remove `clone` in `_compute_jacobian_wrt_params_with_sample_wise_trick`

[99warriors]

Summary: In https://www.internalfb.com/code/fbsource/[76c57d350097]/fbcode/pytorch/captum/captum/_utils/gradient.py?lines=840-841 we are calling clone on the elements of inputs. However, since inputs is of type Tuple[Any,...], those elements may not be Tensors, and thus may not have the clone method. My understanding is that we call clone because in apply_gradient_requirements, we change requires_grad=True for all elements of inputs. Even if those elements were Tensors, this would not be necessary, because in this function we seek gradients wrt to parameters of the model, and inputs refers to inputs to the model. Furthermore, since inputs is not a tuple of tensors, it is not actually possible to call apply_gradient_requirements on inputs.

Also see discussion at https://www.internalfb.com/diff/D41687791 (https://github.com/pytorch/captum/commit/288cd3a6754d85cbcb0ce74784aa014876284b6c)?dst_version_fbid=1539905103125262&transaction_fbid=587574556076948

In summary, because inputs is of type Tuple[Any,...] and not Tuple[Tensor,...], it does not make sense to call clone on the elements of inputs, nor call apply_gradient_requirements(inputs). And furthermore, we do not actually need to call the latter, because inputs is not parameters. Thus, this diff simply removes those 2 calls.

Differential Revision: D43135296

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This pull request was exported from Phabricator. Differential Revision: D43135296

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