"NameError: name 'faiss' is not defined" on `.add_faiss_index` when `device` is not None
## Describe the bug

When using `datasets` to calculate the FAISS indices of a dataset, the exception `NameError: name 'faiss' is not defined` is triggered when trying to calculate those on a device (GPU), so `.add_faiss_index(..., device=0)` fails with that exception.

All that assuming that `datasets` is properly installed and `faiss-gpu` too, as well as all the CUDA drivers required.

## Steps to reproduce the bug

```python
# Sample code to reproduce the bug
from transformers import DPRContextEncoder, DPRContextEncoderTokenizer
import torch
torch.set_grad_enabled(False)
ctx_encoder = DPRContextEncoder.from_pretrained("facebook/dpr-ctx_encoder-single-nq-base")
ctx_tokenizer = DPRContextEncoderTokenizer.from_pretrained("facebook/dpr-ctx_encoder-single-nq-base")

from datasets import load_dataset
ds = load_dataset('crime_and_punish', split='train[:100]')
ds_with_embeddings = ds.map(lambda example: {'embeddings': ctx_encoder(**ctx_tokenizer(example["line"], return_tensors="pt"))[0][0].numpy()})

ds_with_embeddings.add_faiss_index(column='embeddings', device=0) # default `device=None`
```

## Expected results

A new column named `embeddings` in the dataset that we're adding the index to.

## Actual results

An exception is triggered with the following message `NameError: name 'faiss' is not defined`.

## Environment info

- `datasets` version: 2.1.0
- Platform: Linux-5.13.0-1022-azure-x86_64-with-glibc2.31
- Python version: 3.9.12
- PyArrow version: 7.0.0
- Pandas version: 1.4.2
