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/*
* Copyright (c) 2016-2020 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 "src/core/NEON/kernels/NEScaleKernel.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Window.h"
#include "arm_compute/core/utils/misc/Utility.h"
#include "src/core/AccessWindowStatic.h"
#include "src/core/CPP/Validate.h"
#include "src/core/NEON/wrapper/wrapper.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/ScaleHelpers.h"
#include "src/core/helpers/WindowHelpers.h"
#include "src/core/utils/ScaleUtils.h"
#include "support/Rounding.h"
#include <arm_neon.h>
#include <map>
namespace arm_compute
{
namespace
{
inline float compute_bilinear(float a00, float a01, float a10, float a11, float dx_val, float dy_val)
{
const float dx1_val = 1.0f - dx_val;
const float dy1_val = 1.0f - dy_val;
const float w1 = dx1_val * dy1_val;
const float w2 = dx_val * dy1_val;
const float w3 = dx1_val * dy_val;
const float w4 = dx_val * dy_val;
return a00 * w1 + a01 * w2 + a10 * w3 + a11 * w4;
}
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *dx, const ITensorInfo *dy,
const ITensorInfo *offsets, ITensorInfo *output, const ScaleKernelInfo &info)
{
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S16, DataType::F16, DataType::F32, DataType::QASYMM8, DataType::QASYMM8_SIGNED);
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(output == input);
ARM_COMPUTE_RETURN_ERROR_ON(info.sampling_policy != SamplingPolicy::CENTER && info.sampling_policy != SamplingPolicy::TOP_LEFT);
ARM_COMPUTE_UNUSED(info.constant_border_value);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.use_padding, "Padding is not supported");
const DataLayout data_layout = input->data_layout();
const auto width_index = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
const auto height_index = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
const auto output_width = output->dimension(width_index);
const auto output_height = output->dimension(height_index);
ARM_COMPUTE_RETURN_ERROR_ON(output_width == 0);
ARM_COMPUTE_RETURN_ERROR_ON(output_height == 0);
if(info.interpolation_policy == InterpolationPolicy::NEAREST_NEIGHBOR)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(offsets, 1, DataType::S32);
}
if(info.interpolation_policy == InterpolationPolicy::BILINEAR)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(offsets, 1, DataType::S32);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dx, 1, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dy, 1, DataType::F32);
}
ARM_COMPUTE_RETURN_ERROR_ON(info.align_corners && !scale_utils::is_align_corners_allowed_sampling_policy(info.sampling_policy));
if(info.interpolation_policy == InterpolationPolicy::AREA)
{
ARM_COMPUTE_RETURN_ERROR_ON(data_layout != DataLayout::NCHW);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
}
return Status{};
}
} // namespace
NEScaleKernel::NEScaleKernel()
: _func(nullptr), _offsets(nullptr), _dx(nullptr), _dy(nullptr), _input(nullptr), _output(nullptr), _policy(), _border_mode(), _constant_border_value(PixelValue()), _sampling_offset(0),
_align_corners(false)
{
}
void NEScaleKernel::configure(const ITensor *input, const ITensor *dx, const ITensor *dy, const ITensor *offsets,
ITensor *output, const ScaleKernelInfo &info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(),
dx != nullptr ? dx->info() : nullptr,
dy != nullptr ? dy->info() : nullptr,
offsets != nullptr ? offsets->info() : nullptr,
output->info(),
info));
// Get data layout and width/height indices
const DataLayout data_layout = input->info()->data_layout();
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);
_input = input;
_output = output;
_offsets = offsets;
_dx = dx;
_dy = dy;
_policy = info.interpolation_policy;
_border_mode = info.border_mode;
_constant_border_value = info.constant_border_value;
_align_corners = info.align_corners;
if(info.sampling_policy == SamplingPolicy::CENTER)
{
_sampling_offset = 0.5f;
}
// Compute the ratio between source width/height and destination width/height
const auto wr = scale_utils::calculate_resize_ratio(input->info()->dimension(idx_width), output->info()->dimension(idx_width), _align_corners);
const auto hr = scale_utils::calculate_resize_ratio(input->info()->dimension(idx_height), output->info()->dimension(idx_height), _align_corners);
// Area interpolation behaves as Nearest Neighbour in case of up-sampling
const auto policy_to_use = (info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) ? InterpolationPolicy::NEAREST_NEIGHBOR : _policy;
if(_border_mode == BorderMode::UNDEFINED)
{
_border_mode = BorderMode::CONSTANT;
_constant_border_value = PixelValue();
}
std::string function_to_call("scale_");
function_to_call += string_from_data_type(_input->info()->data_type()) + "_";
function_to_call += string_from_data_layout(_input->info()->data_layout()) + "_";
function_to_call += string_from_interpolation_policy(policy_to_use);
static std::map<std::string, ScaleFunctionPtr> map_function =
{
{ "scale_U8_NCHW_AREA_CONSTANT", &NEScaleKernel::scale_area_nchw_u8 },
{ "scale_U8_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_nchw<uint8_t> },
{ "scale_U8_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<uint8_t> },
{ "scale_U8_NHWC_BILINEAR", &NEScaleKernel::scale_bilinear_nhwc<uint8_t> },
{ "scale_U8_NHWC_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nhwc<uint8_t> },
{ "scale_QASYMM8_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_qasymm<uint8_t> },
{ "scale_QASYMM8_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<uint8_t> },
{ "scale_QASYMM8_NHWC_BILINEAR", &NEScaleKernel::scale_bilinear_qasymm<uint8_t> },
{ "scale_QASYMM8_NHWC_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nhwc<uint8_t> },
{ "scale_QASYMM8_SIGNED_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_qasymm<int8_t> },
{ "scale_QASYMM8_SIGNED_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<uint8_t> },
{ "scale_QASYMM8_SIGNED_NHWC_BILINEAR", &NEScaleKernel::scale_bilinear_qasymm<int8_t> },
{ "scale_QASYMM8_SIGNED_NHWC_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nhwc<uint8_t> },
{ "scale_S16_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_nchw<int16_t> },
{ "scale_S16_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<uint16_t> },
{ "scale_S16_NHWC_BILINEAR", &NEScaleKernel::scale_bilinear_nhwc<int16_t> },
{ "scale_S16_NHWC_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nhwc<uint16_t> },
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
{ "scale_F16_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_nchw<float16_t> },
{ "scale_F16_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<uint16_t> },
{ "scale_F16_NHWC_BILINEAR", &NEScaleKernel::scale_bilinear_nhwc<float16_t> },
{ "scale_F16_NHWC_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nhwc<uint16_t> },
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
{ "scale_F32_NCHW_BILINEAR", &NEScaleKernel::scale_bilinear_nchw<float> },
{ "scale_F32_NCHW_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nchw<float> },
{ "scale_F32_NHWC_BILINEAR", &NEScaleKernel::scale_bilinear_nhwc<float> },
{ "scale_F32_NHWC_NEAREST_NEIGHBOUR", &NEScaleKernel::scale_nearest_nhwc<float> },
};
auto it = map_function.find(function_to_call);
if(it != map_function.end())
{
_func = it->second;
}
// Configure window
Window win = calculate_max_window(*output->info(), Steps());
Coordinates coord;
coord.set_num_dimensions(output->info()->num_dimensions());
output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));
INEKernel::configure(win);
}
template <typename T>
void NEScaleKernel::scale_nearest_nchw(const Window &window)
{
const size_t in_stride_x = _input->info()->dimension(0) + _input->info()->padding().left + _input->info()->padding().right;
// Compute the ratio between source height and destination height
const auto hr = scale_utils::calculate_resize_ratio(_input->info()->dimension(1), _output->info()->dimension(1), _align_corners);
// Don't increment in X and Y direction for the input tensor
// A pointer to the start of this plane is needed as base for the precomputed offsets
Window win_in(window);
win_in.set(Window::DimX, Window::Dimension(0, 0, 0));
win_in.set(Window::DimY, Window::Dimension(0, 0, 0));
// Set offsets window
Window win_off;
win_off.set(Window::DimX, window[Window::DimX]);
win_off.set(Window::DimY, window[Window::DimY]);
for(size_t d = Window::DimZ; d < _offsets->info()->num_dimensions(); ++d)
{
win_off.set(d, Window::Dimension(0, 0, 0));
}
// Create iterators
Iterator in(_input, win_in);
Iterator out(_output, window);
Iterator offsets(_offsets, win_off);
execute_window_loop(window, [&](const Coordinates & id)
{
const auto offsets_ptr = reinterpret_cast<const int32_t *>(offsets.ptr());
const auto in_yi = static_cast<int32_t>(_align_corners ? utils::rounding::round_half_away_from_zero((id.y() + _sampling_offset) * hr) : std::floor((id.y() + _sampling_offset) * hr));
const int32_t offset_row = in_yi * in_stride_x;
*reinterpret_cast<T *>(out.ptr()) = *(reinterpret_cast<const T *>(in.ptr()) + offsets_ptr[0] + offset_row);
},
in, offsets, out);
}
template <typename T>
void NEScaleKernel::scale_bilinear_nchw(const Window &window)
{
// Compute the ratio between source height and destination height
const auto hr = scale_utils::calculate_resize_ratio(_input->info()->dimension(1), _output->info()->dimension(1), _align_corners);
Window win_off;
win_off.set(Window::DimX, window.x());
win_off.set(Window::DimY, window.y());
// Don't increment in X and Y direction for the input tensor
// A pointer to the start of this plane is needed as base for the precomputed offsets
Window win_in(window);
win_in.set(Window::DimX, Window::Dimension(0, 0, 0));
win_in.set(Window::DimY, Window::Dimension(0, 0, 0));
for(size_t d = Window::DimZ; d < _offsets->info()->num_dimensions(); ++d)
{
win_off.set(d, Window::Dimension(0, 0, 0));
}
Iterator in(_input, win_in);
Iterator out(_output, window);
Iterator offsets(_offsets, win_off);
Iterator dx(_dx, win_off);
Iterator dy(_dy, win_off);
const int32_t in_dim_w = _input->info()->dimension(0);
const int32_t in_dim_h = _input->info()->dimension(1);
const int32_t in_stride_w = in_dim_w + _input->info()->padding().left + _input->info()->padding().right;
if(_border_mode == BorderMode::CONSTANT)
{
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
using ConstType = typename std::conditional<std::is_same<T, float16_t>::value, half, T>::type;
#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
using ConstType = T;
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
const T const_border_value = static_cast<T>(_constant_border_value.get<ConstType>());
execute_window_loop(window, [&](const Coordinates & id)
{
const int32_t index_h = std::floor((id.y() + _sampling_offset) * hr - _sampling_offset);
const auto index_w = *(reinterpret_cast<const int32_t *>(offsets.ptr()));
const auto dx_val = *(reinterpret_cast<const float *>(dx.ptr()));
const auto dy_val = *(reinterpret_cast<const float *>(dy.ptr()));
const auto pixel_row_ptr = reinterpret_cast<const T *>(in.ptr());
const auto a00 = (0 <= index_w && index_w < in_dim_w && 0 <= index_h && index_h < in_dim_h) ? (*(pixel_row_ptr + index_w + index_h * in_stride_w)) : const_border_value;
const auto a01 = (-1 <= index_w && index_w < in_dim_w - 1 && 0 <= index_h && index_h < in_dim_h) ? (*(pixel_row_ptr + index_w + 1 + index_h * in_stride_w)) : const_border_value;
const auto a10 = (0 <= index_w && index_w < in_dim_w && -1 <= index_h
&& index_h < in_dim_h - 1) ?
(*(pixel_row_ptr + index_w + index_h * in_stride_w + in_stride_w)) :
const_border_value;
const auto a11 = (-1 <= index_w && index_w < in_dim_w - 1 && -1 <= index_h
&& index_h < in_dim_h - 1) ?
(*(pixel_row_ptr + index_w + 1 + index_h * in_stride_w + in_stride_w)) :
const_border_value;
*reinterpret_cast<T *>(out.ptr()) = static_cast<T>(compute_bilinear(a00, a01, a10, a11, dx_val, dy_val));
},
in, offsets, dx, dy, out);
}
else if(_border_mode == BorderMode::REPLICATE)
{
execute_window_loop(window, [&](const Coordinates & id)
{
const int index_h = std::floor((id.y() + _sampling_offset) * hr - _sampling_offset);
const auto index_w = *(reinterpret_cast<const int32_t *>(offsets.ptr()));
const auto dx_val = *(reinterpret_cast<const float *>(dx.ptr()));
const auto dy_val = *(reinterpret_cast<const float *>(dy.ptr()));
const auto pixel_row_ptr = reinterpret_cast<const T *>(in.ptr());
auto clamped_x = utility::clamp<int>(index_w, 0, in_dim_w - 1);
auto clamped_x1 = utility::clamp<int>(index_w + 1, 0, in_dim_w - 1);
auto clamped_y = utility::clamp<int>(index_h, 0, in_dim_h - 1);
auto clamped_y1 = utility::clamp<int>(index_h + 1, 0, in_dim_h - 1);
const auto a00 = *(pixel_row_ptr + clamped_x + clamped_y * in_stride_w);
const auto a01 = *(pixel_row_ptr + clamped_x1 + clamped_y * in_stride_w);
const auto a10 = *(pixel_row_ptr + clamped_x + clamped_y1 * in_stride_w);
const auto a11 = *(pixel_row_ptr + clamped_x1 + clamped_y1 * in_stride_w);
*reinterpret_cast<T *>(out.ptr()) = static_cast<T>(compute_bilinear(a00, a01, a10, a11, dx_val, dy_val));
},
in, offsets, dx, dy, out);
}
else
{
ARM_COMPUTE_ERROR("Not implemented");
}
}
void NEScaleKernel::scale_area_nchw_u8(const Window &window)
{
using namespace scale_helpers;
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(_input, 1, DataType::U8);
// Don't increment in width/height/channels for the input tensor
// A pointer to the start of this plane is needed as base for the precomputed offsets
Window win_in(window);
win_in.set(Window::DimX, Window::Dimension(0, 0, 0));
win_in.set(Window::DimY, Window::Dimension(0, 0, 0));
win_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
Iterator in(_input, win_in);
Iterator out(_output, window);
const auto wr = scale_utils::calculate_resize_ratio(_input->info()->dimension(0), _output->info()->dimension(0), _align_corners);
const auto hr = scale_utils::calculate_resize_ratio(_input->info()->dimension(1), _output->info()->dimension(1), _align_corners);
const auto w = _input->info()->dimension(0);
const auto h = _input->info()->dimension(1);
const size_t in_stride = _input->info()->strides_in_bytes()[1];
execute_window_loop(window, [&](const Coordinates & id)
{
const auto in_ptr = reinterpret_cast<const uint8_t *>(in.ptr());
uint8x8_t tmp0 = vdup_n_u8(0);
tmp0 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x(), id.y()), tmp0, 0);
tmp0 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 1, id.y()), tmp0, 1);
tmp0 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 2, id.y()), tmp0, 2);
tmp0 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 3, id.y()), tmp0, 3);
tmp0 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 4, id.y()), tmp0, 4);
tmp0 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 5, id.y()), tmp0, 5);
tmp0 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 6, id.y()), tmp0, 6);
tmp0 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 7, id.y()), tmp0, 7);
uint8x8_t tmp1 = vdup_n_u8(0);
tmp1 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 8, id.y()), tmp1, 0);
tmp1 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 9, id.y()), tmp1, 1);
tmp1 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 10, id.y()), tmp1, 2);
tmp1 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 11, id.y()), tmp1, 3);
tmp1 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 12, id.y()), tmp1, 4);
tmp1 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 13, id.y()), tmp1, 5);
tmp1 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 14, id.y()), tmp1, 6);
tmp1 = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 15, id.y()), tmp1, 7);
vst1q_u8(out.ptr(), vcombine_u8(tmp0, tmp1));
},
in, out);
}
template <typename T>
void NEScaleKernel::scale_nearest_nhwc(const Window &window)
{
const size_t in_stride_c = _input->info()->dimension(0) + _input->info()->padding().left + _input->info()->padding().right;
const size_t in_stride_w = _input->info()->dimension(1) + _input->info()->padding().top + _input->info()->padding().bottom;
const size_t in_stride_wc = in_stride_w * in_stride_c;
const size_t in_dim_h = _input->info()->dimension(2);
// Compute the ratio between source height and destination height
const auto hr = scale_utils::calculate_resize_ratio(in_dim_h, _output->info()->dimension(2), _align_corners);
const auto window_start_x = static_cast<int32_t>(window.x().start());
const auto window_end_x = static_cast<int32_t>(window.x().end());
const int window_step_x = 16 / sizeof(T);
Window win(window);
win.set(Window::DimX, Window::Dimension(0, 1, 1));
Iterator out(_output, win);
const uint8_t *in_ptr_start = _input->buffer() + _input->info()->offset_first_element_in_bytes();
const unsigned int in_stride_bytes_hwc = _input->info()->strides_in_bytes()[3];
execute_window_loop(win, [&](const Coordinates & id)
{
const int32_t offset = *reinterpret_cast<const int32_t *>(_offsets->ptr_to_element(Coordinates(id.y(), id.z()))) * in_stride_c;
const auto in_hi = static_cast<int>(_align_corners ? utils::rounding::round_half_away_from_zero((id.z() + _sampling_offset) * hr) : std::floor((id.z() + _sampling_offset) * hr));
const int offset_row = in_hi * in_stride_wc;
int32_t x = window_start_x;
const T *in_ptr = reinterpret_cast<const T *>(in_ptr_start + in_stride_bytes_hwc * id[3]);
for(; x <= window_end_x - window_step_x; x += window_step_x)
{
wrapper::vstore(reinterpret_cast<T *>(out.ptr()) + x,
wrapper::vloadq(in_ptr + offset + offset_row + x));
}
for(; x < window_end_x; ++x)
{
*(reinterpret_cast<T *>(out.ptr()) + x) = *(in_ptr + offset + offset_row + x);
}
},
out);
}
template <typename T>
void NEScaleKernel::scale_bilinear_nhwc(const Window &window)
{
// Compute the ratio between source height and destination height
const auto hr = scale_utils::calculate_resize_ratio(_input->info()->dimension(2), _output->info()->dimension(2), _align_corners);
Iterator out(_output, window);
const int in_stride_c = _input->info()->dimension(0) + _input->info()->padding().left + _input->info()->padding().right;
const int in_dim_w = _input->info()->dimension(1);
const int in_dim_h = _input->info()->dimension(2);
const int in_stride_wc = in_stride_c * (in_dim_w + _input->info()->padding().top + _input->info()->padding().bottom);
// Don't increment in Y and Z direction for the input tensor
// A pointer to the start of this plane is needed as base for the precomputed offsets
Window win_in(window);
win_in.set(Window::DimY, Window::Dimension(0, 0, 0));
win_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
Iterator in(_input, win_in);
if(_border_mode == BorderMode::CONSTANT)
{
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
using ConstType = typename std::conditional<std::is_same<T, float16_t>::value, half, T>::type;
#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
using ConstType = T;
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
const T const_border_value = static_cast<T>(_constant_border_value.get<ConstType>());
execute_window_loop(window, [&](const Coordinates & id)
{
const auto offset = *reinterpret_cast<const int32_t *>(_offsets->ptr_to_element(Coordinates(id.y(), id.z())));
const auto dx_val = *reinterpret_cast<const float *>(_dx->ptr_to_element(Coordinates(id.y(), id.z())));
const auto dy_val = *reinterpret_cast<const float *>(_dy->ptr_to_element(Coordinates(id.y(), id.z())));
const int32_t in_hi = std::floor((id.z() + _sampling_offset) * hr - _sampling_offset);
const T *in_ptr = reinterpret_cast<const T *>(in.ptr()) + offset * in_stride_c + in_hi * in_stride_wc;
const auto a00 = (0 <= offset && offset < in_dim_w && 0 <= in_hi && in_hi < in_dim_h) ? *in_ptr : const_border_value;
const auto a01 = (-1 <= offset && offset < in_dim_w - 1 && 0 <= in_hi && in_hi < in_dim_h) ? *(in_ptr + in_stride_c) : const_border_value;
const auto a10 = (0 <= offset && offset < in_dim_w && -1 <= in_hi && in_hi < in_dim_h - 1) ? *(in_ptr + in_stride_wc) : const_border_value;
const auto a11 = (-1 <= offset && offset < in_dim_w - 1 && -1 <= in_hi && in_hi < in_dim_h - 1) ? *(in_ptr + in_stride_c + in_stride_wc) : const_border_value;
*reinterpret_cast<T *>(out.ptr()) = static_cast<T>(compute_bilinear(a00, a01, a10, a11, dx_val, dy_val));
},
in, out);
}
else if(_border_mode == BorderMode::REPLICATE)
{
execute_window_loop(window, [&](const Coordinates & id)
{
const auto offset = *reinterpret_cast<const int32_t *>(_offsets->ptr_to_element(Coordinates(id.y(), id.z())));
const auto dx_val = *reinterpret_cast<const float *>(_dx->ptr_to_element(Coordinates(id.y(), id.z())));
const auto dy_val = *reinterpret_cast<const float *>(_dy->ptr_to_element(Coordinates(id.y(), id.z())));
const int in_hi = std::floor((id.z() + _sampling_offset) * hr - _sampling_offset);
auto clamped_w = utility::clamp<int>(offset, 0, in_dim_w - 1);
auto clamped_w1 = utility::clamp<int>(offset + 1, 0, in_dim_w - 1);
auto clamped_h = utility::clamp<int>(in_hi, 0, in_dim_h - 1);
auto clamped_h1 = utility::clamp<int>(in_hi + 1, 0, in_dim_h - 1);
const auto a00 = *(reinterpret_cast<const T *>(in.ptr()) + clamped_w * in_stride_c + clamped_h * in_stride_wc);
const auto a01 = *(reinterpret_cast<const T *>(in.ptr()) + clamped_w1 * in_stride_c + clamped_h * in_stride_wc);
const auto a10 = *(reinterpret_cast<const T *>(in.ptr()) + clamped_w * in_stride_c + clamped_h1 * in_stride_wc);
const auto a11 = *(reinterpret_cast<const T *>(in.ptr()) + clamped_w1 * in_stride_c + clamped_h1 * in_stride_wc);
*reinterpret_cast<T *>(out.ptr()) = static_cast<T>(compute_bilinear(a00, a01, a10, a11, dx_val, dy_val));
},
in, out);
}
else
{
ARM_COMPUTE_ERROR("Not implemented");
}
}
template <typename T>
void NEScaleKernel::scale_bilinear_qasymm(const Window &window)
{
// Get data layout and width/height indices
const DataLayout data_layout = _input->info()->data_layout();
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);
// Compute the ratio between source height and destination height
const auto hr = scale_utils::calculate_resize_ratio(_input->info()->dimension(idx_height), _output->info()->dimension(idx_height), _align_corners);
Window win_off;
win_off.set(Window::DimX, Window::Dimension(0, 0, 0));
win_off.set(Window::DimY, Window::Dimension(0, 0, 0));
// Don't increment in X and Y direction for the input tensor
// A pointer to the start of this plane is needed as base for the precomputed offsets
Window win_in(window);
win_in.set(idx_width, Window::Dimension(0, 0, 0));
win_in.set(idx_height, Window::Dimension(0, 0, 0));
for(size_t d = Window::DimZ; d < _offsets->info()->num_dimensions(); ++d)
{
win_off.set(d, Window::Dimension(0, 0, 0));
}
Iterator in(_input, win_in);
Iterator out(_output, window);
const int32_t in_dim_w = _input->info()->dimension(idx_width);
const int32_t in_dim_h = _input->info()->dimension(idx_height);
const int32_t stride_w = _input->info()->strides_in_bytes()[idx_width];
const int32_t stride_h = _input->info()->strides_in_bytes()[idx_height];
const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform();
const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform();
if(_border_mode == BorderMode::CONSTANT)
{
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
using ConstType = typename std::conditional<std::is_same<T, float16_t>::value, half, T>::type;
#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
using ConstType = T;
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
const T const_border_value = static_cast<T>(_constant_border_value.get<ConstType>());
execute_window_loop(window, [&](const Coordinates & id)
{
const int32_t index_h = std::floor((id[idx_height] + _sampling_offset) * hr - _sampling_offset);
const int32_t index_w = *(reinterpret_cast<const int32_t *>(_offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
const auto dx_val = *(reinterpret_cast<const float *>(_dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
const auto dy_val = *(reinterpret_cast<const float *>(_dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
const auto pixel_row_ptr = reinterpret_cast<const T *>(in.ptr());
const auto a00 = (0 <= index_w && index_w < in_dim_w && 0 <= index_h && index_h < in_dim_h) ?
(*(pixel_row_ptr + index_w * stride_w + index_h * stride_h)) :
const_border_value;
const auto a01 = (-1 <= index_w && index_w < in_dim_w - 1 && 0 <= index_h && index_h < in_dim_h) ?
(*(pixel_row_ptr + (index_w + 1) * stride_w + index_h * stride_h)) :
const_border_value;
const auto a10 = (0 <= index_w && index_w < in_dim_w && -1 <= index_h && index_h < in_dim_h - 1) ?
(*(pixel_row_ptr + index_w * stride_w + (index_h + 1) * stride_h)) :
const_border_value;
const auto a11 = (-1 <= index_w && index_w < in_dim_w - 1 && -1 <= index_h && index_h < in_dim_h - 1) ?
(*(pixel_row_ptr + (index_w + 1) * stride_w + (index_h + 1) * stride_h)) :
const_border_value;
const float inp00 = Qasymm8QuantizationHelper<T>::dequantize(a00, iq_info);
const float inp01 = Qasymm8QuantizationHelper<T>::dequantize(a01, iq_info);
const float inp10 = Qasymm8QuantizationHelper<T>::dequantize(a10, iq_info);
const float inp11 = Qasymm8QuantizationHelper<T>::dequantize(a11, iq_info);
*reinterpret_cast<T *>(out.ptr()) = Qasymm8QuantizationHelper<T>::quantize(compute_bilinear(inp00, inp01, inp10, inp11, dx_val, dy_val), oq_info);
},
in, out);
}
else if(_border_mode == BorderMode::REPLICATE)
{
execute_window_loop(window, [&](const Coordinates & id)
{
const int index_h = std::floor((id[idx_height] + _sampling_offset) * hr - _sampling_offset);
const int32_t index_w = *(reinterpret_cast<const int32_t *>(_offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
const auto dx_val = *(reinterpret_cast<const float *>(_dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
const auto dy_val = *(reinterpret_cast<const float *>(_dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
const auto pixel_row_ptr = reinterpret_cast<const T *>(in.ptr());
auto clamped_w = utility::clamp<int>(index_w, 0, in_dim_w - 1);
auto clamped_w1 = utility::clamp<int>(index_w + 1, 0, in_dim_w - 1);
auto clamped_h = utility::clamp<int>(index_h, 0, in_dim_h - 1);
auto clamped_h1 = utility::clamp<int>(index_h + 1, 0, in_dim_h - 1);
const auto a00 = *(pixel_row_ptr + clamped_w * stride_w + clamped_h * stride_h);
const auto a01 = *(pixel_row_ptr + clamped_w1 * stride_w + clamped_h * stride_h);
const auto a10 = *(pixel_row_ptr + clamped_w * stride_w + clamped_h1 * stride_h);
const auto a11 = *(pixel_row_ptr + clamped_w1 * stride_w + clamped_h1 * stride_h);
const float inp00 = Qasymm8QuantizationHelper<T>::dequantize(a00, iq_info);
const float inp01 = Qasymm8QuantizationHelper<T>::dequantize(a01, iq_info);
const float inp10 = Qasymm8QuantizationHelper<T>::dequantize(a10, iq_info);
const float inp11 = Qasymm8QuantizationHelper<T>::dequantize(a11, iq_info);
*reinterpret_cast<T *>(out.ptr()) = Qasymm8QuantizationHelper<T>::quantize(compute_bilinear(inp00, inp01, inp10, inp11, dx_val, dy_val), oq_info);
},
in, out);
}
else
{
ARM_COMPUTE_ERROR("Not implemented");
}
}
Status NEScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *dx, const ITensorInfo *dy,
const ITensorInfo *offsets, ITensorInfo *output, const ScaleKernelInfo &info)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, dx, dy, offsets, output, info));
return Status{};
}
void NEScaleKernel::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);
ARM_COMPUTE_ERROR_ON(_func == nullptr);
(this->*_func)(window);
}
} // namespace arm_compute