Merge pull request #7616 from Huawei-MRC-OSI:fix-bert-messages

PiperOrigin-RevId: 272700366

Author: tensorflower-gardener

official/nlp/bert_modeling.py

@@ -563,11 +563,11 @@ def build(self, input_shape):
     """Implements build() for the layer."""
     dtype = tf.as_dtype(self.dtype or tf.keras.backend.floatx())
     if not (dtype.is_floating or dtype.is_complex):
-      raise TypeError("Unable to build `Dense` layer with non-floating point "
-                      "dtype %s" % (dtype,))
+      raise TypeError("Unable to build `Dense3D` layer with non-floating "
+                      "point (and non-complex) dtype %s" % (dtype,))
     input_shape = tf.TensorShape(input_shape)
     if tf.compat.dimension_value(input_shape[-1]) is None:
-      raise ValueError("The last dimension of the inputs to `Dense` "
+      raise ValueError("The last dimension of the inputs to `Dense3D` "
                        "should be defined. Found `None`.")
     self.last_dim = tf.compat.dimension_value(input_shape[-1])
     self.input_spec = tf.keras.layers.InputSpec(
@@ -648,12 +648,14 @@ def build(self, input_shape):
     """Implements build() for the layer."""
     dtype = tf.as_dtype(self.dtype or tf.keras.backend.floatx())
     if not (dtype.is_floating or dtype.is_complex):
-      raise TypeError("Unable to build `Dense` layer with non-floating point "
+      raise TypeError("Unable to build `Dense2DProjection` layer with "
+                      "non-floating point (and non-complex) "
                       "dtype %s" % (dtype,))
     input_shape = tf.TensorShape(input_shape)
     if tf.compat.dimension_value(input_shape[-1]) is None:
-      raise ValueError("The last dimension of the inputs to `Dense` "
-                       "should be defined. Found `None`.")
+      raise ValueError("The last dimension of the inputs to "
+                       "`Dense2DProjection` should be defined. "
+                       "Found `None`.")
     last_dim = tf.compat.dimension_value(input_shape[-1])
     self.input_spec = tf.keras.layers.InputSpec(min_ndim=3, axes={-1: last_dim})
     self.kernel = self.add_weight(