| /* |
| * 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 "Winograd.h" |
| |
| #include "tests/validation/Helpers.h" |
| #include "tests/validation/reference/Utils.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| namespace |
| { |
| template <typename T> |
| void winograd_input_transform3x3(const SimpleTensor<T> &src, SimpleTensor<T> &dst, const PadStrideInfo &conv_info) |
| { |
| TensorShape shape4x4(4u, 4u); |
| |
| // Simple tensor for the 4x4 input tile |
| SimpleTensor<T> src_tile{ shape4x4, src.data_type() }; |
| |
| // Simple tensor for the 4x4 temporary tile |
| SimpleTensor<T> tmp_tile{ shape4x4, src.data_type() }; |
| |
| // Simple tensor for the 4x4 output tile |
| SimpleTensor<T> dst_tile{ shape4x4, src.data_type() }; |
| |
| // Simple tensor for the transformation matrix |
| SimpleTensor<T> matrix{ shape4x4, src.data_type() }; |
| |
| // Simple tensor for the transformation matrix transposed |
| SimpleTensor<T> matrix_transposed{ shape4x4, src.data_type() }; |
| |
| const float matrix_values[] = { 1.f, 0.f, -1.f, 0.f, |
| 0.f, 1.f, 1.f, 0.f, |
| 0.f, -1.f, 1.f, 0.f, |
| 0.f, 1.f, 0.f, -1.f |
| }; |
| |
| for(int i = 0; i < matrix.num_elements(); ++i) |
| { |
| matrix[i] = matrix_values[i]; |
| } |
| |
| transpose_matrix(matrix, matrix_transposed); |
| |
| const int in_w = src.shape().x(); |
| const int in_h = src.shape().y(); |
| const int in_d = src.shape().z(); |
| const int num_batches = src.shape().total_size() / (in_w * in_h * in_d); |
| const int num_tiles_x = std::ceil((in_w - 2 + conv_info.pad_left() + conv_info.pad_right()) / 2.0f); |
| const int num_tiles_y = std::ceil((in_h - 2 + conv_info.pad_top() + conv_info.pad_bottom()) / 2.0f); |
| |
| ARM_COMPUTE_ERROR_ON((num_tiles_x * num_tiles_y) != static_cast<int>(dst.shape().y())); |
| |
| for(int b = 0; b < num_batches; ++b) |
| { |
| for(int z = 0; z < in_d; ++z) |
| { |
| for(int y = 0; y < num_tiles_y; ++y) |
| { |
| for(int x = 0; x < num_tiles_x; ++x) |
| { |
| int xi = x * 2 - conv_info.pad_left(); |
| int yi = y * 2 - conv_info.pad_top(); |
| |
| // Get the 4x4 tile from the input tensor |
| get_tile(src, src_tile, Coordinates(xi, yi, z, b)); |
| |
| // Compute the transformation |
| matrix_multiply(matrix, src_tile, tmp_tile); |
| matrix_multiply(tmp_tile, matrix_transposed, dst_tile); |
| |
| // Store the 4x4 output tile across the 16 channels |
| for(int i = 0; i < 16; ++i) |
| { |
| int xo = z; |
| int yo = x + y * num_tiles_x; |
| dst[coords2index(dst.shape(), Coordinates(xo, yo, i, b))] = dst_tile[i]; |
| } |
| } |
| } |
| } |
| } |
| } |
| } // namespace |
| |
| template <typename T> |
| SimpleTensor<T> winograd_input_transform(const SimpleTensor<T> &src, const TensorShape &dst_shape, const PadStrideInfo &conv_info, const Size2D &kernel_dims) |
| { |
| ARM_COMPUTE_ERROR_ON(kernel_dims.width != kernel_dims.height); |
| ARM_COMPUTE_ERROR_ON(src.data_layout() != DataLayout::NCHW); |
| |
| SimpleTensor<T> dst{ dst_shape, src.data_type() }; |
| |
| switch(kernel_dims.width) |
| { |
| case 3: |
| winograd_input_transform3x3(src, dst, conv_info); |
| break; |
| default: |
| ARM_COMPUTE_ERROR("Only 3x3 kernels are supported"); |
| } |
| |
| return dst; |
| } |
| |
| template SimpleTensor<float> winograd_input_transform(const SimpleTensor<float> &src, const TensorShape &dst_shape, const PadStrideInfo &conv_info, const Size2D &kernel_dims); |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |