Add unit test for im2col.

paddle/function/CMakeLists.txt

@@ -33,6 +33,7 @@ if(WITH_GPU)
 endif()
 
 add_simple_unittest(ConvOpTest)
+add_simple_unittest(Im2ColTest)
 endif()
 
 add_style_check_target(paddle_function ${h_files})

paddle/function/Im2ColTest.cpp

@@ -0,0 +1,110 @@
+/* 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 {
+
+TEST(Im2ColFunctor, real) {
+  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}) {
+                if (inputHeight <= filterHeight || inputWidth <= filterWidth)
+                  break;
+                if (padding >= filterHeight || padding >= filterWidth) break;
+                size_t outputHeight =
+                    (inputHeight - filterHeight + 2 * padding + stride) /
+                    stride;
+                size_t outputWidth =
+                    (inputWidth - filterWidth + 2 * padding + stride) / stride;
+
+                TensorShape imShape =
+                    TensorShape({channels, inputHeight, inputWidth});
+                TensorShape colShape1 = TensorShape({channels,
+                                                     filterHeight,
+                                                     filterWidth,
+                                                     outputHeight,
+                                                     outputWidth});
+                TensorShape colShape2 = TensorShape({outputHeight,
+                                                     outputWidth,
+                                                     channels,
+                                                     filterHeight,
+                                                     filterWidth});
+
+                VectorPtr input = Vector::create(imShape.getElements(), false);
+                size_t height = channels * filterHeight * filterWidth;
+                size_t width = outputHeight * outputWidth;
+                MatrixPtr output1 = Matrix::create(height, width, false, false);
+                MatrixPtr output2 = Matrix::create(width, height, false, false);
+                Im2ColFunctor<kCFO, DEVICE_TYPE_CPU, real> im2col1;
+                Im2ColFunctor<kOCF, DEVICE_TYPE_CPU, real> im2col2;
+
+                input->uniform(0.001, 1);
+                im2col1(input->getData(),
+                        imShape,
+                        output1->getData(),
+                        colShape1,
+                        stride,
+                        stride,
+                        padding,
+                        padding);
+                im2col2(input->getData(),
+                        imShape,
+                        output2->getData(),
+                        colShape2,
+                        stride,
+                        stride,
+                        padding,
+                        padding);
+
+                MatrixPtr test;
+                output2->transpose(test, true);
+                autotest::TensorCheckErr(*output1, *test);
+              }
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+#if 0
+TEST(Col2ImFunctor, real) {
+  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}) {
+              }
+            }
+          }
+        }
+      }
+    }
+  }
+}
+#endif
+
+}  // namespace paddle