Im2ColTest.cpp 8.8 KB
Newer Older
H
hedaoyuan 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#include "Im2Col.h"
#include <gtest/gtest.h>
#include "Function.h"
#include "paddle/math/Matrix.h"
#include "paddle/math/tests/TensorCheck.h"

namespace paddle {

H
hedaoyuan 已提交
23 24
template <DeviceType Device, class T>
void TestIm2ColFunctor() {
H
hedaoyuan 已提交
25 26 27 28 29 30 31
  for (size_t channels : {1, 5, 32}) {
    for (size_t inputHeight : {5, 33, 100}) {
      for (size_t inputWidth : {5, 32, 96}) {
        for (size_t filterHeight : {1, 5}) {
          for (size_t filterWidth : {3, 7}) {
            for (size_t stride : {1, 2}) {
              for (size_t padding : {0, 1}) {
X
xzl 已提交
32 33 34
                for (size_t dilation : {1, 3}) {
                  size_t filterSizeH = (filterHeight - 1) * dilation + 1;
                  size_t filterSizeW = (filterWidth - 1) * dilation + 1;
35 36
                  if (inputHeight + 2 * padding < filterSizeH ||
                      inputWidth + 2 * padding < filterSizeW)
X
xzl 已提交
37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123
                    break;
                  if (padding >= filterSizeH || padding >= filterSizeW) break;
                  size_t outputHeight =
                      (inputHeight - filterSizeH + 2 * padding) / stride + 1;
                  size_t outputWidth =
                      (inputWidth - filterSizeW + 2 * padding) / stride + 1;

                  TensorShape imShape =
                      TensorShape({channels, inputHeight, inputWidth});
                  TensorShape colShape1 = TensorShape({channels,
                                                       filterHeight,
                                                       filterWidth,
                                                       outputHeight,
                                                       outputWidth});
                  TensorShape colShape2 = TensorShape({outputHeight,
                                                       outputWidth,
                                                       channels,
                                                       filterHeight,
                                                       filterWidth});

                  size_t height = channels * filterHeight * filterWidth;
                  size_t width = outputHeight * outputWidth;
                  VectorPtr input1 =
                      Vector::create(imShape.getElements(), false);
                  VectorPtr input2 =
                      Vector::create(imShape.getElements(), false);
                  MatrixPtr output1 =
                      Matrix::create(height, width, false, false);
                  MatrixPtr output2 =
                      Matrix::create(width, height, false, false);
                  input1->uniform(0.001, 1);
                  input2->copyFrom(*input1);

                  Im2ColFunctor<kCFO, Device, T> im2Col1;
                  Im2ColFunctor<kOCF, Device, T> im2Col2;
                  im2Col1(input1->getData(),
                          imShape,
                          output1->getData(),
                          colShape1,
                          stride,
                          stride,
                          padding,
                          padding,
                          dilation,
                          dilation);
                  im2Col2(input2->getData(),
                          imShape,
                          output2->getData(),
                          colShape2,
                          stride,
                          stride,
                          padding,
                          padding,
                          dilation,
                          dilation);

                  // The transposition of the result of ColFormat == kCFO
                  // is equal to the result of ColFormat == kOCF.
                  MatrixPtr test;
                  output2->transpose(test, true);
                  autotest::TensorCheckErr(*output1, *test);

                  Col2ImFunctor<kCFO, Device, T> col2Im1;
                  Col2ImFunctor<kOCF, Device, T> col2Im2;

                  col2Im1(input1->getData(),
                          imShape,
                          output1->getData(),
                          colShape1,
                          stride,
                          stride,
                          padding,
                          padding,
                          dilation,
                          dilation);
                  col2Im2(input2->getData(),
                          imShape,
                          output2->getData(),
                          colShape2,
                          stride,
                          stride,
                          padding,
                          padding,
                          dilation,
                          dilation);
                  autotest::TensorCheckErr(*input1, *input2);
                }
H
hedaoyuan 已提交
124 125 126 127 128 129 130 131
              }
            }
          }
        }
      }
    }
  }
}
H
hedaoyuan 已提交
132 133 134

TEST(Im2ColFunctor, CPU) { TestIm2ColFunctor<DEVICE_TYPE_CPU, float>(); }

135
#ifdef PADDLE_WITH_CUDA
H
hedaoyuan 已提交
136 137 138

TEST(Im2ColFunctor, GPU) { TestIm2ColFunctor<DEVICE_TYPE_GPU, float>(); }

H
hedaoyuan 已提交
139 140
#endif

H
hedaoyuan 已提交
141 142
template <class T>
void TestIm2ColMobileFunctor() {
H
hedaoyuan 已提交
143 144 145 146 147 148 149
  for (size_t channels : {32}) {
    for (size_t inputHeight : {33, 100}) {
      for (size_t inputWidth : {32, 96}) {
        for (size_t filterHeight : {5}) {
          for (size_t filterWidth : {7}) {
            for (size_t stride : {2}) {
              for (size_t padding : {1}) {
H
hedaoyuan 已提交
150
                for (size_t dilation : {1, 3}) {
H
hedaoyuan 已提交
151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202
                  size_t filterSizeH = (filterHeight - 1) * dilation + 1;
                  size_t filterSizeW = (filterWidth - 1) * dilation + 1;
                  if (inputHeight + 2 * padding < filterSizeH ||
                      inputWidth + 2 * padding < filterSizeW)
                    break;
                  if (padding >= filterSizeH || padding >= filterSizeW) break;
                  size_t outputHeight =
                      (inputHeight - filterSizeH + 2 * padding) / stride + 1;
                  size_t outputWidth =
                      (inputWidth - filterSizeW + 2 * padding) / stride + 1;

                  TensorShape imShape =
                      TensorShape({channels, inputHeight, inputWidth});
                  TensorShape colShape1 = TensorShape({channels,
                                                       filterHeight,
                                                       filterWidth,
                                                       outputHeight,
                                                       outputWidth});

                  size_t height = channels * filterHeight * filterWidth;
                  size_t width = outputHeight * outputWidth;
                  VectorPtr input1 =
                      Vector::create(imShape.getElements(), false);
                  VectorPtr input2 =
                      Vector::create(imShape.getElements(), false);
                  MatrixPtr output1 =
                      Matrix::create(height, width, false, false);
                  MatrixPtr output2 =
                      Matrix::create(height, width, false, false);
                  input1->uniform(0.001, 1);
                  input2->copyFrom(*input1);

                  Im2ColFunctor<kCFO, DEVICE_TYPE_CPU, T> im2Col1;
                  Im2ColMobileFunctor<T> im2Col2;
                  im2Col1(input1->getData(),
                          imShape,
                          output1->getData(),
                          colShape1,
                          stride,
                          stride,
                          padding,
                          padding,
                          dilation,
                          dilation);
                  im2Col2(input2->getData(),
                          imShape,
                          output2->getData(),
                          colShape1,
                          stride,
                          stride,
                          padding,
                          padding,
H
hedaoyuan 已提交
203 204
                          dilation,
                          dilation,
H
hedaoyuan 已提交
205
                          channels,
H
hedaoyuan 已提交
206
                          0,
H
hedaoyuan 已提交
207 208
                          outputHeight,
                          outputHeight * outputWidth);
H
hedaoyuan 已提交
209 210 211 212 213 214 215 216 217 218 219 220 221 222

                  autotest::TensorCheckEqual(*output1, *output2);
                }
              }
            }
          }
        }
      }
    }
  }
}

TEST(Im2ColFunctor, Mobile) { TestIm2ColMobileFunctor<float>(); }

H
hedaoyuan 已提交
223
}  // namespace paddle