Sanghoon Lee | f47bfb9 | 2018-01-23 15:16:47 +0000 | [diff] [blame] | 1 | /* |
Michele Di Giorgio | d9eaf61 | 2020-07-08 11:12:57 +0100 | [diff] [blame] | 2 | * Copyright (c) 2017-2018 Arm Limited. |
Sanghoon Lee | f47bfb9 | 2018-01-23 15:16:47 +0000 | [diff] [blame] | 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #include "LocallyConnected.h" |
| 25 | |
| 26 | #include "tests/validation/Helpers.h" |
| 27 | #include "tests/validation/reference/Convolution3d.h" |
| 28 | #include "tests/validation/reference/Utils.h" |
| 29 | |
| 30 | #include "tests/framework/Asserts.h" |
| 31 | |
| 32 | namespace arm_compute |
| 33 | { |
| 34 | namespace test |
| 35 | { |
| 36 | namespace validation |
| 37 | { |
| 38 | namespace reference |
| 39 | { |
| 40 | template <typename T, typename TB> |
| 41 | SimpleTensor<T> locally_connected(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &output_shape, const PadStrideInfo &info) |
| 42 | { |
| 43 | // Create reference |
Vidhya Sudhan Loganathan | 014333d | 2018-07-02 09:13:49 +0100 | [diff] [blame] | 44 | SimpleTensor<T> dst{ output_shape, src.data_type(), 1, src.quantization_info() }; |
Sanghoon Lee | f47bfb9 | 2018-01-23 15:16:47 +0000 | [diff] [blame] | 45 | |
| 46 | // Compute reference |
| 47 | const int width_in = src.shape().x(); |
| 48 | const int height_in = src.shape().y(); |
| 49 | const int depth_in = src.shape().z(); |
| 50 | |
| 51 | const int width_out = dst.shape().x(); |
| 52 | const int height_out = dst.shape().y(); |
| 53 | const int depth_out = dst.shape().z(); |
| 54 | |
| 55 | const int width_weights = weights.shape().x(); |
| 56 | const int height_weights = weights.shape().y(); |
| 57 | const int depth_weights = weights.shape().z(); |
| 58 | |
| 59 | const int pad_left = info.pad_left(); |
| 60 | const int pad_top = info.pad_top(); |
| 61 | const int stride_xi = info.stride().first; |
| 62 | const int stride_yi = info.stride().second; |
| 63 | |
| 64 | auto output_wh = scaled_dimensions(width_in, height_in, width_weights, height_weights, info); |
| 65 | |
| 66 | const int start_xi = width_weights / 2 - pad_left; |
| 67 | const int start_yi = height_weights / 2 - pad_top; |
| 68 | const int end_xi = output_wh.first * stride_xi; |
| 69 | const int end_yi = output_wh.second * stride_yi; |
| 70 | const int num_batches = src.shape().total_size() / (width_in * height_in * depth_in); |
| 71 | |
| 72 | for(int r = 0; r < num_batches; ++r) |
| 73 | { |
| 74 | int count = 0; |
| 75 | for(int yi = start_yi; yi < start_yi + end_yi; yi += stride_yi) |
| 76 | { |
| 77 | for(int xi = start_xi; xi < start_xi + end_xi; xi += stride_xi) |
| 78 | { |
| 79 | for(int ofm = 0; ofm < depth_out; ++ofm) |
| 80 | { |
| 81 | // Compute input and output offsets |
| 82 | const int offset_in = r * width_in * height_in * depth_in; |
| 83 | const int xo = (xi - start_xi) / stride_xi; |
| 84 | const int yo = (yi - start_yi) / stride_yi; |
| 85 | const int offset_out = xo + yo * width_out + ofm * width_out * height_out + r * width_out * height_out * depth_out; |
| 86 | |
| 87 | ARM_COMPUTE_ASSERT(xo < width_out); |
| 88 | ARM_COMPUTE_ASSERT(yo < height_out); |
| 89 | |
| 90 | // Compute 3D convolution |
| 91 | convolution_3d::detail::convolution3d(src, weights, bias, dst, |
| 92 | offset_in, count * width_weights * height_weights * depth_weights, count, offset_out, |
| 93 | xi, yi, |
| 94 | width_in, height_in, depth_in, |
| 95 | width_weights, height_weights); |
| 96 | count++; |
| 97 | } |
| 98 | } |
| 99 | } |
| 100 | } |
| 101 | |
| 102 | return dst; |
| 103 | } |
| 104 | |
| 105 | // Locally Connected only supports F32 |
| 106 | template SimpleTensor<float> locally_connected(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &bias, const TensorShape &output_shape, |
| 107 | const PadStrideInfo &info); |
| 108 | } // namespace reference |
| 109 | } // namespace validation |
| 110 | } // namespace test |
| 111 | } // namespace arm_compute |