| /* |
| * Copyright (c) 2017, 2018 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/NEDepthConcatenateLayerKernel.h" |
| |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/IAccessWindow.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/NEON/NEFixedPoint.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| |
| #include <arm_neon.h> |
| #include <cstdint> |
| |
| using namespace arm_compute; |
| |
| namespace |
| { |
| // Overloads of 128-bit vector loads |
| uint8x16_t loadq(const uint8_t *ptr) |
| { |
| return vld1q_u8(ptr); |
| } |
| uint16x8_t loadq(const uint16_t *ptr) |
| { |
| return vld1q_u16(ptr); |
| } |
| uint32x4_t loadq(const uint32_t *ptr) |
| { |
| return vld1q_u32(ptr); |
| } |
| // Overloads of 128-bit vector stores |
| void storeq(uint8_t *ptr, uint8x16_t val) |
| { |
| return vst1q_u8(ptr, val); |
| } |
| void storeq(uint16_t *ptr, uint16x8_t val) |
| { |
| return vst1q_u16(ptr, val); |
| } |
| void storeq(uint32_t *ptr, uint32x4_t val) |
| { |
| return vst1q_u32(ptr, val); |
| } |
| |
| template <typename T> |
| void depth_concat(const ITensor *in, ITensor *out, std::pair<int, int> start_xy, int depth_offset, const Window &window) |
| { |
| const int start_x = start_xy.first; |
| const int start_y = start_xy.second; |
| |
| // Offset input |
| const int input_offset_to_first_elements_in_bytes = in->info()->offset_first_element_in_bytes() - start_x * in->info()->strides_in_bytes()[0] - start_y * in->info()->strides_in_bytes()[1]; |
| uint8_t *input_ptr = in->buffer() + input_offset_to_first_elements_in_bytes; |
| |
| // Offset output |
| const unsigned int output_offset_to_first_elements_in_bytes = out->info()->offset_first_element_in_bytes() + depth_offset * out->info()->strides_in_bytes()[2]; |
| uint8_t *output_ptr = out->buffer() + output_offset_to_first_elements_in_bytes; |
| |
| Iterator input(in, window); |
| Iterator output(out, window); |
| |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| const auto in_ptr = reinterpret_cast<const T *>(input_ptr + input.offset()); |
| const auto out_ptr = reinterpret_cast<T *>(output_ptr + output.offset()); |
| |
| storeq(out_ptr, loadq(in_ptr)); |
| }, |
| input, output); |
| } |
| } // namespace |
| |
| NEDepthConcatenateLayerKernel::NEDepthConcatenateLayerKernel() |
| : _func(nullptr), _input(nullptr), _output(nullptr), _top_bottom(0), _left_right(0), _depth_offset(0) |
| { |
| } |
| |
| BorderSize NEDepthConcatenateLayerKernel::border_size() const |
| { |
| return BorderSize(_top_bottom, _left_right); |
| } |
| |
| void NEDepthConcatenateLayerKernel::configure(const ITensor *input, unsigned int depth_offset, ITensor *output) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); |
| ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) + depth_offset > output->info()->dimension(2)); |
| ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) > output->info()->dimension(0)); |
| ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) > output->info()->dimension(1)); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(3, input, output); |
| |
| // The gaps between the two lowest dimensions of input and output need to be divisible by 2 |
| // Otherwise it is not clear how the padding should be added onto the input tensor |
| ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) - input->info()->dimension(0)) % 2); |
| ARM_COMPUTE_ERROR_ON((output->info()->dimension(1) - input->info()->dimension(1)) % 2); |
| |
| _func = nullptr; |
| _input = input; |
| _output = output; |
| _depth_offset = depth_offset; |
| _left_right = (output->info()->dimension(0) - input->info()->dimension(0)) / 2; |
| _top_bottom = (output->info()->dimension(1) - input->info()->dimension(1)) / 2; |
| |
| switch(input->info()->data_type()) |
| { |
| case DataType::QS8: |
| _func = &depth_concat<uint8_t>; |
| break; |
| case DataType::QS16: |
| case DataType::F16: |
| _func = &depth_concat<uint16_t>; |
| break; |
| case DataType::F32: |
| _func = &depth_concat<uint32_t>; |
| break; |
| default: |
| ARM_COMPUTE_ERROR("Unsupported data type."); |
| } |
| |
| const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); |
| const unsigned int num_elems_read_per_iteration = 16 / input->info()->element_size(); |
| const unsigned int num_rows_read_per_iteration = 1; |
| |
| // The window needs to be based on input as we copy all the depths of input |
| Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration)); |
| win.set(Window::DimZ, Window::Dimension(0, input->info()->tensor_shape().z(), 1)); |
| |
| AccessWindowRectangle input_access(input->info(), -_left_right, -_top_bottom, num_elems_read_per_iteration, num_rows_read_per_iteration); |
| AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); |
| update_window_and_padding(win, input_access, output_access); |
| output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); |
| |
| INEKernel::configure(win); |
| } |
| |
| void NEDepthConcatenateLayerKernel::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); |
| |
| (*_func)(_input, _output, std::make_pair(_left_right, _top_bottom), _depth_offset, window); |
| } |