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/*
* Copyright (c) 2017-2020 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/runtime/NEON/functions/NEReductionOperation.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"
namespace arm_compute
{
namespace
{
/** Define dimension to split the window
*
* @param[in] axis Reduction axis
*
* @return The dimension to split the window
*/
size_t reduction_window_split_dimension(unsigned int axis)
{
switch(axis)
{
case 0:
return Window::DimY;
case 1:
case 2:
case 3:
return Window::DimX;
default:
ARM_COMPUTE_ERROR("Unsupported reduction axis");
}
}
} // namespace
NEReductionOperation::NEReductionOperation(std::shared_ptr<IMemoryManager> memory_manager)
: _memory_group(memory_manager), _reduction_kernel(), _fill_border_kernel(), _reshape(), _output_internal(), _window_split(0), _reduction_axis(), _is_reshape_required(false)
{
}
Status NEReductionOperation::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op, bool keep_dims)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 3, "Unsupported reduction axis");
const auto is_reshape_required = !keep_dims;
auto *output_internal = output;
TensorInfo info_before_reshape;
if(is_reshape_required)
{
const TensorInfo expected_output_shape = output->clone()->set_tensor_shape(arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, keep_dims));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&expected_output_shape, output);
auto shape_before_reshape = input->tensor_shape();
shape_before_reshape.set(axis, 1);
const auto input_num_channles = input->num_channels();
const auto input_qinfo = input->quantization_info();
const auto is_arg_min_max = (op == ReductionOperation::ARG_IDX_MAX) || (op == ReductionOperation::ARG_IDX_MIN);
const auto output_data_type = is_arg_min_max ? DataType::S32 : output->data_type();
info_before_reshape.set_data_type(output_data_type).set_tensor_shape(shape_before_reshape).set_num_channels(input_num_channles).set_quantization_info(input_qinfo);
output_internal = &info_before_reshape;
}
ARM_COMPUTE_RETURN_ON_ERROR(NEReductionOperationKernel::validate(input, output_internal, axis, op));
if(is_reshape_required)
{
ARM_COMPUTE_RETURN_ON_ERROR(NEReshapeLayer::validate(output_internal, output));
}
return Status{};
}
void NEReductionOperation::configure(ITensor *input, ITensor *output, unsigned int axis, ReductionOperation op, bool keep_dims)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
_is_reshape_required = !keep_dims;
auto *output_internal = output;
const auto is_arg_min_max = (op == ReductionOperation::ARG_IDX_MAX) || (op == ReductionOperation::ARG_IDX_MIN);
if(_is_reshape_required)
{
const auto output_internal_shape = arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis);
const auto output_external_shape = arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis, false);
const auto output_data_type = is_arg_min_max ? DataType::S32 : input->info()->data_type();
const auto num_channels = input->info()->num_channels();
const auto qinfo = input->info()->quantization_info();
_output_internal.allocator()->init(input->info()->clone()->set_data_type(output_data_type).set_tensor_shape(output_internal_shape).reset_padding().set_is_resizable(true).set_num_channels(
num_channels).set_quantization_info(qinfo));
_memory_group.manage(&_output_internal);
output_internal = &_output_internal;
auto_init_if_empty(*output->info(), input->info()->clone()->set_data_type(output_data_type).set_tensor_shape(output_external_shape).reset_padding().set_is_resizable(true));
}
ARM_COMPUTE_ERROR_THROW_ON(NEReductionOperation::validate(input->info(), output->info(), axis, op, keep_dims));
// Configure reduction kernel
_reduction_kernel.configure(input, output_internal, axis, op);
_window_split = reduction_window_split_dimension(axis);
_reduction_axis = axis;
if(axis == 0)
{
// Configure fill border kernel
const BorderSize fill_border_size = _reduction_kernel.border_size();
PixelValue pixelValue;
switch(op)
{
case ReductionOperation::PROD:
{
pixelValue = PixelValue(1, input->info()->data_type(), input->info()->quantization_info());
break;
}
case ReductionOperation::MIN:
{
pixelValue = std::get<1>(get_min_max(input->info()->data_type()));
break;
}
case ReductionOperation::MAX:
{
pixelValue = std::get<0>(get_min_max(input->info()->data_type()));
break;
}
case ReductionOperation::ARG_IDX_MAX:
case ReductionOperation::ARG_IDX_MIN:
{
pixelValue = PixelValue(0, input->info()->data_type(), input->info()->quantization_info());
break;
}
case ReductionOperation::MEAN_SUM:
case ReductionOperation::SUM_SQUARE:
case ReductionOperation::SUM:
{
pixelValue = PixelValue(static_cast<uint32_t>(0));
break;
}
default:
ARM_COMPUTE_ERROR("Reduction Operation unsupported");
}
_fill_border_kernel.configure(input, fill_border_size, (is_arg_min_max ? BorderMode::REPLICATE : BorderMode::CONSTANT), pixelValue);
}
if(_is_reshape_required)
{
_reshape.configure(output_internal, output);
_output_internal.allocator()->allocate();
}
}
void NEReductionOperation::run()
{
if(_reduction_axis == 0)
{
NEScheduler::get().schedule(&_fill_border_kernel, Window::DimY);
}
NEScheduler::get().schedule(&_reduction_kernel, _window_split);
if(_is_reshape_required)
{
_reshape.run();
}
}
} // namespace arm_compute
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