tensorflow/models · error · ValueError
Unexpected inputs type to %s.
Error message
Unexpected inputs type to %s.
What it means
Error "Unexpected inputs type to %s." thrown in tensorflow/models.
Source
Thrown at official/nlp/modeling/networks/bert_encoder.py:244
else:
self.inputs = dict(
input_word_ids=tf_keras.Input(shape=(None,), dtype=tf.int32),
input_mask=tf_keras.Input(shape=(None,), dtype=tf.int32),
input_type_ids=tf_keras.Input(shape=(None,), dtype=tf.int32))
def call(self, inputs):
word_embeddings = None
if isinstance(inputs, dict):
word_ids = inputs.get('input_word_ids')
mask = inputs.get('input_mask')
type_ids = inputs.get('input_type_ids')
word_embeddings = inputs.get('input_word_embeddings', None)
dense_inputs = inputs.get('dense_inputs', None)
dense_mask = inputs.get('dense_mask', None)
dense_type_ids = inputs.get('dense_type_ids', None)
else:
raise ValueError('Unexpected inputs type to %s.' % self.__class__)
if word_embeddings is None:
word_embeddings = self._embedding_layer(word_ids)
if dense_inputs is not None:
mask = tf.concat([mask, dense_mask], axis=1)
embeddings = self._get_embeddings(word_ids, type_ids, word_embeddings, # pyrefly: ignore[bad-argument-type]
dense_inputs, dense_type_ids)
embeddings = self._embedding_norm_layer(embeddings)
embeddings = self._embedding_dropout(embeddings)
if self._embedding_projection is not None:
embeddings = self._embedding_projection(embeddings)
attention_mask = self._attention_mask_layer(embeddings, mask)
encoder_outputs = []View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/nlp/modeling/networks/bert_encoder.py:244 when the library encounters an invalid state.
Common situations: See trigger scenarios.
AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24).
Data as JSON: /api/errors/57ff893ec478e01b.
Report an issue: GitHub.