| /* |
| * Copyright (c) 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/NEChannelShuffleLayerKernel.h" |
| |
| #include "arm_compute/core/CPP/Validate.h" |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.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" |
| |
| namespace arm_compute |
| { |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, unsigned int num_groups) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, |
| 1, |
| DataType::U8, DataType::S8, DataType::QASYMM8, |
| DataType::U16, DataType::S16, |
| DataType::U32, DataType::S32, |
| DataType::F16, DataType::F32); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NCHW, DataLayout::NHWC); |
| |
| const unsigned int channels = input->dimension(get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL)); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(num_groups < 2, "Channel shuffling with less than 2 groups would be inefficient"); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(num_groups == channels, "Channel shuffling with same number of groups as number of channels would be inefficient"); |
| ARM_COMPUTE_RETURN_ERROR_ON(num_groups > channels); // There cannot be more groups than channels |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG((channels % num_groups) != 0, "The number of channels must be a multiple of the number of groups"); |
| |
| // Checks performed when output is configured |
| if(output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); |
| } |
| |
| return Status{}; |
| } |
| void channel_shuffle_nhwc(const ITensor *input, ITensor *output, unsigned int num_groups, const Window &window) |
| { |
| const DataLayout data_layout = input->info()->data_layout(); |
| const unsigned int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); |
| |
| const size_t element_size = input->info()->element_size(); |
| const unsigned int K = input->info()->dimension(channel_idx) / num_groups; |
| const float rK = 1.f / K; |
| |
| Iterator in(input, window); |
| |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| // Shuffle channel |
| const unsigned int curr_channel = id.x(); |
| const unsigned int group_id = curr_channel * rK; |
| const unsigned int r = group_id * K; |
| const unsigned int channel_id = curr_channel - r; |
| |
| // Calculate output coordinates |
| Coordinates out_coords = id; |
| out_coords.set(Window::DimX, channel_id * num_groups + group_id); |
| std::copy_n(in.ptr(), element_size, output->ptr_to_element(out_coords)); |
| }, |
| in); |
| } |
| void channel_shuffle_nchw(const ITensor *input, ITensor *output, unsigned int num_groups, const Window &window) |
| { |
| Window win = window; |
| win.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| win.set(Window::DimY, Window::Dimension(0, 1, 1)); |
| |
| const DataLayout data_layout = input->info()->data_layout(); |
| const unsigned int width_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); |
| const unsigned int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); |
| |
| const unsigned int height = input->info()->tensor_shape().y(); |
| const size_t input_stride_y = input->info()->strides_in_bytes().y(); |
| const size_t output_stride_y = output->info()->strides_in_bytes().y(); |
| const size_t row_size = input->info()->dimension(width_idx) * input->info()->element_size(); |
| |
| const unsigned int K = input->info()->dimension(channel_idx) / num_groups; |
| const float rK = 1.f / K; |
| |
| Iterator in(input, win); |
| |
| execute_window_loop(win, [&](const Coordinates & id) |
| { |
| // Shuffle channel |
| const unsigned int curr_channel = id.z(); |
| const unsigned int group_id = curr_channel * rK; |
| const unsigned int r = group_id * K; |
| const unsigned int channel_id = curr_channel - r; |
| |
| // Calculate output coordinates |
| Coordinates out_coords = id; |
| out_coords.set(Window::DimZ, channel_id * num_groups + group_id); |
| const uint8_t *input_ptr = in.ptr(); |
| uint8_t *output_ptr = output->ptr_to_element(out_coords); |
| |
| // Copy plane |
| for(unsigned int y = 0; y < height; ++y) |
| { |
| std::copy_n(input_ptr, row_size, output_ptr); |
| input_ptr += input_stride_y; |
| output_ptr += output_stride_y; |
| } |
| }, |
| in); |
| } |
| } // namespace |
| |
| NEChannelShuffleLayerKernel::NEChannelShuffleLayerKernel() |
| : _input(nullptr), _output(nullptr), _num_groups() |
| { |
| } |
| |
| void NEChannelShuffleLayerKernel::configure(const ITensor *input, ITensor *output, unsigned int num_groups) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| |
| // Output tensor auto initialization if not yet initialized |
| auto_init_if_empty(*output->info(), *input->info()->clone()); |
| |
| _input = input; |
| _output = output; |
| _num_groups = num_groups; |
| |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), num_groups)); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*input->info(), Steps()); |
| |
| // The NEChannelShuffleLayerKernel doesn't need padding so update_window_and_padding() can be skipped |
| Coordinates coord; |
| coord.set_num_dimensions(output->info()->num_dimensions()); |
| output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape())); |
| |
| INEKernel::configure(win); |
| } |
| |
| Status NEChannelShuffleLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int num_groups) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, num_groups)); |
| return Status{}; |
| } |
| |
| void NEChannelShuffleLayerKernel::run(const Window &window, const ThreadInfo &info) |
| { |
| ARM_COMPUTE_UNUSED(info); |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); |
| |
| switch(_input->info()->data_layout()) |
| { |
| case DataLayout::NHWC: |
| channel_shuffle_nhwc(_input, _output, _num_groups, window); |
| break; |
| case DataLayout::NCHW: |
| channel_shuffle_nchw(_input, _output, _num_groups, window); |
| break; |
| default: |
| ARM_COMPUTE_ERROR("Unsupported data layout!"); |
| break; |
| } |
| } |
| } // namespace arm_compute |