imporve efficiency

python/paddle/nn/functional/loss.py

@@ -1411,11 +1411,13 @@ def cross_entropy(input,
                 out = core.ops.elementwise_mul(out, weight_gather_reshape)
 
             else:
-                for label_val in label.flatten():
-                    if label_val < 0 or label_val >= input.shape[-1]:
-                        raise ValueError(
-                            'Expected 0 <= label_value < class_dimension({}), but got label_value {}'.
-                            format(input.shape[-1], label_val.numpy()))
+                label_min = paddle.min(label)
+                label_max = paddle.max(label)
+                if label_min < 0 or label_max >= input.shape[-1]:
+                    raise ValueError(
+                        'Expected 0 <= label_value < class_dimension({}), but got {} <= label_value <= {} '.
+                        format(input.shape[-1],
+                               label_min.numpy(), label_max.numpy()))
                 weight_gather = core.ops.gather_nd(weight, label)
                 input_shape = list(label.shape)
                 weight_gather_reshape = reshape(