| /* |
| * Copyright (c) 2018-2019 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/NEConvertFullyConnectedWeightsKernel.h" |
| |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/Types.h" |
| |
| namespace arm_compute |
| { |
| NEConvertFullyConnectedWeightsKernel::NEConvertFullyConnectedWeightsKernel() |
| : _input(nullptr), _output(nullptr), _factor1(0), _factor2(0) |
| { |
| } |
| |
| void NEConvertFullyConnectedWeightsKernel::configure(const ITensor *input, ITensor *output, const TensorShape &original_input_shape, |
| DataLayout data_layout) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| |
| // Output tensor auto initialisation if not yet initialized |
| auto_init_if_empty(*output->info(), *input->info()->clone()); |
| |
| ARM_COMPUTE_ERROR_THROW_ON(NEConvertFullyConnectedWeightsKernel::validate(input->info(), output->info(), original_input_shape, data_layout)); |
| |
| _input = input; |
| _output = output; |
| |
| const DataLayout input_data_layout = (data_layout == DataLayout::NCHW) ? DataLayout::NHWC : DataLayout::NCHW; |
| |
| const int width_idx = get_data_layout_dimension_index(input_data_layout, DataLayoutDimension::WIDTH); |
| const int height_idx = get_data_layout_dimension_index(input_data_layout, DataLayoutDimension::HEIGHT); |
| const int channel_idx = get_data_layout_dimension_index(input_data_layout, DataLayoutDimension::CHANNEL); |
| |
| const unsigned int num_elems_per_input_plane = original_input_shape[width_idx] * original_input_shape[height_idx]; |
| const unsigned int num_channels = original_input_shape[channel_idx]; |
| |
| _factor1 = (data_layout == DataLayout::NCHW) ? num_elems_per_input_plane : num_channels; |
| _factor2 = (data_layout == DataLayout::NCHW) ? num_channels : num_elems_per_input_plane; |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*input->info(), Steps()); |
| INEKernel::configure(win); |
| } |
| |
| Status NEConvertFullyConnectedWeightsKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const TensorShape &original_input_shape, |
| DataLayout data_layout) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); |
| //Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use NEON FP16 instructions. |
| ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() != 2); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) != original_input_shape.total_size_lower(3)); |
| ARM_COMPUTE_RETURN_ERROR_ON(data_layout == DataLayout::UNKNOWN); |
| |
| // Checks performed when output is configured |
| if((output != nullptr) && (output->total_size() != 0)) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); |
| } |
| |
| return Status{}; |
| } |
| |
| template <typename T> |
| void NEConvertFullyConnectedWeightsKernel::run_convert_fc_weights(const Window &window) |
| { |
| const unsigned int dst_stride_x = _output->info()->strides_in_bytes().x(); |
| const unsigned int dst_stride_y = _output->info()->strides_in_bytes().y(); |
| |
| Iterator input(_input, window); |
| Iterator output(_output, window); |
| |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| *reinterpret_cast<T *>(output.ptr() + id.x() * dst_stride_x + (id.y() % _factor1 * _factor2 + id.y() / _factor1) * dst_stride_y) = *reinterpret_cast<T *>(input.ptr()); |
| }, |
| input); |
| } |
| |
| void NEConvertFullyConnectedWeightsKernel::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); |
| |
| switch(_input->info()->element_size()) |
| { |
| case 1: |
| run_convert_fc_weights<uint8_t>(window); |
| break; |
| case 2: |
| run_convert_fc_weights<uint16_t>(window); |
| break; |
| case 4: |
| run_convert_fc_weights<uint32_t>(window); |
| break; |
| default: |
| ARM_COMPUTE_ERROR("Data type not supported."); |
| break; |
| } |
| } |
| } // namespace arm_compute |