Merge pull request #4415 from jacquesqiao/fix-SoftmaxWithCrossEntropyOp

fix the conflicts of SoftmaxWithCrossEntropyOp with the latest dev branch.

paddle/operators/math/softmax.cc

@@ -18,7 +18,7 @@ namespace paddle {
 namespace operators {
 namespace math {
 
-template class SoftmaxFunctor<platform::GPUPlace, float>;
+template class SoftmaxFunctor<platform::CPUPlace, float>;
 
 }  // namespace math
 }  // namespace operators

paddle/operators/softmax_with_cross_entropy_op.cc

@@ -82,40 +82,38 @@ class SoftmaxWithCrossEntropyOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
  protected:
-  void InferShape(const framework::InferShapeContext& ctx) const override {
-    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Logits"),
-                            "Input(Logits) should be not null.");
-    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Label"),
-                            "Input(Label) should be not null.");
-
-    PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Softmax"),
-                            "Output(Softmax) should be not null.");
-    PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Loss"),
-                            "Output(Loss) should be not null.");
-
-    const Tensor* logits = ctx.Input<Tensor>("Logits");
-    const Tensor* labels = ctx.Input<Tensor>("Label");
+  void InferShape(framework::InferShapeContextBase* ctx) const override {
+    PADDLE_ENFORCE(ctx->HasInput("Logits"),
+                   "Input(Logits) should be not null.");
+    PADDLE_ENFORCE(ctx->HasInput("Label"), "Input(Label) should be not null.");
+
+    PADDLE_ENFORCE(ctx->HasOutput("Softmax"),
+                   "Output(Softmax) should be not null.");
+    PADDLE_ENFORCE(ctx->HasOutput("Loss"), "Output(Loss) should be not null.");
+
+    auto logits_dims = ctx->GetInputDim("Logits");
+    auto labels_dims = ctx->GetInputDim("Label");
     PADDLE_ENFORCE_EQ(
-        logits->dims().size(), 2UL,
+        logits_dims.size(), 2UL,
         "The input of softmax_with_cross_entropy should be a 2-D tensor.");
-    PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("Label")->dims().size(), 2UL,
+    PADDLE_ENFORCE_EQ(labels_dims.size(), 2UL,
                       "The labels should be a 2-D tensor.");
 
-    if (ctx.Attr<bool>("softLabel")) {
-      PADDLE_ENFORCE_EQ(logits->dims()[1], labels->dims()[1],
+    if (ctx->Attrs().Get<bool>("softLabel")) {
+      PADDLE_ENFORCE_EQ(logits_dims[1], labels_dims[1],
                         "If Attr(softLabel) == true, the 2nd dimension of "
                         "Input(X) and Input(Label) should be equal.");
     } else {
-      PADDLE_ENFORCE_EQ(labels->dims()[1], 1UL,
+      PADDLE_ENFORCE_EQ(labels_dims[1], 1UL,
                         "If Attr(softLabel) == false, the 2nd dimension of "
                         "Input(Label) should be 1.");
     }
 
-    ctx.Output<framework::Tensor>("Softmax")->Resize(logits->dims());
-    ctx.Output<framework::Tensor>("Loss")->Resize({logits->dims()[0], 1});
+    ctx->SetOutputDim("Softmax", logits_dims);
+    ctx->SetOutputDim("Loss", {logits_dims[0], 1});
 
-    ctx.ShareLoD("Logits", /*->*/ "Softmax");
-    ctx.ShareLoD("Logits", /*->*/ "Loss");
+    ctx->ShareLoD("Logits", /*->*/ "Softmax");
+    ctx->ShareLoD("Logits", /*->*/ "Loss");
   }
 };
 
@@ -124,33 +122,32 @@ class SoftmaxWithCrossEntropyOpGrad : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
  protected:
-  void InferShape(const framework::InferShapeContext& ctx) const override {
-    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Loss")),
-                            "Input(Loss@Grad) should not be null.");
-    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Softmax"),
-                            "Input(Softmax) should be not null.");
-    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Label"),
-                            "Input(Label) should be not null.");
-    PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar(framework::GradVarName("Logits")),
-                            "Output(Logits@Grad) should be not null.");
-
-    const Tensor* softmax = ctx.Input<Tensor>("Softmax");
-    const Tensor* labels = ctx.Input<Tensor>("Label");
-    PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("Label")->dims().size(), 2UL,
+  void InferShape(framework::InferShapeContextBase* ctx) const override {
+    PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Loss")),
+                   "Input(Loss@Grad) should not be null.");
+    PADDLE_ENFORCE(ctx->HasInput("Softmax"),
+                   "Input(Softmax) should be not null.");
+    PADDLE_ENFORCE(ctx->HasInput("Label"), "Input(Label) should be not null.");
+    PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("Logits")),
+                   "Output(Logits@Grad) should be not null.");
+
+    auto softmax_dims = ctx->GetInputDim("Softmax");
+    auto labels_dims = ctx->GetInputDim("Label");
+    PADDLE_ENFORCE_EQ(labels_dims.size(), 2UL,
                       "The labels should be a 2-D tensor.");
 
-    if (ctx.Attr<bool>("softLabel")) {
-      PADDLE_ENFORCE_EQ(softmax->dims()[1], labels->dims()[1],
+    if (ctx->Attrs().Get<bool>("softLabel")) {
+      PADDLE_ENFORCE_EQ(softmax_dims[1], labels_dims[1],
                         "When Attr(softLabel) == true, the 2nd dimension of "
                         "Input(X) and Input(Label) should be equal.");
     } else {
-      PADDLE_ENFORCE_EQ(labels->dims()[1], 1UL,
+      PADDLE_ENFORCE_EQ(labels_dims[1], 1UL,
                         "When Attr(softLabel) == false, the 2nd dimension of "
                         "Input(Label) should be 1.");
     }
 
-    ctx.Output<framework::LoDTensor>(framework::GradVarName("Logits"))
-        ->Resize(ctx.Input<Tensor>("Softmax")->dims());
+    ctx->SetOutputDim(framework::GradVarName("Logits"),
+                      ctx->GetInputDim("Softmax"));
   }
 };