tensorflow/models · error · ValueError

If inputs is None, `length` must be set in RelativePositionE

Error message

If inputs is None, `length` must be set in RelativePositionEmbedding().

What it means

Error "If inputs is None, `length` must be set in RelativePositionEmbedding()." thrown in tensorflow/models.

Source

Thrown at official/nlp/modeling/layers/position_embedding.py:153

    }
    base_config = super(RelativePositionEmbedding, self).get_config()
    return dict(list(base_config.items()) + list(config.items()))

  def call(self, inputs, length=None):
    """Implements call() for the layer.

    Args:
      inputs: An tensor whose second dimension will be used as `length`. If
        `None`, the other `length` argument must be specified.
      length: An optional integer specifying the number of positions. If both
        `inputs` and `length` are spcified, `length` must be equal to the second
        dimension of `inputs`.

    Returns:
      A tensor in shape of `(length, hidden_size)`.
    """
    if inputs is None and length is None:
      raise ValueError("If inputs is None, `length` must be set in "
                       "RelativePositionEmbedding().")
    if inputs is not None:
      input_shape = tf_utils.get_shape_list(inputs)
      if length is not None and length != input_shape[1]:
        raise ValueError(
            "If inputs is not None, `length` must equal to input_shape[1].")
      length = input_shape[1]
    position = tf.cast(tf.range(length), tf.float32)
    num_timescales = self._hidden_size // 2
    min_timescale, max_timescale = self._min_timescale, self._max_timescale
    log_timescale_increment = (
        math.log(float(max_timescale) / float(min_timescale)) /
        (tf.cast(num_timescales, tf.float32) - 1))
    inv_timescales = min_timescale * tf.exp(
        tf.cast(tf.range(num_timescales), tf.float32) *
        -log_timescale_increment)
    scaled_time = tf.expand_dims(position, 1) * tf.expand_dims(
        inv_timescales, 0)

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/nlp/modeling/layers/position_embedding.py:153 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/96a241eb70f5cc30. Report an issue: GitHub.