test exconv layerGrad and im2col

paddle/function/Im2ColTest.cpp

@@ -29,14 +29,16 @@ void TestIm2ColFunctor() {
           for (size_t filterWidth : {3, 7}) {
             for (size_t stride : {1, 2}) {
               for (size_t padding : {0, 1}) {
-                if (inputHeight <= filterHeight || inputWidth <= filterWidth)
+                for (size_t dilation : {1, 3}) {
+                  size_t filterSizeH = (filterHeight - 1) * dilation + 1;
+                  size_t filterSizeW = (filterWidth - 1) * dilation + 1;
+                  if (inputHeight <= filterSizeH || inputWidth <= filterSizeW)
                     break;
-                if (padding >= filterHeight || padding >= filterWidth) break;
+                  if (padding >= filterSizeH || padding >= filterSizeW) break;
                   size_t outputHeight =
-                    (inputHeight - filterHeight + 2 * padding + stride) /
-                    stride;
+                      (inputHeight - filterSizeH + 2 * padding) / stride + 1;
                   size_t outputWidth =
-                    (inputWidth - filterWidth + 2 * padding + stride) / stride;
+                      (inputWidth - filterSizeW + 2 * padding) / stride + 1;
 
                   TensorShape imShape =
                       TensorShape({channels, inputHeight, inputWidth});
@@ -53,10 +55,14 @@ void TestIm2ColFunctor() {
 
                   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);
+                  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);
 
@@ -69,7 +75,9 @@ void TestIm2ColFunctor() {
                           stride,
                           stride,
                           padding,
-                        padding);
+                          padding,
+                          dilation,
+                          dilation);
                   im2Col2(input2->getData(),
                           imShape,
                           output2->getData(),
@@ -77,7 +85,9 @@ void TestIm2ColFunctor() {
                           stride,
                           stride,
                           padding,
-                        padding);
+                          padding,
+                          dilation,
+                          dilation);
 
                   // The transposition of the result of ColFormat == kCFO
                   // is equal to the result of ColFormat == kOCF.
@@ -87,6 +97,7 @@ void TestIm2ColFunctor() {
 
                   Col2ImFunctor<kCFO, Device, T> col2Im1;
                   Col2ImFunctor<kOCF, Device, T> col2Im2;
+
                   col2Im1(input1->getData(),
                           imShape,
                           output1->getData(),
@@ -94,7 +105,9 @@ void TestIm2ColFunctor() {
                           stride,
                           stride,
                           padding,
-                        padding);
+                          padding,
+                          dilation,
+                          dilation);
                   col2Im2(input2->getData(),
                           imShape,
                           output2->getData(),
@@ -102,8 +115,9 @@ void TestIm2ColFunctor() {
                           stride,
                           stride,
                           padding,
-                        padding);
-
+                          padding,
+                          dilation,
+                          dilation);
                   autotest::TensorCheckErr(*input1, *input2);
                 }
               }
@@ -112,6 +126,7 @@ void TestIm2ColFunctor() {
         }
       }
     }
+  }
 }
 
 TEST(Im2ColFunctor, CPU) { TestIm2ColFunctor<DEVICE_TYPE_CPU, float>(); }

paddle/gserver/tests/test_LayerGrad.cpp

@@ -434,7 +434,7 @@ void testConvLayer(const string& type, bool trans, bool useGpu) {
   config.layerConfig.set_partial_sum(1);
   config.layerConfig.set_shared_biases(true);
 
-  int dilation = 1;
+  int dilation = 2;
   if (type == "cudnn_conv") {
 #if CUDNN_VERSION >= 6000
     dilation = 2;