tensorflow/models · error · ValueError

`max_length` must be an Integer, not `None`.

Error message

`max_length` must be an Integer, not `None`.

What it means

Error "`max_length` must be an Integer, not `None`." thrown in tensorflow/models.

Source

Thrown at official/nlp/modeling/layers/position_embedding.py:58

    max_length: The maximum size of the dynamic sequence.
    initializer: The initializer to use for the embedding weights. Defaults to
      "glorot_uniform".
    seq_axis: The axis of the input tensor where we add the embeddings.

  Reference: This layer creates a positional embedding as described in
  [BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding](https://arxiv.org/abs/1810.04805).
  """

  def __init__(self,
               max_length,
               initializer="glorot_uniform",
               seq_axis=1,
               **kwargs):

    super().__init__(**kwargs)
    if max_length is None:
      raise ValueError(
          "`max_length` must be an Integer, not `None`."
      )
    self._max_length = max_length
    self._initializer = tf_keras.initializers.get(initializer)
    self._seq_axis = seq_axis

  def get_config(self):
    config = {
        "max_length": self._max_length,
        "initializer": tf_keras.initializers.serialize(self._initializer),
        "seq_axis": self._seq_axis,
    }
    base_config = super(PositionEmbedding, self).get_config()
    return dict(list(base_config.items()) + list(config.items()))

  def build(self, input_shape):
    dimension_list = input_shape
    width = dimension_list[-1]

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/nlp/modeling/layers/position_embedding.py:58 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/8691b32d6aac64a7. Report an issue: GitHub.