remove hard labels check

python/paddle/fluid/tests/unittests/test_cross_entropy_loss.py

@@ -1466,34 +1466,6 @@ class TestCrossEntropyFAPIError(unittest.TestCase):
 
             self.assertRaises(ValueError, test_WeightLength_NotEqual)
 
-            def test_LabelValue_ExceedMax():
-                input_data = paddle.rand(shape=[20, 100])
-                label_data = paddle.randint(
-                    0, 100, shape=[20, 1], dtype="int64")  # hard label
-                label_data[0] = 100
-                weight_data = paddle.rand([100])  # provide weight
-                paddle.nn.functional.cross_entropy(
-                    input=input_data,
-                    label=label_data,
-                    weight=weight_data,
-                    ignore_index=-100)
-
-            self.assertRaises(IndexError, test_LabelValue_ExceedMax)
-
-            def test_LabelValue_ExceedMin():
-                input_data = paddle.rand(shape=[20, 100])
-                label_data = paddle.randint(
-                    0, 100, shape=[20, 1], dtype="int64")  # hard label
-                label_data[0] = -1
-                weight_data = paddle.rand([100])  # provide weight
-                paddle.nn.functional.cross_entropy(
-                    input=input_data,
-                    label=label_data,
-                    weight=weight_data,
-                    ignore_index=-100)
-
-            self.assertRaises(IndexError, test_LabelValue_ExceedMin)
-
             def static_test_WeightLength_NotEqual():
                 input_np = np.random.random([2, 4]).astype('float32')
                 label_np = np.random.randint(0, 4, size=(2)).astype(np.int64)

python/paddle/nn/functional/loss.py

@@ -1705,23 +1705,6 @@ def cross_entropy(input,
 
                 valid_label = paddle.where(label == ignore_index,
                                            paddle.zeros_like(label), label)
-                # TODO: Temporarily use paddle.nonzero instead of paddle.max 
-                # to detect and find out possible illegal label values
-                if len(paddle.nonzero(valid_label < 0)) > 0:
-                    invalid_label = paddle.gather_nd(
-                        valid_label, paddle.nonzero(valid_label < 0))
-                    raise IndexError(
-                        "Target({}) is out of class_dimension's lower bound({})".
-                        format(invalid_label[0], 0))
-                # TODO: Temporarily use paddle.nonzero instead of paddle.max 
-                # to detect and find out possible illegal label values
-                if len(paddle.nonzero(valid_label >= input.shape[axis])) > 0:
-                    invalid_label = paddle.gather_nd(
-                        valid_label,
-                        paddle.nonzero(valid_label >= input.shape[axis]))
-                    raise IndexError(
-                        "Target({}) is out of class_dimension's upper bound({})".
-                        format(invalid_label[0], input.shape[axis] - 1))
 
                 ignore_weight_mask = paddle.cast((label != ignore_index),
                                                  out.dtype)