| /* |
| * 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 "Im2Col.h" |
| |
| #include "arm_compute/core/Types.h" |
| #include "tests/validation/Helpers.h" |
| #include "tests/validation/reference/Utils.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| template <typename T> |
| void im2col_nchw(const SimpleTensor<T> &src, SimpleTensor<T> &dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int num_groups) |
| { |
| ARM_COMPUTE_ERROR_ON(src.data_layout() != DataLayout::NCHW); |
| const int stride_x = conv_info.stride().first; |
| const int stride_y = conv_info.stride().second; |
| const int kernel_width = kernel_dims.width; |
| const int kernel_height = kernel_dims.height; |
| const int pad_x = conv_info.pad().first; |
| const int pad_y = conv_info.pad().second; |
| const int src_width = src.shape().x(); |
| const int src_height = src.shape().y(); |
| const int src_channels = src.shape().z(); |
| const int batches = src.shape().total_size_upper(3); |
| const int dst_height = dst.shape().y(); |
| const int pad_val = is_data_type_quantized_asymmetric(src.data_type()) ? src.quantization_info().offset : 0; |
| int dst_idx = 0; |
| |
| // Compute width and height of the convolved tensors |
| std::pair<unsigned int, unsigned int> convolved_dims = scaled_dimensions(src_width, src_height, kernel_dims.width, kernel_dims.height, conv_info); |
| |
| for(int b = 0; b < batches; ++b) |
| { |
| for(int g = 0; g < static_cast<int>(num_groups); ++g) |
| { |
| const int first_group_ch = g * (src_channels / num_groups); |
| const int last_group_ch = (g + 1) * (src_channels / num_groups); |
| |
| for(int yo = 0; yo < dst_height; ++yo) |
| { |
| // Compute input spatial coordinates |
| const int xi = (yo % convolved_dims.first) * stride_x; |
| const int yi = (yo / convolved_dims.first) * stride_y; |
| |
| for(int ci = first_group_ch; ci < last_group_ch; ++ci) |
| { |
| for(int yk = 0; yk < kernel_height; ++yk) |
| { |
| for(int xk = 0; xk < kernel_width; ++xk) |
| { |
| dst[dst_idx++] = tensor_elem_at(src, Coordinates(xi + xk - pad_x, yi + yk - pad_y, ci, b), BorderMode::CONSTANT, static_cast<T>(pad_val)); |
| } |
| } |
| } |
| |
| if(has_bias) |
| { |
| dst[dst_idx++] = static_cast<T>(1); |
| } |
| } |
| } |
| } |
| } |
| |
| template <typename T> |
| void im2col_nhwc(const SimpleTensor<T> &src, SimpleTensor<T> &dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias) |
| { |
| ARM_COMPUTE_ERROR_ON(src.data_layout() != DataLayout::NHWC); |
| const int stride_x = conv_info.stride().first; |
| const int stride_y = conv_info.stride().second; |
| const int kernel_width = kernel_dims.width; |
| const int kernel_height = kernel_dims.height; |
| const int pad_x = conv_info.pad().first; |
| const int pad_y = conv_info.pad().second; |
| const int src_width = src.shape().y(); |
| const int src_height = src.shape().z(); |
| const int src_channels = src.shape().x(); |
| const int batches = src.shape().total_size_upper(3); |
| const int dst_width = has_bias ? dst.shape().x() - 1 : dst.shape().x(); |
| const int dst_height = dst.shape().y(); |
| const int pad_val = is_data_type_quantized_asymmetric(src.data_type()) ? src.quantization_info().offset : 0; |
| |
| // Compute width and height of the convolved tensors |
| std::pair<unsigned int, unsigned int> convolved_dims = scaled_dimensions(src_width, src_height, kernel_dims.width, kernel_dims.height, conv_info); |
| |
| for(int b = 0; b < batches; ++b) |
| { |
| for(int yo = 0; yo < dst_height; ++yo) |
| { |
| // Compute input spatial coordinates |
| const int xi = (yo % convolved_dims.first) * stride_x; |
| const int yi = (yo / convolved_dims.first) * stride_y; |
| |
| for(int ci = 0; ci < src_channels; ++ci) |
| { |
| for(int yk = 0; yk < kernel_height; ++yk) |
| { |
| for(int xk = 0; xk < kernel_width; ++xk) |
| { |
| dst[ci + (xk + yk * kernel_width) * src_channels + yo * dst.shape().x() + b * dst.shape().x() * dst.shape().y()] = tensor_elem_at(src, Coordinates(ci, xi + xk - pad_x, yi + yk - pad_y, b), |
| BorderMode::CONSTANT, static_cast<T>(pad_val)); |
| } |
| } |
| } |
| |
| if(has_bias) |
| { |
| dst[dst_width + yo * dst.shape().x() + b * dst.shape().x() * dst.shape().y()] = static_cast<T>(1); |
| } |
| } |
| } |
| } |
| |
| template <typename T> |
| void im2col(const SimpleTensor<T> &src, SimpleTensor<T> &dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const unsigned int num_groups) |
| { |
| switch(src.data_layout()) |
| { |
| case DataLayout::NCHW: |
| { |
| im2col_nchw(src, dst, kernel_dims, conv_info, has_bias, num_groups); |
| break; |
| } |
| case DataLayout::NHWC: |
| { |
| im2col_nhwc(src, dst, kernel_dims, conv_info, has_bias); |
| break; |
| } |
| default: |
| { |
| ARM_COMPUTE_ERROR("Not supported."); |
| break; |
| } |
| } |
| } |
| |
| template void im2col(const SimpleTensor<uint8_t> &src, SimpleTensor<uint8_t> &dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int num_groups); |
| template void im2col(const SimpleTensor<half> &src, SimpleTensor<half> &dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int num_groups); |
| template void im2col(const SimpleTensor<float> &src, SimpleTensor<float> &dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int num_groups); |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |