Persist IF tensors to storage for large models

[Xuzzo]

Problem: As highlighted in a discussion in MR #375, a lot of the tensors we create for influence calculation end up being very large. For example, the influence factors are stored in a matrix of size (N_test_points, N_model_parameters). Often, these cannot fit into RAM (be it ordinary or on GPU).

A simple fix would use generators. Instead of creating all the influence factors, we could calculate batch-by-batch within the compute_influences_up and compute_influences_pert methods. Same can be said of grads within these methods. However, this would imply re-calculating influence factors or grads several times, with massive computational overhead.

A better fix would cache the tensors to disk. We could create a CachedTensor class that saves the tensors into files and loads them whenever needed, thus freeing the VRAM. Even the output of the compute_influences method could be a CachedTensor: one would only need to remember to flush it when it is no longer needed.