update enhance error message for Initializer, smooth_l1 (#23912)

* update enhance error message test=develop

* update details test=develop

paddle/fluid/operators/gaussian_random_op.cc

@@ -58,10 +58,12 @@ class GaussianRandomOp : public framework::OperatorWithKernel {
     for (auto dim : shape) {
       temp.push_back(static_cast<int64_t>(dim));
     }
-    PADDLE_ENFORCE_GT(shape.size(), 0UL,
+    PADDLE_ENFORCE_GT(
+        shape.size(), 0UL,
         platform::errors::InvalidArgument(
             "Attribute(shape) of GaussianRandomOp must be set "
-                          "and shape.size() > 0."));
+            "and shape.size() > 0, but reveived shape.size() is %d",
+            shape.size()));
     ctx->SetOutputDim("Out", framework::make_ddim(temp));
   }
 

paddle/fluid/operators/smooth_l1_loss_op.cc

@@ -34,15 +34,18 @@ class SmoothL1LossOp : public framework::OperatorWithKernel {
       check = false;
     }
     if (check) {
-      PADDLE_ENFORCE_EQ(x_dims, y_dims,
+      PADDLE_ENFORCE_EQ(
+          x_dims, y_dims,
           platform::errors::InvalidArgument(
               "Input(X) ans Input(Y) of SmoothL1LossOp should "
-                            "have the same size"));
+              "have the same size, but received X dim is %s, Y dim is %s",
+              x_dims.to_str(), y_dims.to_str()));
     }
     PADDLE_ENFORCE_GE(x_dims.size(), 2,
                       platform::errors::InvalidArgument(
                           "The tensor rank of Input(X) of SmoothL1LossOp "
-                          "should not be less than 2."));
+                          "should not be less than 2, but received %d.",
+                          x_dims.size()));
     if (ctx->HasInput("InsideWeight")) {
       PADDLE_ENFORCE_EQ(ctx->HasInput("OutsideWeight"), true,
                         platform::errors::InvalidArgument(
@@ -58,7 +61,9 @@ class SmoothL1LossOp : public framework::OperatorWithKernel {
         PADDLE_ENFORCE_EQ(x_dims, dims,
                           platform::errors::InvalidArgument(
                               "Input(X) ans Input(InsideWeight) of "
-                              "SmoothL1LossOp should have the same size"));
+                              "SmoothL1LossOp should have the same size, but "
+                              "received X dim is %s, InsideWeight dim is %s",
+                              x_dims.to_str(), dims.to_str()));
       }
 
       dims = ctx->GetInputDim("OutsideWeight");
@@ -71,7 +76,9 @@ class SmoothL1LossOp : public framework::OperatorWithKernel {
         PADDLE_ENFORCE_EQ(x_dims, dims,
                           platform::errors::InvalidArgument(
                               "Input(X) ans Input(OutsideWeight) of "
-                              "SmoothL1LossOp should have the same size"));
+                              "SmoothL1LossOp should have the same size, but "
+                              "received X dim is %s, OutsideWeight dim is %s",
+                              x_dims.to_str(), dims.to_str()));
       }
     }
 
@@ -145,18 +152,23 @@ class SmoothL1LossGradOp : public framework::OperatorWithKernel {
     auto in_dims = ctx->GetInputDim("Diff");
     auto out_dims = ctx->GetInputDim(framework::GradVarName("Out"));
 
-    PADDLE_ENFORCE_GE(out_dims.size(), 2,
+    PADDLE_ENFORCE_GE(
+        out_dims.size(), 2,
         platform::errors::InvalidArgument(
-                          "The tensor rank of Input(Out@Grad) should be 2."));
+            "The tensor rank of Input(Out@Grad) should be 2, but received %d.",
+            out_dims.size()));
     if (ctx->IsRuntime()) {
-      PADDLE_ENFORCE_EQ(out_dims[0], in_dims[0],
+      PADDLE_ENFORCE_EQ(
+          out_dims[0], in_dims[0],
           platform::errors::InvalidArgument(
               "The 1st dimension of Input(Out@Grad) must be "
-                            "same as input in SmoothL1LossGradOp."));
+              "same as input in SmoothL1LossGradOp, but received %d and %d.",
+              out_dims[0], in_dims[0]));
       PADDLE_ENFORCE_EQ(out_dims[1], 1,
                         platform::errors::InvalidArgument(
                             "The 2nd dimension of Input(Out@Grad) must be 1 in "
-                            "SmoothL1LossGradOp."));
+                            "SmoothL1LossGradOp, but received %d.",
+                            out_dims[1]));
     }
 
     auto x_grad_name = framework::GradVarName("X");