Minor docstring fixes

curvlinops/kfac.py

@@ -117,13 +117,14 @@ def __init__(
  from the model's predictive distribution. Defaults to ``2147483647``.
  fisher_type: The type of Fisher/GGN to approximate. If ``'type-2'``, the
  expectation over the model outputs is computed exactly by
- computing the backwward pass for each output dimension. This is
+ computing the backward pass for each output dimension. This is
  sometimes also called type-2 Fisher. If ``'mc'``, the expectation
  is approximated by sampling ``mc_samples`` labels from the model's
  predictive distribution. If ``'empirical'``, the empirical gradients
  are used which corresponds to the uncentered gradient covariance, or
  the empirical Fisher. Defaults to ``'mc'``.
  mc_samples: The number of Monte-Carlo samples to use per data point.
+ Will be ignored when ``fisher_type`` is not ``'mc'``.
  Defaults to ``1``.
 
  Raises:
@@ -226,7 +227,6 @@ def _compute_kfac(self):
  NotImplementedError: If ``fisher_type == 'type-2'``.
  ValueError: If ``fisher_type`` is not ``'type-2'``, ``'mc'``, or
  ``'empirical'``.
-
  """
  # install forward and backward hooks
  hook_handles: List[RemovableHandle] = []