error message of NCE API enhancement (#23544)

* error message of NCE API enhancement

python/paddle/fluid/dygraph/nn.py

@@ -26,6 +26,7 @@ from ..param_attr import ParamAttr
 from ..initializer import Normal, Constant, NumpyArrayInitializer
 from .. import unique_name
 from .layer_object_helper import LayerObjectHelper
+from ..data_feeder import check_variable_and_dtype, check_type
 import numpy as np
 import numbers
 import logging
@@ -2019,6 +2020,10 @@ class NCE(layers.Layer):
         self._inputs['Weight'] = self.weight
 
     def forward(self, input, label, sample_weight=None):
+        check_variable_and_dtype(input, "input", ['float32', 'float64'], "NCE")
+        check_variable_and_dtype(label, "label", ['int64'], "NCE")
+        check_type(sample_weight, 'sample_weight', (Variable, type(None)),
+                   'NCE')
         assert isinstance(input, Variable)
         assert isinstance(label, Variable)
 

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

@@ -252,5 +252,47 @@ class TestNCE_OpError(unittest.TestCase):
             self.assertRaises(TypeError, fluid.layers.nce, input4, label4, 5)
 
 
+class TestDygraphNCE_OpError(unittest.TestCase):
+    def test_NCE_errors(self):
+        with program_guard(Program(), Program()):
+            nce = fluid.NCE(20, 5)
+            input1 = fluid.create_lod_tensor(
+                np.array([0.0, 3.0, 2.0, 4.0]), [[1, 1, 2]], fluid.CPUPlace())
+            label1 = fluid.layers.data(
+                name='label1', shape=[-1, 4], dtype="int64")
+            # the input(input) of NCE layer must be Variable.
+            self.assertRaises(TypeError, nce, input1, label1)
+
+            input2 = fluid.layers.data(
+                name='input2', shape=[-1, 4], dtype="float32")
+            label2 = fluid.create_lod_tensor(
+                np.array([0.0, 3.0, 2.0, 4.0]), [[1, 1, 2]], fluid.CPUPlace())
+            # the input(label) of NCE layer must be Variable.
+            self.assertRaises(TypeError, nce, input2, label2)
+
+            input3 = fluid.layers.data(
+                name='input3', shape=[-1, 4], dtype="float16")
+            label3 = fluid.layers.data(
+                name='label3', shape=[-1, 1], dtype="int64")
+            # the data type of input(input) must be float32 or float64.
+            self.assertRaises(TypeError, nce, input3, label3)
+
+            input4 = fluid.layers.data(
+                name='input4', shape=[-1, 4], dtype="float32")
+            label4 = fluid.layers.data(
+                name='label4', shape=[-1, 1], dtype="int32")
+            # the data type of input(label) must be int64.
+            self.assertRaises(TypeError, nce, input4, label4)
+
+            input5 = fluid.layers.data(
+                name='input5', shape=[-1, 4], dtype="float32")
+            label5 = fluid.layers.data(
+                name='label5', shape=[-1, 1], dtype="int64")
+            sample_weight = fluid.create_lod_tensor(
+                np.array([0.0, 3.0, 2.0, 4.0]), [[1, 1, 2]], fluid.CPUPlace())
+            # the sample_weight of nce must be Variable or None.
+            self.assertRaises(TypeError, nce, input5, label5, sample_weight)
+
+
 if __name__ == '__main__':
     unittest.main()