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/*
* Copyright (c) 2019 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/core/NEON/kernels/NEGenerateProposalsLayerKernel.h"
#include "arm_compute/core/AccessWindowStatic.h"
#include "arm_compute/core/CPP/Validate.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Window.h"
#include <arm_neon.h>
namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(anchors, all_anchors);
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(anchors);
ARM_COMPUTE_RETURN_ERROR_ON(anchors->dimension(0) != info.values_per_roi());
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(anchors, DataType::QSYMM16, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON(anchors->num_dimensions() > 2);
if(all_anchors->total_size() > 0)
{
const size_t feature_height = info.feat_height();
const size_t feature_width = info.feat_width();
const size_t num_anchors = anchors->dimension(1);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(all_anchors, anchors);
ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->num_dimensions() > 2);
ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->dimension(0) != info.values_per_roi());
ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->dimension(1) != feature_height * feature_width * num_anchors);
if(is_data_type_quantized(anchors->data_type()))
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(anchors, all_anchors);
}
}
return Status{};
}
} // namespace
NEComputeAllAnchorsKernel::NEComputeAllAnchorsKernel()
: _anchors(nullptr), _all_anchors(nullptr), _anchors_info(0.f, 0.f, 0.f)
{
}
void NEComputeAllAnchorsKernel::configure(const ITensor *anchors, ITensor *all_anchors, const ComputeAnchorsInfo &info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(anchors, all_anchors);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(anchors->info(), all_anchors->info(), info));
// Metadata
const size_t num_anchors = anchors->info()->dimension(1);
const DataType data_type = anchors->info()->data_type();
const float width = info.feat_width();
const float height = info.feat_height();
// Initialize the output if empty
const TensorShape output_shape(info.values_per_roi(), width * height * num_anchors);
auto_init_if_empty(*all_anchors->info(), TensorInfo(output_shape, 1, data_type, anchors->info()->quantization_info()));
// Set instance variables
_anchors = anchors;
_all_anchors = all_anchors;
_anchors_info = info;
Window win = calculate_max_window(*all_anchors->info(), Steps(info.values_per_roi()));
INEKernel::configure(win);
}
Status NEComputeAllAnchorsKernel::validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(anchors, all_anchors, info));
return Status{};
}
template <>
void NEComputeAllAnchorsKernel::internal_run<int16_t>(const Window &window)
{
Iterator all_anchors_it(_all_anchors, window);
Iterator anchors_it(_all_anchors, window);
const size_t num_anchors = _anchors->info()->dimension(1);
const float stride = 1.f / _anchors_info.spatial_scale();
const size_t feat_width = _anchors_info.feat_width();
const UniformQuantizationInfo qinfo = _anchors->info()->quantization_info().uniform();
execute_window_loop(window, [&](const Coordinates & id)
{
const size_t anchor_offset = id.y() % num_anchors;
const auto out_anchor_ptr = reinterpret_cast<int16_t *>(all_anchors_it.ptr());
const auto anchor_ptr = reinterpret_cast<int16_t *>(_anchors->ptr_to_element(Coordinates(0, anchor_offset)));
const size_t shift_idy = id.y() / num_anchors;
const float shiftx = (shift_idy % feat_width) * stride;
const float shifty = (shift_idy / feat_width) * stride;
const float new_anchor_x1 = dequantize_qsymm16(*anchor_ptr, qinfo.scale) + shiftx;
const float new_anchor_y1 = dequantize_qsymm16(*(1 + anchor_ptr), qinfo.scale) + shifty;
const float new_anchor_x2 = dequantize_qsymm16(*(2 + anchor_ptr), qinfo.scale) + shiftx;
const float new_anchor_y2 = dequantize_qsymm16(*(3 + anchor_ptr), qinfo.scale) + shifty;
*out_anchor_ptr = quantize_qsymm16(new_anchor_x1, qinfo.scale);
*(out_anchor_ptr + 1) = quantize_qsymm16(new_anchor_y1, qinfo.scale);
*(out_anchor_ptr + 2) = quantize_qsymm16(new_anchor_x2, qinfo.scale);
*(out_anchor_ptr + 3) = quantize_qsymm16(new_anchor_y2, qinfo.scale);
},
all_anchors_it);
}
template <typename T>
void NEComputeAllAnchorsKernel::internal_run(const Window &window)
{
Iterator all_anchors_it(_all_anchors, window);
Iterator anchors_it(_all_anchors, window);
const size_t num_anchors = _anchors->info()->dimension(1);
const T stride = 1.f / _anchors_info.spatial_scale();
const size_t feat_width = _anchors_info.feat_width();
execute_window_loop(window, [&](const Coordinates & id)
{
const size_t anchor_offset = id.y() % num_anchors;
const auto out_anchor_ptr = reinterpret_cast<T *>(all_anchors_it.ptr());
const auto anchor_ptr = reinterpret_cast<T *>(_anchors->ptr_to_element(Coordinates(0, anchor_offset)));
const size_t shift_idy = id.y() / num_anchors;
const T shiftx = (shift_idy % feat_width) * stride;
const T shifty = (shift_idy / feat_width) * stride;
*out_anchor_ptr = *anchor_ptr + shiftx;
*(out_anchor_ptr + 1) = *(1 + anchor_ptr) + shifty;
*(out_anchor_ptr + 2) = *(2 + anchor_ptr) + shiftx;
*(out_anchor_ptr + 3) = *(3 + anchor_ptr) + shifty;
},
all_anchors_it);
}
void NEComputeAllAnchorsKernel::run(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);
switch(_anchors->info()->data_type())
{
case DataType::QSYMM16:
{
internal_run<int16_t>(window);
break;
}
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
{
internal_run<float16_t>(window);
break;
}
#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F32:
{
internal_run<float>(window);
break;
}
default:
{
ARM_COMPUTE_ERROR("Data type not supported");
}
}
}
} // namespace arm_compute
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