tensorflow/models · error · TypeError

Invalid sequence: only supports single level {!r} of {!r} or

Error message

Invalid sequence: only supports single level {!r} of {!r} or dict or ParamsDict found: {!r}

What it means

Error "Invalid sequence: only supports single level {!r} of {!r} or dict or ParamsDict found: {!r}" thrown in tensorflow/models.

Source

Thrown at official/modeling/hyperparams/base_config.py:148

    if not isinstance(v, cls.SEQUENCE_TYPES):
      return False
    return (all(isinstance(e, cls.IMMUTABLE_TYPES) for e in v) or
            all(isinstance(e, dict) for e in v) or
            all(isinstance(e, params_dict.ParamsDict) for e in v))

  @classmethod
  def _import_config(cls, v, subconfig_type):
    """Returns v with dicts converted to Configs, recursively."""
    if not issubclass(subconfig_type, params_dict.ParamsDict):
      raise TypeError(
          'Subconfig_type should be subclass of ParamsDict, found {!r}'.format(
              subconfig_type))
    if isinstance(v, cls.IMMUTABLE_TYPES):
      return v
    elif isinstance(v, cls.SEQUENCE_TYPES):
      # Only support one layer of sequence.
      if not cls._isvalidsequence(v):
        raise TypeError(
            'Invalid sequence: only supports single level {!r} of {!r} or '
            'dict or ParamsDict found: {!r}'.format(cls.SEQUENCE_TYPES,
                                                    cls.IMMUTABLE_TYPES, v))
      import_fn = functools.partial(
          cls._import_config, subconfig_type=subconfig_type)
      return type(v)(map(import_fn, v))
    elif isinstance(v, params_dict.ParamsDict):
      # Deepcopy here is a temporary solution for preserving type in nested
      # Config object.
      return copy.deepcopy(v)
    elif isinstance(v, dict):
      return subconfig_type(v)
    else:
      raise TypeError('Unknown type: {!r}'.format(type(v)))

  @classmethod
  def _export_config(cls, v):
    """Returns v with Configs converted to dicts, recursively."""

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/modeling/hyperparams/base_config.py:148 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/4eaba8784a22f93a. Report an issue: GitHub.