Using LoDTensor for output.

paddle/operators/modified_huber_loss_op.cc

@@ -34,8 +34,8 @@ class ModifiedHuberLossOp : public framework::OperatorWithKernel {
     PADDLE_ENFORCE_EQ(x->dims().size(), 2, "The tensor rank of X must be 2.");
     PADDLE_ENFORCE_EQ(x->dims()[1], 1, "The 2nd dimension of X must be 1.");
 
-    context.Output<Tensor>("IntermediateVal")->Resize(x->dims());
-    context.Output<Tensor>("Out")->Resize({x->dims()[0], 1});
+    context.Output<framework::LoDTensor>("IntermediateVal")->Resize(x->dims());
+    context.Output<framework::LoDTensor>("Out")->Resize({x->dims()[0], 1});
   }
 };
 
@@ -80,7 +80,8 @@ class ModifiedHuberLossGradOp : public framework::OperatorWithKernel {
     auto* y = context.Input<Tensor>("Y");
     auto* intermediate_val = context.Input<Tensor>("IntermediateVal");
     auto* out_grad = context.Input<Tensor>(framework::GradVarName("Out"));
-    auto* x_grad = context.Output<Tensor>(framework::GradVarName("X"));
+    auto* x_grad =
+        context.Output<framework::LoDTensor>(framework::GradVarName("X"));
 
     PADDLE_ENFORCE_NOT_NULL(x, "X must be initialized.");
     PADDLE_ENFORCE_NOT_NULL(y, "Y must be initialized.");

paddle/operators/modified_huber_loss_op.h

@@ -52,8 +52,8 @@ class ModifiedHuberLossKernel : public framework::OpKernel {
   void Compute(const framework::ExecutionContext& context) const override {
     auto* in0 = context.Input<Tensor>("X");
     auto* in1 = context.Input<Tensor>("Y");
-    auto* out0 = context.Output<Tensor>("IntermediateVal");
-    auto* out1 = context.Output<Tensor>("Out");
+    auto* out0 = context.Output<framework::LoDTensor>("IntermediateVal");
+    auto* out1 = context.Output<framework::LoDTensor>("Out");
 
     out0->mutable_data<T>(context.GetPlace());
     out1->mutable_data<T>(context.GetPlace());
@@ -77,9 +77,11 @@ class ModifiedHuberLossGradCPUKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
     auto* in0 = context.Input<Tensor>("Y");
-    auto* in1 = context.Input<Tensor>("IntermediateVal");
-    auto* in2 = context.Input<Tensor>(framework::GradVarName("Out"));
-    auto* out0 = context.Output<Tensor>(framework::GradVarName("X"));
+    auto* in1 = context.Input<framework::LoDTensor>("IntermediateVal");
+    auto* in2 =
+        context.Input<framework::LoDTensor>(framework::GradVarName("Out"));
+    auto* out0 =
+        context.Output<framework::LoDTensor>(framework::GradVarName("X"));
 
     if (out0) {
       const T* y_ptr = in0->data<T>();