API (layers.data/fluid.data) error message enhancement (#23427)

* Api (fluid.data/layers.data) error message enhancement. test=develop

python/paddle/fluid/data.py

@@ -15,8 +15,9 @@
 import numpy as np
 import six
 
-from . import core
-from .layer_helper import LayerHelper
+from paddle.fluid import core
+from paddle.fluid.layer_helper import LayerHelper
+from paddle.fluid.data_feeder import check_dtype, check_type
 
 __all__ = ['data']
 
@@ -99,6 +100,10 @@ def data(name, shape, dtype='float32', lod_level=0):
 
     """
     helper = LayerHelper('data', **locals())
+
+    check_type(name, 'name', (six.binary_type, six.text_type), 'data')
+    check_type(shape, 'shape', (list, tuple), 'data')
+
     shape = list(shape)
     for i in six.moves.range(len(shape)):
         if shape[i] is None:

python/paddle/fluid/layers/io.py

@@ -31,6 +31,7 @@ from ..layer_helper import LayerHelper
 from ..unique_name import generate as unique_name
 from ..transpiler.distribute_transpiler import DistributedMode
 import logging
+from ..data_feeder import check_dtype, check_type
 
 __all__ = [
     'data', 'read_file', 'double_buffer', 'py_reader',
@@ -73,7 +74,7 @@ def data(name,
     Args:
        name(str): The name/alias of the variable, see :ref:`api_guide_Name`
             for more details.
-       shape(list): Tuple declaring the shape. If :code:`append_batch_size` is 
+       shape(list|tuple): Tuple declaring the shape. If :code:`append_batch_size` is
             True and there is no -1 inside :code:`shape`, it should be 
             considered as the shape of the each sample. Otherwise, it should
             be considered as the shape of the batched data.  
@@ -107,6 +108,10 @@ def data(name,
           data = fluid.layers.data(name='x', shape=[784], dtype='float32')
     """
     helper = LayerHelper('data', **locals())
+
+    check_type(name, 'name', (six.binary_type, six.text_type), 'data')
+    check_type(shape, 'shape', (list, tuple), 'data')
+
     shape = list(shape)
     for i in six.moves.range(len(shape)):
         if shape[i] is None:

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

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import unittest
+
+import paddle.fluid as fluid
+import paddle.fluid.layers as layers
+from paddle.fluid import Program, program_guard
+
+
+class TestApiDataError(unittest.TestCase):
+    def test_fluid_data(self):
+        with program_guard(Program(), Program()):
+
+            # 1. The type of 'name' in fluid.data must be str.
+            def test_name_type():
+                fluid.data(name=1, shape=[2, 25], dtype="bool")
+
+            self.assertRaises(TypeError, test_name_type)
+
+            # 2. The type of 'shape' in fluid.data must be list or tuple.
+            def test_shape_type():
+                fluid.data(name='data1', shape=2, dtype="bool")
+
+            self.assertRaises(TypeError, test_shape_type)
+
+    def test_layers_data(self):
+        with program_guard(Program(), Program()):
+
+            # 1. The type of 'name' in layers.data must be str.
+            def test_name_type():
+                layers.data(name=1, shape=[2, 25], dtype="bool")
+
+            self.assertRaises(TypeError, test_name_type)
+
+            # 2. The type of 'shape' in layers.data must be list or tuple.
+            def test_shape_type():
+                layers.data(name='data1', shape=2, dtype="bool")
+
+            self.assertRaises(TypeError, test_shape_type)
+
+
+if __name__ == "__main__":
+    unittest.main()