Method init_spec

lit_nlp/api/model.py:105–129

Attempts to infer a Spec describing a Model's constructor parameters. The Model base class attempts to infer a Spec for the constructor using `lit_nlp.api.types.infer_spec_for_func()`. If successful, this function will return a `dict[str, LitType]`. If unsucessful (i.e., the infere

(cls)

  @classmethod
  def init_spec(cls) -> Optional[Spec]:
    """Attempts to infer a Spec describing a Model's constructor parameters.

    The Model base class attempts to infer a Spec for the constructor using
    `lit_nlp.api.types.infer_spec_for_func()`.

    If successful, this function will return a `dict[str, LitType]`. If
    unsucessful (i.e., the inferencer raises a `TypeError` because it encounters
    a parameter that it not supported by `infer_spec_for_func()`), this function
    will return None, log a warning describing where and how the inferencing
    failed, and LIT users **will not** be able to load new instances of this
    model from the UI.

    Returns:
      A Spec representation of the Model's constructor, or None if a Spec could
      not be inferred.
    """
    try:
      spec = types.infer_spec_for_func(cls.__init__)
    except TypeError as e:
      spec = None
      logging.warning(
          "Unable to infer init spec for model '%s'. %s", cls.__name__, str(e)
      )
    return spec

  def is_compatible_with_dataset(self, dataset: lit_dataset.Dataset) -> bool:
    """Return true if this model is compatible with the dataset spec."""