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Fix bert_modeling error messages #7616

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merged 1 commit into from
Oct 3, 2019
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Fix bert_modeling error messages #7616

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14 changes: 8 additions & 6 deletions official/nlp/bert_modeling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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 "
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Could you help fix just these two lint errors?
official/nlp/bert_modeling.py:651: [C0301(line-too-long), ] Line too long (90/80)

official/nlp/bert_modeling.py:655: [C0301(line-too-long), ] Line too long (81/80)

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Done. I couldn't find pylint script or config, but I hope this particular errors shoud gone now.

"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(
Expand Down Expand Up @@ -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(
Expand Down