pass test_recognize_digits

paddle/fluid/operators/conv_op.cc

@@ -60,8 +60,9 @@ void ConvOp::InferShape(framework::InferShapeContext* ctx) const {
                    "Due to the settings of paddings, filter_dims and "
                    "dilations, the output size is less than 0, please check "
                    "again.");
-    output_shape.push_back(OutputSize(in_dims[i + 2], filter_dims[i + 2],
-                                      dilations[i], paddings[i], strides[i]));
+    output_shape.push_back(ConvOutputSize(in_dims[i + 2], filter_dims[i + 2],
+                                          dilations[i], paddings[i],
+                                          strides[i]));
   }
   ctx->SetOutputDim("Output", framework::make_ddim(output_shape));
   ctx->ShareLoD("Input", "Output");

paddle/fluid/operators/conv_op.h

@@ -28,8 +28,8 @@ using Tensor = framework::Tensor;
 
 // Base convolution operator definations for other conv
 // like operators to reuse the implementation.
-inline int OutputSize(int input_size, int filter_size, int dilation,
-                      int padding, int stride) {
+inline int ConvOutputSize(int input_size, int filter_size, int dilation,
+                          int padding, int stride) {
   const int dkernel = dilation * (filter_size - 1) + 1;
   const int output_size = (input_size + 2 * padding - dkernel) / stride + 1;
   return output_size;

paddle/fluid/operators/parallel_do_op.cc

@@ -256,6 +256,10 @@ class ParallelDoGradOp : public framework::OperatorBase {
       }
     }
     for (auto &s : Outputs(framework::GradVarName(kParameters))) {
+      if (s == "@EMPTY@") {
+        continue;
+      }
+      VLOG(3) << "Moving " << s;
       CopyOrShare(*sub_scopes[0]->FindVar(s), place, scope.FindVar(s));
     }
     WaitOnPlaces(places);
@@ -266,6 +270,9 @@ class ParallelDoGradOp : public framework::OperatorBase {
                       const std::vector<framework::Scope *> &sub_scopes,
                       const platform::PlaceList &places) const {
     for (auto &s : Outputs(framework::GradVarName(kParameters))) {
+      if (s == "@EMPTY@") {
+        continue;
+      }
       VLOG(3) << "Accumulating " << s;
       if (s == framework::kEmptyVarName) continue;
       std::string tmp_name;