, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask));
     ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), starts, ends,
                                                               strides, begin_mask, end_mask, shrink_axis_mask)
                                     .first);

     return Status{};
 }

 void NEStridedSliceKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
 {
     ARM_COMPUTE_UNUSED(info);
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);

     const ITensor *input  = tensors.get_const_tensor(TensorType::ACL_SRC_0);
     const ITensor *output = tensors.get_tensor(TensorType::ACL_DST);

     size_t width_size = input->info()->element_size();

     const bool is_shrink_x = arm_compute::helpers::bit_ops::is_bit_set(_shrink_mask, 0);
     const bool is_shrink_y = arm_compute::helpers::bit_ops::is_bit_set(_shrink_mask, 1);
     const bool is_shrink_z = arm_compute::helpers::bit_ops::is_bit_set(_shrink_mask, 2);
     const bool is_shrink_w = arm_compute::helpers::bit_ops::is_bit_set(_shrink_mask, 3);

     unsigned int index = 0;
     const int    idx_x = is_shrink_x ? 0 : index++;
     const int    idx_y = is_shrink_y ? 0 : index++;
     const int    idx_z = is_shrink_z ? 0 : index++;
     const int    idx_w = is_shrink_w ? 0 : index;

     BiStrides shrinked_strides;
     shrinked_strides.set(0, is_shrink_x ? 0 : _final_strides[0]);
     shrinked_strides.set(1, is_shrink_y ? 0 : _final_strides[1]);
     shrinked_strides.set(2, is_shrink_z ? 0 : _final_strides[2]);
     shrinked_strides.set(3, is_shrink_w ? 0 : _final_strides[3]);

     Window win = window;

     size_t length_x = win.shape()[0];

     if (_final_strides[0] == 1 && !is_shrink_x)
     {
         win.set(Window::DimX, Window::Dimension(0, 1, 1));
         width_size = width_size * length_x;
     }

     Iterator output_it(output, win);

     const int start_0 = _starts_abs[0];
     const int start_1 = _starts_abs[1];
     const int start_2 = _starts_abs[2];
     const int start_3 = _starts_abs[3];

     const int shrinked_stride_0 = shrinked_strides[0];
     const int shrinked_stride_1 = shrinked_strides[1];
     const int shrinked_stride_2 = shrinked_strides[2];
     const int shrinked_stride_3 = shrinked_strides[3];

     const int byte_increment_0 = static_cast<int>(input->info()->strides_in_bytes()[0]);
     const int byte_increment_1 = static_cast<int>(input->info()->strides_in_bytes()[1]);
     const int byte_increment_2 = static_cast<int>(input->info()->strides_in_bytes()[2]);
     const int byte_increment_3 = static_cast<int>(input->info()->strides_in_bytes()[3]);

     uint8_t *input_base = input->ptr_to_element(Coordinates(0, 0, 0, 0));
     uint8_t *cur_ptr;

     execute_window_loop(
         win,
         [&](const Coordinates &id)
         {
             cur_ptr = input_base;
             cur_ptr += (start_0 + (id[idx_x] * shrinked_stride_0)) * byte_increment_0;
             cur_ptr += (start_1 + (id[idx_y] * shrinked_stride_1)) * byte_increment_1;
             cur_ptr += (start_2 + (id[idx_z] * shrinked_stride_2)) * byte_increment_2;
             cur_ptr += (start_3 + (id[idx_w] * shrinked_stride_3)) * byte_increment_3;

             std::copy_n(cur_ptr, width_size, output_it.ptr());
         },
         output_it);
 }
 } // namespace arm_compute
	/*
	* Copyright (c) 2018-2021, 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/NEON/kernels/NEStridedSliceKernel.h"

	#include "arm_compute/core/ITensor.h"
	#include "arm_compute/core/TensorInfo.h"
	#include "arm_compute/core/Types.h"
	#include "arm_compute/core/utils/helpers/tensor_transform.h"
	#include "arm_compute/core/utils/misc/ShapeCalculator.h"
	#include "arm_compute/core/Window.h"

	#include "src/core/CPP/Validate.h"
	#include "src/core/helpers/AutoConfiguration.h"
	#include "src/core/helpers/WindowHelpers.h"
	#include "src/core/utils/helpers/bit_ops.h"

	namespace arm_compute
	{
	namespace
	{
	Status validate_arguments(const ITensorInfo *input,
	const ITensorInfo *output,
	const Coordinates &starts,
	const Coordinates &ends,
	const BiStrides &strides,
	int32_t begin_mask,
	int32_t end_mask,
	int32_t shrink_axis_mask)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);

	ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape().num_dimensions() > 4);
	ARM_COMPUTE_RETURN_ERROR_ON(starts.num_dimensions() > input->num_dimensions());
	ARM_COMPUTE_RETURN_ERROR_ON(ends.num_dimensions() > input->num_dimensions());
	ARM_COMPUTE_RETURN_ERROR_ON(strides.num_dimensions() > input->num_dimensions());
	ARM_COMPUTE_RETURN_ERROR_ON(
	std::any_of(strides.cbegin(), strides.cbegin() + strides.num_dimensions(), [](int i) { return i == 0; }));

	// Get expected output shape
	const TensorShape exp_output_shape = arm_compute::misc::shape_calculator::compute_strided_slice_shape(
	*input, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask);
	ARM_COMPUTE_RETURN_ERROR_ON(exp_output_shape.total_size() == 0);

	// Checks output if configured
	if (output->total_size() != 0)
	{
	const TensorInfo exp_output_info = output->clone()->set_tensor_shape(exp_output_shape);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &exp_output_info);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	}

	return Status{};
	}

	std::pair<Status, Window> validate_and_configure_window(const ITensorInfo *input,
	ITensorInfo *output,
	const Coordinates &starts,
	const Coordinates &ends,
	const BiStrides &strides,
	int32_t begin_mask,
	int32_t end_mask,
	int32_t shrink_axis_mask)
	{
	// Output tensor auto initialization if not yet initialized
	const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_strided_slice_shape(
	*input, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask);
	auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape));

	// Create window
	Window win = calculate_max_window(*output, Steps());

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

	NEStridedSliceKernel::NEStridedSliceKernel() : _starts_abs(), _final_strides(), _shrink_mask()
	{
	}

	void NEStridedSliceKernel::configure(const ITensorInfo *input,
	ITensorInfo *output,
	const Coordinates &starts,
	const Coordinates &ends,
	const BiStrides &strides,
	int32_t begin_mask,
	int32_t end_mask,
	int32_t shrink_axis_mask)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
	ARM_COMPUTE_ERROR_THROW_ON(
	validate_arguments(input, output, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask));
	_shrink_mask = shrink_axis_mask;
	const TensorShape &input_shape = input->tensor_shape();
	Coordinates ends_abs;
	std::tie(_starts_abs, ends_abs, _final_strides) =
	arm_compute::helpers::tensor_transform::calculate_strided_slice_coords(input_shape, starts, ends, strides,
	begin_mask, end_mask, shrink_axis_mask);
	// Configure kernel window
	auto win_config =
	validate_and_configure_window(input, output, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask);
	ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
	INEKernel::configure(win_config.second);
	}

	Status NEStridedSliceKernel::validate(const ITensorInfo *input,
	const ITensorInfo *output,
	const Coordinates &starts,
	const Coordinates &ends,
	const BiStrides &strides,
	int32_t begin_mask,
	int32_t end_mask,
	int32_t shrink_axis_mask)
	{
	ARM_COMPUTE_RETURN_ON_ERROR(
	validate_arguments(input, output, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask));
	ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), starts, ends,
	strides, begin_mask, end_mask, shrink_axis_mask)
	.first);

	return Status{};
	}

	void NEStridedSliceKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
	{
	ARM_COMPUTE_UNUSED(info);
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);

	const ITensor *input = tensors.get_const_tensor(TensorType::ACL_SRC_0);
	const ITensor *output = tensors.get_tensor(TensorType::ACL_DST);

	size_t width_size = input->info()->element_size();

	const bool is_shrink_x = arm_compute::helpers::bit_ops::is_bit_set(_shrink_mask, 0);
	const bool is_shrink_y = arm_compute::helpers::bit_ops::is_bit_set(_shrink_mask, 1);
	const bool is_shrink_z = arm_compute::helpers::bit_ops::is_bit_set(_shrink_mask, 2);
	const bool is_shrink_w = arm_compute::helpers::bit_ops::is_bit_set(_shrink_mask, 3);

	unsigned int index = 0;
	const int idx_x = is_shrink_x ? 0 : index++;
	const int idx_y = is_shrink_y ? 0 : index++;
	const int idx_z = is_shrink_z ? 0 : index++;
	const int idx_w = is_shrink_w ? 0 : index;

	BiStrides shrinked_strides;
	shrinked_strides.set(0, is_shrink_x ? 0 : _final_strides[0]);
	shrinked_strides.set(1, is_shrink_y ? 0 : _final_strides[1]);
	shrinked_strides.set(2, is_shrink_z ? 0 : _final_strides[2]);
	shrinked_strides.set(3, is_shrink_w ? 0 : _final_strides[3]);

	Window win = window;

	size_t length_x = win.shape()[0];

	if (_final_strides[0] == 1 && !is_shrink_x)
	{
	win.set(Window::DimX, Window::Dimension(0, 1, 1));
	width_size = width_size * length_x;
	}

	Iterator output_it(output, win);

	const int start_0 = _starts_abs[0];
	const int start_1 = _starts_abs[1];
	const int start_2 = _starts_abs[2];
	const int start_3 = _starts_abs[3];

	const int shrinked_stride_0 = shrinked_strides[0];
	const int shrinked_stride_1 = shrinked_strides[1];
	const int shrinked_stride_2 = shrinked_strides[2];
	const int shrinked_stride_3 = shrinked_strides[3];

	const int byte_increment_0 = static_cast<int>(input->info()->strides_in_bytes()[0]);
	const int byte_increment_1 = static_cast<int>(input->info()->strides_in_bytes()[1]);
	const int byte_increment_2 = static_cast<int>(input->info()->strides_in_bytes()[2]);
	const int byte_increment_3 = static_cast<int>(input->info()->strides_in_bytes()[3]);

	uint8_t *input_base = input->ptr_to_element(Coordinates(0, 0, 0, 0));
	uint8_t *cur_ptr;

	execute_window_loop(
	win,
	[&](const Coordinates &id)
	{
	cur_ptr = input_base;
	cur_ptr += (start_0 + (id[idx_x] * shrinked_stride_0)) * byte_increment_0;
	cur_ptr += (start_1 + (id[idx_y] * shrinked_stride_1)) * byte_increment_1;
	cur_ptr += (start_2 + (id[idx_z] * shrinked_stride_2)) * byte_increment_2;
	cur_ptr += (start_3 + (id[idx_w] * shrinked_stride_3)) * byte_increment_3;

	std::copy_n(cur_ptr, width_size, output_it.ptr());
	},
	output_it);
	}
	} // namespace arm_compute