    def used_params(self) -> List[torch.nn.Parameter]:
        """
        The parameters of the model that have non-zero gradients after a backwards pass.

        This can be used to gather the corresponding gradients with respect to a loss
        via the `torch.autograd.grad` function.

        !!! Note
            Accessing this property requires calling `self._gather_train_instances_and_compute_gradients()`
            if it hasn't been called yet, which may take several minutes.
        """
        if self._used_params is None:
            self._gather_train_instances_and_compute_gradients()
        assert self._used_params is not None
        return self._used_params
The parameters of the model that have non-zero gradients after a backwards pass.

This can be used to gather the corresponding gradients with respect to a loss
via the `torch.autograd.grad` function.

!!! Note
Accessing this property requires calling `self._gather_train_instances_and_compute_gradients()`
if it hasn't been called yet, which may take several minutes.
allennlp/interpret/influence_interpreters/influence_interpreter.py