Iterable dataset.filter should not override features

[alex-hh]

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

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

[lhoestq]

closed by https://github.com/huggingface/datasets/pull/7209, thanks @alex-hh !