diff --git a/paddle/fluid/operators/nll_loss_op.cc b/paddle/fluid/operators/nll_loss_op.cc
index f0b5f4a466a0049c53d51d8610cf115d8bfe0295..263a73451c909422c7c7c5b57f707374e186c31f 100644
--- a/paddle/fluid/operators/nll_loss_op.cc
+++ b/paddle/fluid/operators/nll_loss_op.cc
@@ -53,10 +53,14 @@ class NLLLossOp : public framework::OperatorWithKernel {
         PADDLE_ENFORCE_EQ(w_dims.size(), 1,
                           platform::errors::InvalidArgument(
                               "Input(Weight) should be a 1D tensor."));
-        PADDLE_ENFORCE_EQ(x_dims[1], w_dims[0],
-                          platform::errors::InvalidArgument(
-                              "Input(Weight) Tensor's size should match "
-                              "to the the total number of classes."));
+        PADDLE_ENFORCE_EQ(
+            x_dims[1], w_dims[0],
+            platform::errors::InvalidArgument(
+                "Expected input tensor Weight's size should equal "
+                "to the first dimension of the input tensor X. But received "
+                "Weight's "
+                "size is %d, the first dimension of input X is %d",
+                w_dims[0], x_dims[1]));
       }
     }
     if (x_dims.size() == 2) {
@@ -68,7 +72,8 @@ class NLLLossOp : public framework::OperatorWithKernel {
     } else if (x_dims.size() == 4) {
       PADDLE_ENFORCE_EQ(label_dims.size(), 3,
                         platform::errors::InvalidArgument(
-                            "The tensor rank of Input(Label) must be 3."));
+                            "Expected Input(Lable) dimensions=3, received %d.",
+                            label_dims.size()));
       auto input0 = x_dims[0];
       auto input2 = x_dims[2];
       auto input3 = x_dims[3];