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/*
* Copyright (c) 2019-2023 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/NEGatherKernel.h"
#include "arm_compute/core/Coordinates.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *indices, const ITensorInfo *output, int axis)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, indices, output);
ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
if (axis < 0)
{
axis += input->num_dimensions();
}
ARM_COMPUTE_RETURN_ERROR_ON(0 > axis || axis >= static_cast<int32_t>(input->num_dimensions()));
ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() + indices->num_dimensions() - 1 >
Coordinates::num_max_dimensions);
ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
if (output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
TensorShape output_shape = arm_compute::misc::shape_calculator::compute_gather_shape(
input->tensor_shape(), indices->tensor_shape(), axis);
ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() != output->tensor_shape().total_size());
}
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(indices, 1, DataType::U32, DataType::S32);
return Status{};
}
} // namespace
NEGatherKernel::NEGatherKernel()
: _input{}, _indices{}, _axis{}, _output{}, _func{}, _src_it_strides{}, _idx_it_strides{}
{
}
template <typename TIndex>
void NEGatherKernel::gather_common(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
auto dst_win = window;
const auto src_info = _input->info();
const auto idx_info = _indices->info();
const auto dst_info = _output->info();
const auto num_dims = dst_info->num_dimensions();
const auto chunk_stride = src_info->strides_in_bytes()[_axis];
const auto window_start_x = window.x().start();
const auto window_end_x = window.x().end();
auto window_size_x = src_info->element_size();
const auto idx_limit = static_cast<TIndex>(src_info->tensor_shape()[_axis]);
if (_axis != 0)
{
dst_win.set(0, Window::Dimension(window_start_x, window_start_x + 1, 1));
window_size_x *= window_end_x - window_start_x;
}
// Compute source and index tensors window based on the output window.
auto src_win = dst_win;
Window idx_win;
for (size_t i = 0; i < idx_info->num_dimensions(); ++i)
{
src_win.set(_axis + i, Window::Dimension(0, 1, 1));
idx_win.set(_axis + i, window[_axis + i]);
}
// Use the custom strides to access all three tensors using the same loop.
Iterator src_it(num_dims, _src_it_strides, _input->buffer(), src_info->offset_first_element_in_bytes(), src_win);
Iterator idx_it(num_dims, _idx_it_strides, _indices->buffer(), idx_info->offset_first_element_in_bytes(), idx_win);
Iterator dst_it(num_dims, dst_info->strides_in_bytes(), _output->buffer(),
dst_info->offset_first_element_in_bytes(), dst_win);
execute_window_loop(
dst_win,
[&](const Coordinates &)
{
const auto idx = *reinterpret_cast<const TIndex *>(idx_it.ptr());
if (idx >= 0 && idx < idx_limit)
{
const auto src_ptr = src_it.ptr() + idx * chunk_stride;
std::copy_n(src_ptr, window_size_x, dst_it.ptr());
}
else
{
std::fill_n(dst_it.ptr(), window_size_x, 0);
}
},
src_it, idx_it, dst_it);
}
void NEGatherKernel::configure(const ITensor *input, const ITensor *indices, ITensor *output, int axis)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, indices);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), indices->info(), output->info(), axis));
_input = input;
_indices = indices;
_output = output;
_axis = axis;
if (_axis < 0)
{
_axis += input->info()->num_dimensions();
}
ARM_COMPUTE_ERROR_ON(0 > _axis || _axis >= static_cast<int32_t>(input->info()->num_dimensions()));
switch (_indices->info()->data_type())
{
case DataType::U32:
_func = &NEGatherKernel::gather_common<uint32_t>;
break;
case DataType::S32:
_func = &NEGatherKernel::gather_common<int32_t>;
break;
default:
ARM_COMPUTE_ERROR("Not supported");
break;
}
// Output auto initialization if not yet initialized
const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_gather_shape(
input->info()->tensor_shape(), indices->info()->tensor_shape(), _axis);
auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
// Create window
Window win = calculate_max_window(*output->info(), Steps());
INEKernel::configure(win);
// Create input and indices strides that have the same number of dimensions as the output tensor.
// These will be used to iterate lock-step through all tensors (input, indices and output).
size_t dim_no = 0;
const auto input_info = input->info();
const auto &input_strides = input_info->strides_in_bytes();
const auto indices_info = indices->info();
const auto &indices_strides = indices_info->strides_in_bytes();
const auto indices_num_dims = indices_info->num_dimensions();
for (; dim_no < static_cast<size_t>(_axis); ++dim_no)
{
_src_it_strides[dim_no] = input_strides[dim_no];
}
for (; dim_no < static_cast<size_t>(_axis) + indices_num_dims; ++dim_no)
{
_idx_it_strides[dim_no] = indices_strides[dim_no - _axis];
}
for (; dim_no < Coordinates::num_max_dimensions; ++dim_no)
{
_src_it_strides[dim_no] = input_strides[dim_no - indices_num_dims + 1];
}
}
Status
NEGatherKernel::validate(const ITensorInfo *input, const ITensorInfo *indices, const ITensorInfo *output, int axis)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, indices, output, axis));
return Status{};
}
void NEGatherKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON(_func == nullptr);
(this->*_func)(window, info);
}
} // namespace arm_compute
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