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/*
* Copyright (c) 2019-2020, 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/NEDepthToSpaceLayerKernel.h"
#include "arm_compute/core/CoreTypes.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/core/Validate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "src/cpu/kernels/depth_to_space/list.h"
#include <cstdint>
namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, int32_t block_shape)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
ARM_COMPUTE_RETURN_ERROR_ON(block_shape < 2);
const DataLayout data_layout = input->data_layout();
const int idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] % (block_shape * block_shape) != 0);
// Validate output if initialized
if (output->total_size() != 0)
{
const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_width] !=
(block_shape * input->tensor_shape()[idx_width]));
ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_height] !=
(block_shape * input->tensor_shape()[idx_height]));
ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
return Status{};
}
} // namespace
NEDepthToSpaceLayerKernel::NEDepthToSpaceLayerKernel()
: _input(nullptr),
_output(nullptr),
_block_shape(),
_data_layout(DataLayout::UNKNOWN),
_split_dimension(Window::DimY)
{
}
void NEDepthToSpaceLayerKernel::configure(const ITensor *input, ITensor *output, int32_t block_shape)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
TensorShape output_shape = misc::shape_calculator::compute_depth_to_space_shape(
input->info()->tensor_shape(), input->info()->data_layout(), block_shape);
// Output auto inizialitation if not yet initialized
auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
// Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), block_shape));
_input = input;
_output = output;
_block_shape = block_shape;
_data_layout = input->info()->data_layout();
constexpr size_t dim_b = 3;
const auto dim_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
const auto dim_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
const auto dim_c = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);
ARM_COMPUTE_ERROR_ON(get_data_layout_dimension_index(_data_layout, DataLayoutDimension::BATCHES) != dim_b);
// Configure kernel window
Steps steps;
steps.set(dim_h, block_shape);
steps.set(dim_w, block_shape);
steps.set(dim_c, output->info()->dimension(dim_c));
Window win = calculate_max_window(*output->info(), steps);
ICPPKernel::configure(win);
const auto num_batches = input->info()->tensor_shape().total_size_upper(dim_b);
if (num_batches > 1)
{
_split_dimension = dim_b;
}
else
{
_split_dimension = dim_h;
}
}
Status NEDepthToSpaceLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, int32_t block_shape)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, block_shape));
return Status{};
}
size_t NEDepthToSpaceLayerKernel::get_split_dimension() const
{
return _split_dimension;
}
void NEDepthToSpaceLayerKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICPPKernel::window(), window);
const auto *input_info = _input->info();
const auto *output_info = _output->info();
const auto element_size = input_info->element_size();
const auto &input_strides = input_info->strides_in_bytes();
const auto &output_strides = output_info->strides_in_bytes();
const auto &input_shape = input_info->tensor_shape();
const uintptr_t k_input_strides[] = {input_strides[0], input_strides[1], input_strides[2], input_strides[3]};
const uintptr_t k_output_strides[] = {output_strides[0], output_strides[1], output_strides[2], output_strides[3]};
const uint8_t *k_input_ptr = _input->buffer();
uint8_t *k_output_ptr = //
_output->buffer() + //
window[3].start() * output_strides[3] + //
window[2].start() * output_strides[2] + //
window[1].start() * output_strides[1] + //
window[0].start() * output_strides[0];
if (_data_layout == DataLayout::NCHW)
{
ARM_COMPUTE_ERROR_ON_MSG(window[2].start() != 0 || window[2].end() != window[2].step(),
"The window cannot be splitted in channel dimension");
const uintptr_t k_input_shape[] = {
window.num_iterations(0), //
window.num_iterations(1), //
input_shape[2], // The window cannot be splitted in channel dimension.
window.num_iterations(3) //
};
k_input_ptr += window[3].start() * input_strides[3] + //
window[2].start() * _block_shape * _block_shape * input_strides[2] + //
(window[1].start() / _block_shape) * input_strides[1] + //
(window[0].start() / _block_shape) * input_strides[0];
cpu::depth_to_space_nchw_any( //
k_input_ptr, k_output_ptr, //
k_input_shape, k_input_strides, k_output_strides, //
element_size, _block_shape);
}
else
{
ARM_COMPUTE_ERROR_ON_MSG(window[0].start() != 0 || window[0].end() != window[0].step(),
"The window cannot be splitted in channel dimension");
const uintptr_t k_input_shape[] = {
input_shape[0], // The window cannot be splitted in channel dimension.
window.num_iterations(1), //
window.num_iterations(2), //
window.num_iterations(3) //
};
k_input_ptr += window[3].start() * input_strides[3] + //
(window[2].start() / _block_shape) * input_strides[2] + //
(window[1].start() / _block_shape) * input_strides[1] + //
window[0].start() * _block_shape * _block_shape * input_strides[0];
cpu::depth_to_space_nhwc_any( //
k_input_ptr, k_output_ptr, //
k_input_shape, k_input_strides, k_output_strides, //
element_size, _block_shape);
}
}
} // namespace arm_compute
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