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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/NEBatchToSpaceLayerKernel.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/TensorInfo.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"
using namespace arm_compute::misc::shape_calculator;
namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_info, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, output);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(block_info, 1, DataType::S32);
ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
// Validate output if initialized
if (output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
return Status{};
}
Status validate_arguments_static(const ITensorInfo *input,
int block_shape_x,
int block_shape_y,
const ITensorInfo *output,
const CropInfo &crop_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x <= 0);
ARM_COMPUTE_RETURN_ERROR_ON(block_shape_y <= 0);
const DataLayout data_layout = input->data_layout();
const int idx_batch = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_batch] % (block_shape_x * block_shape_y) != 0);
// Validate output if initialized
if (output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
const TensorShape expected_output_shape = compute_batch_to_space_shape(
input->data_layout(), input->tensor_shape(), block_shape_x, block_shape_y, crop_info);
const TensorInfo expected_output = output->clone()->set_tensor_shape(expected_output_shape);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &expected_output);
}
return Status{};
}
} // namespace
NEBatchToSpaceLayerKernel::NEBatchToSpaceLayerKernel()
: _input(nullptr),
_block_shape(nullptr),
_output(nullptr),
_data_layout(DataLayout::UNKNOWN),
_block_shape_x(),
_block_shape_y(),
_crop_info()
{
}
void NEBatchToSpaceLayerKernel::configure(const ITensor *input, const ITensor *block_shape, ITensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), output->info()));
_input = input;
_block_shape = block_shape;
_output = output;
_data_layout = input->info()->data_layout();
// Configure kernel window
Window win = calculate_max_window(*output->info(), Steps());
ICPPKernel::configure(win);
}
void NEBatchToSpaceLayerKernel::configure(
const ITensor *input, int32_t block_shape_x, int32_t block_shape_y, ITensor *output, const CropInfo &crop_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
const TensorShape output_shape = compute_batch_to_space_shape(
input->info()->data_layout(), input->info()->tensor_shape(), block_shape_x, block_shape_y);
// Output auto initialization 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_static(input->info(), block_shape_x, block_shape_y, output->info(), crop_info));
_input = input;
_output = output;
_block_shape_x = block_shape_x;
_block_shape_y = block_shape_y;
_data_layout = input->info()->data_layout();
_crop_info = crop_info;
// Configure kernel window
Window win = calculate_max_window(*output->info(), Steps());
ICPPKernel::configure(win);
}
Status
NEBatchToSpaceLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_shape, output);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, block_shape, output));
return Status{};
}
Status NEBatchToSpaceLayerKernel::validate(const ITensorInfo *input,
int32_t block_shape_x,
int32_t block_shape_y,
const ITensorInfo *output,
const CropInfo &crop_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, output, crop_info));
return Status{};
}
void NEBatchToSpaceLayerKernel::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);
if (_block_shape != nullptr)
{
// Retrieve the block shapes dynamically
_block_shape_x = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(0)));
_block_shape_y = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(1)));
}
const int batch_size = _output->info()->dimension(3);
const int element_size = _output->info()->element_size();
Window slice_out = window.first_slice_window_3D();
int batch_id = 0;
// Main loop for NCHW and NHWC
if (_data_layout == DataLayout::NCHW)
{
do
{
Iterator out(_output, slice_out);
execute_window_loop(
slice_out,
[&](const Coordinates &id)
{
const int x = id.x();
const int y = id.y();
const int z = id.z();
// Translate x, y to uncropped version
const int x_c = x + _crop_info.left;
const int y_c = y + _crop_info.top;
const int in_batch =
batch_id + ((x_c % _block_shape_x) + (y_c % _block_shape_y) * _block_shape_x) * batch_size;
const int in_x = x_c / _block_shape_x;
const int in_y = y_c / _block_shape_y;
Coordinates input_coords{in_x, in_y, z, in_batch};
memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size);
},
out);
++batch_id;
} while (window.slide_window_slice_3D(slice_out));
}
else
{
// For NHWC we can perform a block copy on the Channel (first) dimension. Thus we do not need to iterate over this dimension
slice_out.set(0U, Window::Dimension(0U, 1U, 1U));
do
{
Iterator out(_output, slice_out);
execute_window_loop(
slice_out,
[&](const Coordinates &id)
{
const int x = id.y();
const int y = id.z();
// Translate x, y to uncropped version
const int x_c = x + _crop_info.left;
const int y_c = y + _crop_info.top;
const int in_batch =
batch_id + ((x_c % _block_shape_x) + (y_c % _block_shape_y) * _block_shape_x) * batch_size;
const int in_x = x_c / _block_shape_x;
const int in_y = y_c / _block_shape_y;
Coordinates input_coords{0, in_x, in_y, in_batch};
memcpy(out.ptr(), _input->ptr_to_element(input_coords),
element_size * _input->info()->dimension(0));
},
out);
++batch_id;
} while (window.slide_window_slice_3D(slice_out));
}
}
} // namespace arm_compute
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