[Wav2Vec2FeatureExtractor] Fix `extractor.pad()` dtype backwards compatibility
Resolves #13689

This fixes an issue introduced by #13650 with speech feature extractors' tensors being returned as torch.float64 when `.pad()` is called directly:

```python
from transformers import Wav2Vec2FeatureExtractor
import numpy as np

extractor = Wav2Vec2FeatureExtractor.from_pretrained("facebook/wav2vec2-base-960h")

rand_input = np.ones((100,), dtype=np.float64)
out = extractor.pad([{"input_values": rand_input}], return_tensors="pt")

print(out.dtype) # <- this should be `torch.float32`
```

This is due to how pytorch converts float numpy arrays (new padding logic) vs python lists (old padding logic):

* uses torch.float32 for python lists by default: `torch.tensor([1.2, 2.3]).dtype  #  torch.float32`
* `np.array([1.2, 2.3]).dtype  # np.float64` 
* uses source dtype for numpy arrays: `torch.tensor(np.array([1.2, 2.3])).dtype  #  torch.float64`