diff --git a/python/paddle/nn/functional/loss.py b/python/paddle/nn/functional/loss.py
index 8eb6e05fc04e6bded9c335a87cdc4b541005347d..f13f14cdde118ec24161f5a722edca384b4f684a 100755
--- a/python/paddle/nn/functional/loss.py
+++ b/python/paddle/nn/functional/loss.py
@@ -1696,6 +1696,13 @@ def cross_entropy(input,
                 out = _C_ops.elementwise_mul(out, weight_gather_reshape)
 
             else:
+                if input.shape[axis] != weight.shape[-1]:
+                    raise ValueError(
+                        "input's class_dimension({}) must equal to "
+                        "weight's class_dimension({}) "
+                        "when weight is provided" \
+                            .format(input.shape[axis], weight.shape[-1]))
+
                 valid_label = paddle.where(label == ignore_index,
                                            paddle.zeros_like(label), label)
                 # TODO: Temporarily use paddle.nonzero instead of paddle.max 
@@ -1715,12 +1722,6 @@ def cross_entropy(input,
                     raise ValueError(
                         "Target({}) is out of class_dimension's upper bound({})".
                         format(invalid_label[0], input.shape[axis] - 1))
-                if input.shape[axis] != weight.shape[-1]:
-                    raise ValueError(
-                        "input's class_dimension({}) must equal to "
-                        "weight's class_dimension({}) "
-                        "when weight is provided" \
-                            .format(input.shape[axis], weight.shape[-1]))
 
                 ignore_weight_mask = paddle.cast((label != ignore_index),
                                                  out.dtype)