| /* |
| * 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/NEDepthwiseVectorToTensorKernel.h" |
| |
| #include "arm_compute/core/AccessWindowTranspose.h" |
| #include "arm_compute/core/Coordinates.h" |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/NEON/INEKernel.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/TensorShape.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| |
| using namespace arm_compute; |
| |
| template <typename T> |
| void NEDepthwiseVectorToTensorKernel::vector_to_tensor(const Window &window) |
| { |
| // const int input_w = _input->info()->dimension(0); |
| const int output_stride_x = _output->info()->strides_in_bytes().x(); |
| const int output_stride_y = _output->info()->strides_in_bytes().y(); |
| const int output_stride_z = _output->info()->strides_in_bytes().z(); |
| |
| // Setup output window |
| Window window_out(window); |
| window_out.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| window_out.set(Window::DimY, Window::Dimension(0, 0, 0)); |
| window_out.set(Window::DimZ, Window::Dimension(0, 0, 0)); |
| |
| Iterator in(_input, window); |
| Iterator out(_output, window_out); |
| |
| const int patch_size = _conv_dims.first * _conv_dims.second; |
| |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| const int z = id.x() / patch_size; |
| const int index2D = id.x() - z * patch_size; |
| |
| auto input_ptr = reinterpret_cast<T *>(in.ptr()); |
| auto output_ptr = reinterpret_cast<T *>(out.ptr() + index2D % _conv_dims.first * output_stride_x + index2D / _conv_dims.first * output_stride_y + z * output_stride_z); |
| |
| *output_ptr = *input_ptr; |
| }, |
| in, out); |
| } |
| |
| NEDepthwiseVectorToTensorKernel::NEDepthwiseVectorToTensorKernel() |
| : _func(nullptr), _input(nullptr), _output(nullptr), _conv_dims() |
| { |
| } |
| |
| void NEDepthwiseVectorToTensorKernel::configure(const ITensor *input, ITensor *output, size_t conv_w, size_t conv_h) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::S32, DataType::F16, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_NULLPTR(output); |
| |
| TensorShape output_shape = input->info()->tensor_shape(); |
| output_shape.set(0, conv_w); |
| output_shape.set(1, conv_h); |
| output_shape.set(2, input->info()->tensor_shape()[0] / (conv_w * conv_h)); |
| |
| // Output auto inizialitation if not yet initialized |
| auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); |
| |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); |
| |
| _input = input; |
| _output = output; |
| _conv_dims = std::pair<size_t, size_t>(conv_w, conv_h); |
| |
| // Set appropriate function to run |
| switch(input->info()->data_type()) |
| { |
| case DataType::QASYMM8: |
| _func = &NEDepthwiseVectorToTensorKernel::vector_to_tensor<uint8_t>; |
| break; |
| case DataType::S32: |
| _func = &NEDepthwiseVectorToTensorKernel::vector_to_tensor<int32_t>; |
| break; |
| case DataType::F16: |
| _func = &NEDepthwiseVectorToTensorKernel::vector_to_tensor<half>; |
| break; |
| case DataType::F32: |
| _func = &NEDepthwiseVectorToTensorKernel::vector_to_tensor<float>; |
| break; |
| default: |
| ARM_COMPUTE_ERROR("Unsupported data type"); |
| } |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*input->info(), Steps()); |
| // The NEDepthwisevectorToTensorKernel doesn't need padding so update_window_and_padding() can be skipped |
| output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape())); |
| |
| INEKernel::configure(win); |
| } |
| |
| void NEDepthwiseVectorToTensorKernel::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); |
| |
| if(_func != nullptr) |
| { |
| (this->*_func)(window); |
| } |
| } |