tensorflow/models · error · ValueError

"channels_first" mode is unsupported.

Error message

"channels_first" mode is unsupported.

What it means

Error ""channels_first" mode is unsupported." thrown in tensorflow/models.

Source

Thrown at official/vision/modeling/layers/nn_layers.py:601

    """
    frames = input_shape[1]
    channels = input_shape[-1]
    pos_encoding = self._positional_encoding(
        frames, channels, start_position=frame_count, dtype=self.dtype)
    pos_encoding = tf.reshape(pos_encoding, [1, frames, 1, 1, channels])
    return pos_encoding

  def build(self, input_shape):
    """Builds the layer with the given input shape.

    Args:
      input_shape: The input shape.

    Raises:
      ValueError: If using 'channels_first' data format.
    """
    if tf_keras.backend.image_data_format() == 'channels_first':
      raise ValueError('"channels_first" mode is unsupported.')

    if self._cache_encoding:
      self._pos_encoding = self._get_pos_encoding(input_shape)

    super(PositionalEncoding, self).build(input_shape)

  def call(
      self,
      inputs: tf.Tensor,
      states: Optional[States] = None,
      output_states: bool = True,
  ) -> Union[tf.Tensor, Tuple[tf.Tensor, States]]:
    """Calls the layer with the given inputs.

    Args:
      inputs: An input `tf.Tensor`.
      states: A `dict` of states such that, if any of the keys match for this
        layer, will overwrite the contents of the buffer(s). Expected keys

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Use 'channels_last' data format.
2. Transpose inputs to NHWC instead of using channels_first.

When it happens

Trigger: Thrown at official/vision/modeling/layers/nn_layers.py:601 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/acc03b1a42af6f93. Report an issue: GitHub.