| /* |
| * Copyright (c) 2017 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 "DepthwiseConvolution.h" |
| |
| #include "ConvolutionLayer.h" |
| #include "TensorElementAt.h" |
| |
| #include "tests/validation_new/Helpers.h" |
| #include "tests/validation_new/half.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| /** Perform a depthwise convolution |
| * |
| * - Three dimensions tensors |
| * - Third dimention is number of channels |
| * - Depths of input tensor and filter are equals |
| * - Padding, stride and output shape "match" |
| * |
| */ |
| template <typename T> |
| SimpleTensor<T> depthwise_convolution(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const TensorShape &dst_shape, const PadStrideInfo &conv_info) |
| { |
| // Create reference |
| SimpleTensor<T> dst{ dst_shape, src.data_type(), 1, src.fixed_point_position() }; |
| |
| // Compute reference |
| const size_t filter_width = weights.shape().x(); |
| const size_t filter_height = weights.shape().y(); |
| const size_t filter_plane = filter_width * filter_height; |
| const size_t input_width = src.shape().x(); |
| const size_t input_height = src.shape().y(); |
| const size_t input_depth = src.shape().z(); |
| |
| const size_t filter_half_size = filter_width / 2; |
| const size_t pad_x = std::min(filter_half_size, static_cast<size_t>(conv_info.pad().first)); |
| const size_t pad_y = std::min(filter_half_size, static_cast<size_t>(conv_info.pad().second)); |
| const size_t minimum_x = -pad_x + filter_half_size; |
| const size_t minimum_y = -pad_y + filter_half_size; |
| |
| int out_pos = 0; |
| for(size_t z = 0; z < input_depth; ++z) |
| { |
| for(size_t y = minimum_y; y < input_height + pad_y - filter_half_size; y += conv_info.stride().second) |
| { |
| for(size_t x = minimum_x; x < input_width + pad_x - filter_half_size; x += conv_info.stride().first) |
| { |
| Coordinates coords(static_cast<int>(x), static_cast<int>(y), static_cast<int>(z)); |
| size_t filter_offset = filter_plane * z; |
| |
| T val = 0; |
| for(int j = y - filter_half_size; j <= static_cast<int>(y + filter_half_size); ++j) |
| { |
| for(int i = x - filter_half_size; i <= static_cast<int>(x + filter_half_size); ++i) |
| { |
| coords.set(0, i); |
| coords.set(1, j); |
| val += *(weights.data() + filter_offset) * tensor_elem_at(src, coords, BorderMode::CONSTANT, 0.f); |
| ++filter_offset; |
| } |
| } |
| coords.set(0, x); |
| coords.set(1, y); |
| dst[out_pos++] = saturate_cast<T>(val); |
| } |
| } |
| } |
| |
| return dst; |
| } |
| |
| template SimpleTensor<float> depthwise_convolution(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const TensorShape &dst_shape, const PadStrideInfo &conv_info); |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |