/* * Copyright (c) 2019-2022 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/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/common/Registrars.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" #include "src/core/utils/helpers/bit_ops.h" #include "src/cpu/kernels/crop/list.h" namespace arm_compute { namespace { struct CropSelectorData { DataType dt; }; using CropSelectorPtr = std::add_pointer::type; using CropUKernelPtr = std::add_pointer::type; struct CropUKernel { const char *name; const CropSelectorPtr is_selected; CropUKernelPtr ukernel; }; static const CropUKernel available_kernels[] = { { "fp16_neon_crop", [](const CropSelectorData & data) { return data.dt == DataType::F16; }, REGISTER_FP16_NEON(arm_compute::cpu::fp16_in_bounds_crop_window) }, { "f32_neon_crop", [](const CropSelectorData & data) { return data.dt == DataType::F32; }, REGISTER_FP32_NEON(arm_compute::cpu::fp32_in_bounds_crop_window) }, { "u8_neon_crop", [](const CropSelectorData & data) { return data.dt == DataType::U8; }, REGISTER_INTEGER_NEON(arm_compute::cpu::u8_in_bounds_crop_window) }, { "u16_neon_crop", [](const CropSelectorData & data) { return data.dt == DataType::U16; }, REGISTER_INTEGER_NEON(arm_compute::cpu::u16_in_bounds_crop_window) }, { "u32_neon_crop", [](const CropSelectorData & data) { return data.dt == DataType::U32; }, REGISTER_INTEGER_NEON(arm_compute::cpu::u32_in_bounds_crop_window) }, { "s8_neon_crop", [](const CropSelectorData & data) { return data.dt == DataType::S8; }, REGISTER_INTEGER_NEON(arm_compute::cpu::s8_in_bounds_crop_window) }, { "s16_neon_crop", [](const CropSelectorData & data) { return data.dt == DataType::S16; }, REGISTER_INTEGER_NEON(arm_compute::cpu::s16_in_bounds_crop_window) }, { "s32_neon_crop", [](const CropSelectorData & data) { return data.dt == DataType::S32; }, REGISTER_INTEGER_NEON(arm_compute::cpu::s32_in_bounds_crop_window) }, }; /** Micro-kernel selector * * @param[in] data Selection data passed to help pick the appropriate micro-kernel * * @return A matching micro-kernel else nullptr */ const CropUKernel *get_implementation(const CropSelectorData &data) { for(const auto &uk : available_kernels) { if(uk.is_selected(data)) { return &uk; } } return nullptr; } 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(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 &rows_out_of_bounds, const std::array &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(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(row) < static_cast(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() { } 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; } 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); const auto *uk = get_implementation(CropSelectorData{ input->data_type() }); ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr); 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(_crop_boxes->ptr_to_element(Coordinates(1, _crop_box_ind))); const float y0 = *reinterpret_cast(_crop_boxes->ptr_to_element(Coordinates(0, _crop_box_ind))); const float x1 = *reinterpret_cast(_crop_boxes->ptr_to_element(Coordinates(3, _crop_box_ind))); const float y1 = *reinterpret_cast(_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(_input->info()->dimension(2)) ? std::min(static_cast(_start[1] - _input->info()->dimension(2) + 1), static_cast(_output->info()->dimension(2))) : 0; _rows_out_of_bounds[1] = _end[1] < 0 ? std::min(static_cast(-_end[1]), static_cast(_output->info()->dimension(2))) : 0; } else { _rows_out_of_bounds[0] = _start[1] < 0 ? std::min(static_cast(-_start[1]), static_cast(_output->info()->dimension(2))) : 0; _rows_out_of_bounds[1] = _end[1] >= static_cast(_input->info()->dimension(2)) ? std::min(static_cast(_end[1] - _input->info()->dimension(2) + 1), static_cast(_output->info()->dimension(2))) : 0; } if(is_width_flipped) { _cols_out_of_bounds[0] = _start[0] >= static_cast(_input->info()->dimension(1)) ? std::min(static_cast(_start[0] - _input->info()->dimension(1) + 1), static_cast(_output->info()->dimension(1))) : 0; _cols_out_of_bounds[1] = _end[0] < 0 ? std::min(static_cast(-_end[0]), static_cast(_output->info()->dimension(1))) : 0; } else { _cols_out_of_bounds[0] = _start[0] < 0 ? std::min(static_cast(-_start[0]), static_cast(_output->info()->dimension(1))) : 0; _cols_out_of_bounds[1] = _end[0] >= static_cast(_input->info()->dimension(1)) ? std::min(static_cast(_end[0] - _input->info()->dimension(1) + 1), static_cast(_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()); const auto *uk = get_implementation(CropSelectorData{ _input->info()->data_type() }); uint32_t batch_index = *(reinterpret_cast(_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, uk->ukernel, _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