tensorflow/models · error · ValueError

Unsupported checkpoint format {checkpoint_format}.

Error message

Unsupported checkpoint format {checkpoint_format}.

What it means

Error "Unsupported checkpoint format {checkpoint_format}." thrown in tensorflow/models.

Source

Thrown at official/projects/edgetpu/vision/modeling/common_modules.py:126

  """Load model weights from the given file path.

  Args:
    model: the model to load weights into
    model_weights_path: the path of the model weights
    checkpoint_format: The source of checkpoint files. By default, we assume the
      checkpoint is saved by tf.train.Checkpoint().save(). For legacy reasons,
      we can also resotre checkpoint from keras model.save_weights() method by
      setting checkpoint_format = 'keras_checkpoint'.
  """
  if checkpoint_format == 'tf_checkpoint':
    checkpoint_dict = {'model': model}
    checkpoint = tf.train.Checkpoint(**checkpoint_dict)
    checkpoint.restore(model_weights_path).assert_existing_objects_matched()
  elif checkpoint_format == 'keras_checkpoint':
    # Assert makes sure load is successeful.
    model.load_weights(model_weights_path).assert_existing_objects_matched()
  else:
    raise ValueError(f'Unsupported checkpoint format {checkpoint_format}.')


def normalize_images(
    features: tf.Tensor,
    num_channels: int = 3,
    dtype: str = 'float32',
    data_format: str = 'channels_last',
    mean_rgb: Tuple[float, ...] = MEAN_RGB,
    stddev_rgb: Tuple[float, ...] = STDDEV_RGB,
) -> tf.Tensor:
  """Normalizes the input image channels with the given mean and stddev.

  Args:
    features: `Tensor` representing decoded images in float format.
    num_channels: the number of channels in the input image tensor.
    dtype: the dtype to convert the images to. Set to `None` to skip conversion.
    data_format: the format of the input image tensor ['channels_first',
      'channels_last'].

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/edgetpu/vision/modeling/common_modules.py:126 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/24c8024bbb4f83fe. Report an issue: GitHub.