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/*
* Copyright (c) 2019-2020 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/NECropKernel.h"
#include "arm_compute/core/IAccessWindow.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Window.h"
#include "arm_compute/core/utils/helpers/tensor_transform.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "src/core/CPP/Validate.h"
#include "src/core/NEON/wrapper/wrapper.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "src/core/utils/helpers/bit_ops.h"
namespace arm_compute
{
namespace
{
template <typename T>
inline float32x4_t load_as_f32(T *ptr)
{
ARM_COMPUTE_UNUSED(ptr);
ARM_COMPUTE_ERROR("Type not supported.");
}
template <>
inline float32x4_t load_as_f32(float *ptr)
{
return wrapper::vloadq(ptr);
}
template <>
inline float32x4_t load_as_f32(int32_t *ptr)
{
return vcvtq_f32_s32(wrapper::vloadq(ptr));
}
template <>
inline float32x4_t load_as_f32(uint32_t *ptr)
{
return vcvtq_f32_u32(wrapper::vloadq(ptr));
}
template <>
inline float32x4_t load_as_f32(int16_t *ptr)
{
return vcvtq_f32_s32(vmovl_s16(wrapper::vload(ptr)));
}
template <>
inline float32x4_t load_as_f32(uint16_t *ptr)
{
return vcvtq_f32_u32(vmovl_u16(wrapper::vload(ptr)));
}
template <>
inline float32x4_t load_as_f32(uint8_t *ptr)
{
return vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8(wrapper::vload(ptr)))));
}
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
template <>
inline float32x4_t load_as_f32(float16_t *ptr)
{
return vcvt_f32_f16(wrapper::vload(ptr));
}
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
template <typename T>
inline void in_bounds_crop_window(const ITensor *input, const ITensor *output, float *output_ptr, Coordinates input_offset,
int32_t window_step_x, int32_t output_width_start, int32_t output_width_limit, bool input_has_single_channel, bool is_width_flipped)
{
// Reverse elements if width flipped.
if(is_width_flipped)
{
// Collapse first dimension if possible.
if(input_has_single_channel)
{
int32_t x = output_width_start;
Coordinates negative_offset(input_offset);
negative_offset.set(1, negative_offset[1] - window_step_x + 1);
for(; x <= output_width_limit - window_step_x; x += window_step_x, negative_offset[1] -= window_step_x)
{
auto in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(negative_offset)));
in = wrapper::vrev64(in);
in = wrapper::vcombine(wrapper::vgethigh(in), wrapper::vgetlow(in));
wrapper::vstore(output_ptr + x, in);
}
input_offset[1] = negative_offset[1] + window_step_x - 1;
for(; x < output_width_limit; ++x, --input_offset[1])
{
*(output_ptr + x) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
}
}
else
{
for(int32_t x = output_width_start; x < output_width_limit; ++x, --input_offset[1])
{
input_offset.set(0, 0);
int32_t c = 0;
for(; c <= static_cast<int32_t>(input->info()->dimension(0)) - window_step_x; c += window_step_x, input_offset[0] += window_step_x)
{
auto in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
wrapper::vstore(output_ptr + x * output->info()->dimension(0) + c, in);
}
for(; c < static_cast<int32_t>(input->info()->dimension(0)); ++c, ++input_offset[0])
{
*(output_ptr + x * output->info()->dimension(0) + c) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
}
}
}
}
else
{
// Use memcpy if the elements don't need converting to float.
if(std::is_same<T, float>::value)
{
memcpy(static_cast<void *>(output_ptr + output_width_start * output->info()->dimension(0)),
reinterpret_cast<const void *>(input->ptr_to_element(input_offset)),
(output_width_limit - output_width_start) * output->info()->dimension(0) * output->info()->element_size());
}
else
{
int32_t x = 0;
int32_t limit = (output_width_limit - output_width_start) * static_cast<int32_t>(output->info()->dimension(0));
float *output_start_ptr = output_ptr + output_width_start * output->info()->dimension(0);
for(; x <= limit - window_step_x; x += window_step_x, input_offset[0] += window_step_x)
{
auto in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
wrapper::vstore(output_start_ptr + x, in);
}
for(; x < limit; ++x, ++input_offset[0])
{
*(output_start_ptr + x) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));
}
}
}
}
inline void out_of_bounds_crop_window(const ITensor *output, float *output_ptr, float extrapolation_value,
int32_t window_step_x, int32_t output_width_start, int32_t output_width_limit)
{
auto in = wrapper::vdup_n(extrapolation_value, wrapper::traits::vector_128_tag());
int32_t x = 0;
int32_t limit = (output_width_limit - output_width_start) * static_cast<int32_t>(output->info()->dimension(0));
float *output_start_ptr = output_ptr + output_width_start * output->info()->dimension(0);
for(; x <= limit - window_step_x; x += window_step_x)
{
wrapper::vstore(output_start_ptr + x, in);
}
for(; x < limit; ++x)
{
*(output_start_ptr + x) = extrapolation_value;
}
}
inline void execute_window(const ITensor *input, const ITensor *output, Coordinates input_offset, float extrapolation_value,
const std::array<uint32_t, 2> &rows_out_of_bounds, const std::array<uint32_t, 2> &cols_out_of_bounds, NECropKernel::InBoundsCropFunction *in_bounds_crop_function,
bool is_height_flipped, bool has_cols_in_bounds, bool has_cols_out_of_bounds_before, bool has_cols_out_of_bounds_after, bool input_has_single_channel, bool is_width_flipped)
{
// Output is always float.
const int window_step_x = 16 / sizeof(float);
auto *output_ptr = reinterpret_cast<float *>(output->buffer());
// Output window:
// --------------------------------
// | Out of bounds |
// | rows before |
// |------------------------------|
// | Out of | In | Out of |
// | bounds | bounds | bounds |
// | cols | elements | cols |
// | before | copied | after |
// | | from input | |
// --------------------------------
// | Out of bounds |
// | rows after |
// |------------------------------|
// Fill all output rows that have no elements that are within the input bounds with the extrapolation value.
// First for the rows before the in bounds rows.
out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, 0, rows_out_of_bounds[0] * output->info()->dimension(1));
output_ptr += rows_out_of_bounds[0] * output->info()->dimension(1) * output->info()->dimension(0);
// Iterate through each row that has any elements within the input bounds.
for(uint32_t row = rows_out_of_bounds[0]; static_cast<int32_t>(row) < static_cast<int32_t>(output->info()->dimension(2) - rows_out_of_bounds[1]);
++row, is_height_flipped ? --input_offset[2] : ++input_offset[2])
{
// Fill all elements in the row that are out of bounds with the extrapolation value.
// First for the elements before the in bounds elements.
if(has_cols_out_of_bounds_before)
{
out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, 0, cols_out_of_bounds[0]);
}
// Copy all elements within the input bounds from the input tensor.
if(has_cols_in_bounds)
{
(*in_bounds_crop_function)(input, output, output_ptr, input_offset, window_step_x, cols_out_of_bounds[0],
output->info()->dimension(1) - cols_out_of_bounds[1], input_has_single_channel, is_width_flipped);
}
// Fill all elements after the in bounds elements with the extrapolation value.
if(has_cols_out_of_bounds_after)
{
out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, output->info()->dimension(1) - cols_out_of_bounds[1], output->info()->dimension(1));
}
output_ptr += output->info()->dimension(1) * output->info()->dimension(0);
}
// Fill all rows after the in bounds elements with the extrapolation value.
out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, 0, rows_out_of_bounds[1] * output->info()->dimension(1));
}
} // namespace
NECropKernel::NECropKernel()
: _input(nullptr), _crop_boxes(nullptr), _box_ind(nullptr), _output(nullptr), _start(), _end(), _crop_box_ind(0), _extrapolation_value(0), _rows_out_of_bounds(), _cols_out_of_bounds(),
_in_bounds_crop_function(nullptr)
{
}
void NECropKernel::configure(const ITensor *input, const ITensor *crop_boxes, const ITensor *box_ind, ITensor *output, uint32_t crop_box_ind, float extrapolation_value)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(validate(input->info(), crop_boxes->info(), box_ind->info(), output->info(), crop_box_ind, extrapolation_value));
_input = input;
_crop_boxes = crop_boxes;
_box_ind = box_ind;
_output = output;
_crop_box_ind = crop_box_ind;
_extrapolation_value = extrapolation_value;
switch(input->info()->data_type())
{
case DataType::F32:
_in_bounds_crop_function = &in_bounds_crop_window<float>;
break;
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
_in_bounds_crop_function = &in_bounds_crop_window<float16_t>;
break;
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
case DataType::U32:
_in_bounds_crop_function = &in_bounds_crop_window<uint32_t>;
break;
case DataType::S32:
_in_bounds_crop_function = &in_bounds_crop_window<int32_t>;
break;
case DataType::U16:
_in_bounds_crop_function = &in_bounds_crop_window<uint16_t>;
break;
case DataType::S16:
_in_bounds_crop_function = &in_bounds_crop_window<int16_t>;
break;
case DataType::U8:
_in_bounds_crop_function = &in_bounds_crop_window<uint8_t>;
break;
default:
ARM_COMPUTE_ERROR("Datatype not supported");
}
}
Status NECropKernel::validate(const ITensorInfo *input, const ITensorInfo *crop_boxes, const ITensorInfo *box_ind, const ITensorInfo *output, uint32_t crop_box_ind, float extrapolation_value)
{
ARM_COMPUTE_UNUSED(extrapolation_value);
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::U16, DataType::S16, DataType::F16, DataType::U32, DataType::S32, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NHWC);
ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape().num_dimensions() > 4);
ARM_COMPUTE_RETURN_ERROR_ON(crop_boxes->tensor_shape()[0] != 4);
ARM_COMPUTE_RETURN_ERROR_ON(crop_boxes->tensor_shape()[1] != box_ind->tensor_shape()[0]);
ARM_COMPUTE_RETURN_ERROR_ON(crop_boxes->tensor_shape()[1] <= crop_box_ind);
ARM_COMPUTE_RETURN_ERROR_ON(box_ind->tensor_shape()[0] <= crop_box_ind);
if(output->total_size() > 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(output, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() != 3);
ARM_COMPUTE_RETURN_ERROR_ON(output->has_padding());
}
return Status{};
}
void NECropKernel::configure_output_shape()
{
// _crop_box_ind is used to index _crop_boxes and retrieve the appropriate crop box.
// The crop box is specified by normalized coordinates [y0, x0, y1, x1].
const float x0 = *reinterpret_cast<const float *>(_crop_boxes->ptr_to_element(Coordinates(1, _crop_box_ind)));
const float y0 = *reinterpret_cast<const float *>(_crop_boxes->ptr_to_element(Coordinates(0, _crop_box_ind)));
const float x1 = *reinterpret_cast<const float *>(_crop_boxes->ptr_to_element(Coordinates(3, _crop_box_ind)));
const float y1 = *reinterpret_cast<const float *>(_crop_boxes->ptr_to_element(Coordinates(2, _crop_box_ind)));
// The normalized coordiantes are scaled to retrieve the floating point image coordinates which are rounded to integers.
_start = Coordinates(std::floor(x0 * (_input->info()->tensor_shape()[1] - 1) + 0.5f),
std::floor(y0 * (_input->info()->tensor_shape()[2] - 1) + 0.5f));
_end = Coordinates(std::floor(x1 * (_input->info()->tensor_shape()[1] - 1) + 0.5f),
std::floor(y1 * (_input->info()->tensor_shape()[2] - 1) + 0.5f));
const TensorShape out_shape(_input->info()->tensor_shape()[0], abs(_end[0] - _start[0]) + 1, abs(_end[1] - _start[1]) + 1);
_output->info()->set_tensor_shape(out_shape);
bool is_width_flipped = _end[0] < _start[0];
bool is_height_flipped = _end[1] < _start[1];
if(is_height_flipped)
{
_rows_out_of_bounds[0] = _start[1] >= static_cast<int32_t>(_input->info()->dimension(2)) ? std::min(static_cast<uint32_t>(_start[1] - _input->info()->dimension(2) + 1),
static_cast<uint32_t>(_output->info()->dimension(2))) :
0;
_rows_out_of_bounds[1] = _end[1] < 0 ? std::min(static_cast<uint32_t>(-_end[1]),
static_cast<uint32_t>(_output->info()->dimension(2))) :
0;
}
else
{
_rows_out_of_bounds[0] = _start[1] < 0 ? std::min(static_cast<uint32_t>(-_start[1]),
static_cast<uint32_t>(_output->info()->dimension(2))) :
0;
_rows_out_of_bounds[1] = _end[1] >= static_cast<int32_t>(_input->info()->dimension(2)) ? std::min(static_cast<uint32_t>(_end[1] - _input->info()->dimension(2) + 1),
static_cast<uint32_t>(_output->info()->dimension(2))) :
0;
}
if(is_width_flipped)
{
_cols_out_of_bounds[0] = _start[0] >= static_cast<int32_t>(_input->info()->dimension(1)) ? std::min(static_cast<uint32_t>(_start[0] - _input->info()->dimension(1) + 1),
static_cast<uint32_t>(_output->info()->dimension(1))) :
0;
_cols_out_of_bounds[1] = _end[0] < 0 ? std::min(static_cast<uint32_t>(-_end[0]),
static_cast<uint32_t>(_output->info()->dimension(1))) :
0;
}
else
{
_cols_out_of_bounds[0] = _start[0] < 0 ? std::min(static_cast<uint32_t>(-_start[0]),
static_cast<uint32_t>(_output->info()->dimension(1))) :
0;
_cols_out_of_bounds[1] = _end[0] >= static_cast<int32_t>(_input->info()->dimension(1)) ? std::min(static_cast<uint32_t>(_end[0] - _input->info()->dimension(1) + 1),
static_cast<uint32_t>(_output->info()->dimension(1))) :
0;
}
INEKernel::configure(calculate_max_window(*_output->info()));
}
void NECropKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(window, info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
ARM_COMPUTE_ERROR_ON(_input->info()->has_padding());
ARM_COMPUTE_ERROR_ON(_output->info()->has_padding());
uint32_t batch_index = *(reinterpret_cast<int32_t *>(_box_ind->ptr_to_element(Coordinates(_crop_box_ind))));
Coordinates input_offset(0, _end[0] < _start[0] ? _start[0] - _cols_out_of_bounds[0] : _start[0] + _cols_out_of_bounds[0],
_end[1] < _start[1] ? _start[1] - _rows_out_of_bounds[0] : _start[1] + _rows_out_of_bounds[0], batch_index);
execute_window(_input, _output, input_offset, _extrapolation_value, _rows_out_of_bounds, _cols_out_of_bounds, _in_bounds_crop_function, _end[1] < _start[1],
_cols_out_of_bounds[0] + _cols_out_of_bounds[1] < _output->info()->dimension(1), _cols_out_of_bounds[0] > 0, _cols_out_of_bounds[1] > 0,
_start[0] <= _end[0], _end[0] < _start[0]);
}
} // namespace arm_compute