API(BilinearTensorProduct) error message enhancement (#23528)

* err msg enhance for BilinearTensorProduct
test=develop

* rebase dev
test=develop

* add ut
test=develop

python/paddle/fluid/dygraph/nn.py

@@ -2371,6 +2371,10 @@ class BilinearTensorProduct(layers.Layer):
             is_bias=True)
 
     def forward(self, x, y):
+        check_variable_and_dtype(x, 'x', ['float32', 'float64'],
+                                 'BilinearTensorProduct')
+        check_variable_and_dtype(y, 'y', ['float32', 'float64'],
+                                 'BilinearTensorProduct')
         self._inputs = {"X": x, "Y": y, "Weight": self.weight}
         if self.bias is not None:
             self._inputs["Bias"] = self.bias

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

@@ -16,9 +16,25 @@ from __future__ import print_function
 
 import unittest
 import numpy as np
+import paddle.fluid as fluid
 from op_test import OpTest
 
 
+class TestDygraphBilinearTensorProductAPIError(unittest.TestCase):
+    def test_errors(self):
+        with fluid.program_guard(fluid.Program(), fluid.Program()):
+            layer = fluid.dygraph.nn.BilinearTensorProduct(
+                input1_dim=5, input2_dim=4, output_dim=1000)
+            # the input must be Variable.
+            x0 = fluid.create_lod_tensor(
+                np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace())
+            self.assertRaises(TypeError, layer, x0)
+            # the input dtype must be float32 or float64
+            x1 = fluid.data(name='x1', shape=[-1, 5], dtype="float16")
+            x2 = fluid.data(name='x2', shape=[-1, 4], dtype="float32")
+            self.assertRaises(TypeError, layer, x1, x2)
+
+
 class TestBilinearTensorProductOp(OpTest):
     def setUp(self):
         self.op_type = "bilinear_tensor_product"