| /* |
| * 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/NECropKernel.h" |
| |
| #include "arm_compute/core/CPP/Validate.h" |
| #include "arm_compute/core/IAccessWindow.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Window.h" |
| |
| #include "arm_compute/core/NEON/wrapper/wrapper.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/utils/helpers/bit_ops.h" |
| #include "arm_compute/core/utils/helpers/tensor_transform.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| |
| #include <map> |
| |
| 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))); |
| } |
| |
| #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, bool input_has_single_channel, bool is_width_flipped> |
| 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) |
| { |
| // 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; |
| } |
| } |
| |
| template <bool is_height_flipped, bool has_cols_in_bounds, bool has_cols_out_of_bounds_before, bool has_cols_out_of_bounds_after> |
| 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) |
| { |
| // 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]); |
| } |
| // 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_functions(), _in_bounds_crop_function(nullptr), _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; |
| |
| const static std::map<std::pair<DataType, bool>, std::pair<NECropKernel::InBoundsCropFunction *, NECropKernel::InBoundsCropFunction *>> in_map_function = |
| { |
| { { DataType::F32, false }, { &in_bounds_crop_window<float, false, false>, &in_bounds_crop_window<float, false, true> } }, |
| { { DataType::F32, true }, { &in_bounds_crop_window<float, true, false>, &in_bounds_crop_window<float, true, true> } }, |
| { { DataType::U16, false }, { &in_bounds_crop_window<uint16_t, false, false>, &in_bounds_crop_window<uint16_t, false, true> } }, |
| { { DataType::U16, true }, { &in_bounds_crop_window<uint16_t, true, false>, &in_bounds_crop_window<uint16_t, true, true> } }, |
| { { DataType::S16, false }, { &in_bounds_crop_window<int16_t, false, false>, &in_bounds_crop_window<int16_t, false, true> } }, |
| { { DataType::S16, true }, { &in_bounds_crop_window<int16_t, true, false>, &in_bounds_crop_window<int16_t, true, true> } }, |
| { { DataType::U32, false }, { &in_bounds_crop_window<uint32_t, false, false>, &in_bounds_crop_window<uint32_t, false, true> } }, |
| { { DataType::U32, true }, { &in_bounds_crop_window<uint32_t, true, false>, &in_bounds_crop_window<uint32_t, true, true> } }, |
| { { DataType::S32, false }, { &in_bounds_crop_window<int32_t, false, false>, &in_bounds_crop_window<int32_t, false, true> } }, |
| { { DataType::S32, true }, { &in_bounds_crop_window<int32_t, true, false>, &in_bounds_crop_window<int32_t, true, true> } }, |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| { { DataType::F16, false }, { &in_bounds_crop_window<float16_t, false, false>, &in_bounds_crop_window<float16_t, false, true> } }, |
| { { DataType::F16, false }, { &in_bounds_crop_window<float16_t, true, false>, &in_bounds_crop_window<float16_t, true, true> } } |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| }; |
| |
| auto in_it = in_map_function.find({ input->info()->data_type(), input->info()->dimension(0) == 1 }); |
| |
| if(in_it != in_map_function.end()) |
| { |
| _in_bounds_crop_functions = in_it->second; |
| } |
| } |
| |
| 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::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); |
| |
| _in_bounds_crop_function = _start[0] <= _end[0] ? _in_bounds_crop_functions.first : _in_bounds_crop_functions.second; |
| |
| 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; |
| } |
| |
| const static std::map<std::tuple<bool, bool, bool, bool>, NECropKernel::CropFunction *> map_function = |
| { |
| { std::make_tuple(false, false, false, false), &execute_window<false, false, false, false> }, |
| { std::make_tuple(false, false, false, true), &execute_window<false, false, false, true> }, |
| { std::make_tuple(false, false, true, false), &execute_window<false, false, true, false> }, |
| { std::make_tuple(false, false, true, true), &execute_window<false, false, true, true> }, |
| { std::make_tuple(false, true, false, false), &execute_window<false, true, false, false> }, |
| { std::make_tuple(false, true, false, true), &execute_window<false, true, false, true> }, |
| { std::make_tuple(false, true, true, false), &execute_window<false, true, true, false> }, |
| { std::make_tuple(false, true, true, true), &execute_window<false, true, true, true> }, |
| { std::make_tuple(true, false, false, false), &execute_window<true, false, false, false> }, |
| { std::make_tuple(true, false, false, true), &execute_window<true, false, false, true> }, |
| { std::make_tuple(true, false, true, false), &execute_window<true, false, true, false> }, |
| { std::make_tuple(true, false, true, true), &execute_window<true, false, true, true> }, |
| { std::make_tuple(true, true, false, false), &execute_window<true, true, false, false> }, |
| { std::make_tuple(true, true, false, true), &execute_window<true, true, false, true> }, |
| { std::make_tuple(true, true, true, false), &execute_window<true, true, true, false> }, |
| { std::make_tuple(true, true, true, true), &execute_window<true, true, true, true> }, |
| }; |
| |
| auto it = map_function.find(std::make_tuple(is_height_flipped, |
| _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)); |
| |
| if(it != map_function.end()) |
| { |
| _crop_function = it->second; |
| } |
| |
| 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); |
| (*_crop_function)(_input, _output, input_offset, _extrapolation_value, _rows_out_of_bounds, _cols_out_of_bounds, _in_bounds_crop_function); |
| } |
| } // namespace arm_compute |