Iterable dataset.filter should not override features
### Describe the bug

When calling filter on an iterable dataset, the features get set to None

### Steps to reproduce the bug

import numpy as np
import time
from datasets import Dataset, Features, Array3D

```python
features=Features(**{"array0": Array3D((None, 10, 10), dtype="float32"), "array1": Array3D((None,10,10), dtype="float32")})
dataset = Dataset.from_dict({f"array{i}": [np.zeros((x,10,10), dtype=np.float32) for x in [2000,1000]*25] for i in range(2)}, features=features)
ds = dataset.to_iterable_dataset()
orig_column_names = ds.column_names
ds = ds.filter(lambda x: True)
assert ds.column_names == orig_column_names
```

### Expected behavior

Filter should preserve features information

### Environment info

3.0.2