Fix PandasArrayExtensionArray.take coercing fill_value when not filling

[aryansk]

Fixes #8465

Problem

PandasArrayExtensionArray.take coerces fill_value to the pandas dtype before checking whether any row is actually missing. When allow_fill=True with a mask that contains no missing indices, take still needs to return a proper pandas Series — but the coercion can blow up for values that don't fit the column dtype, e.g.:

import pandas as pd
from datasets.features.features import PandasArrayExtensionArray

arr = PandasArrayExtensionArray(pd.array(["a", "b", "c"], dtype=pd.StringDtype()))
arr.take([0, 1, 2], allow_fill=True, fill_value=False)  # conversion error even though nothing is missing

Change

Coerce fill_value to the pandas dtype only when filling is actually needed (a missing index was requested), and always return a proper pandas.Series from take — previously the no-fill path could return a bare np.ndarray, breaking downstream code that expects Series semantics (indexing by boolean mask etc.).

Testing

• Regression test: take with allow_fill=True and a complete mask no longer errors on a non-matching fill_value, and the result matches a plain take.
• Existing suite green.