restore arrow array to numpy to numpy extractor

src/datasets/formatting/formatting.py

@@ -107,41 +107,6 @@ def _is_array_with_nulls(pa_array: pa.Array) -> bool:
     return pa_array.null_count > 0
 
 
-def _arrow_array_to_numpy(pa_array: pa.Array) -> np.ndarray:
-    if isinstance(pa_array, pa.ChunkedArray):
-        if isinstance(pa_array.type, _ArrayXDExtensionType):
-            # don't call to_pylist() to preserve dtype of the fixed-size array
-            zero_copy_only = _is_zero_copy_only(pa_array.type.storage_dtype, unnest=True)
-            array: List = [row for chunk in pa_array.chunks for row in chunk.to_numpy(zero_copy_only=zero_copy_only)]
-        else:
-            zero_copy_only = _is_zero_copy_only(pa_array.type) and all(
-                not _is_array_with_nulls(chunk) for chunk in pa_array.chunks
-            )
-            array: List = [row for chunk in pa_array.chunks for row in chunk.to_numpy(zero_copy_only=zero_copy_only)]
-    else:
-        if isinstance(pa_array.type, _ArrayXDExtensionType):
-            # don't call to_pylist() to preserve dtype of the fixed-size array
-            zero_copy_only = _is_zero_copy_only(pa_array.type.storage_dtype, unnest=True)
-            array: List = pa_array.to_numpy(zero_copy_only=zero_copy_only)
-        else:
-            zero_copy_only = _is_zero_copy_only(pa_array.type) and not _is_array_with_nulls(pa_array)
-            array: List = pa_array.to_numpy(zero_copy_only=zero_copy_only).tolist()
-
-    if len(array) > 0:
-        if any(
-            (isinstance(x, np.ndarray) and (x.dtype == object or x.shape != array[0].shape))
-            or (isinstance(x, float) and np.isnan(x))
-            for x in array
-        ):
-            if np.lib.NumpyVersion(np.__version__) >= "2.0.0b1":
-                return np.asarray(array, dtype=object)
-            return np.array(array, copy=False, dtype=object)
-    if np.lib.NumpyVersion(np.__version__) >= "2.0.0b1":
-        return np.asarray(array)
-    else:
-        return np.array(array, copy=False)
-
-
 def dict_of_lists_to_list_of_dicts(dict_of_lists: Dict[str, List[T]]) -> List[Dict[str, T]]:
     # convert to list of dicts
     list_of_dicts = []
@@ -231,7 +196,41 @@ def extract_column(self, pa_table: pa.Table) -> np.ndarray:
         return self._arrow_array_to_numpy(pa_table[pa_table.column_names[0]])
 
     def extract_batch(self, pa_table: pa.Table) -> dict:
-        return {col: _arrow_array_to_numpy(pa_table[col]) for col in pa_table.column_names}
+        return {col: self._arrow_array_to_numpy(pa_table[col]) for col in pa_table.column_names}
+
+    def _arrow_array_to_numpy(self, pa_array: pa.Array) -> np.ndarray:
+        if isinstance(pa_array, pa.ChunkedArray):
+            if isinstance(pa_array.type, _ArrayXDExtensionType):
+                # don't call to_pylist() to preserve dtype of the fixed-size array
+                zero_copy_only = _is_zero_copy_only(pa_array.type.storage_dtype, unnest=True)
+                array: List = [row for chunk in pa_array.chunks for row in chunk.to_numpy(zero_copy_only=zero_copy_only)]
+            else:
+                zero_copy_only = _is_zero_copy_only(pa_array.type) and all(
+                    not _is_array_with_nulls(chunk) for chunk in pa_array.chunks
+                )
+                array: List = [row for chunk in pa_array.chunks for row in chunk.to_numpy(zero_copy_only=zero_copy_only)]
+        else:
+            if isinstance(pa_array.type, _ArrayXDExtensionType):
+                # don't call to_pylist() to preserve dtype of the fixed-size array
+                zero_copy_only = _is_zero_copy_only(pa_array.type.storage_dtype, unnest=True)
+                array: List = pa_array.to_numpy(zero_copy_only=zero_copy_only)
+            else:
+                zero_copy_only = _is_zero_copy_only(pa_array.type) and not _is_array_with_nulls(pa_array)
+                array: List = pa_array.to_numpy(zero_copy_only=zero_copy_only).tolist()
+
+        if len(array) > 0:
+            if any(
+                (isinstance(x, np.ndarray) and (x.dtype == object or x.shape != array[0].shape))
+                or (isinstance(x, float) and np.isnan(x))
+                for x in array
+            ):
+                if np.lib.NumpyVersion(np.__version__) >= "2.0.0b1":
+                    return np.asarray(array, dtype=object)
+                return np.array(array, copy=False, dtype=object)
+        if np.lib.NumpyVersion(np.__version__) >= "2.0.0b1":
+            return np.asarray(array)
+        else:
+            return np.array(array, copy=False)
 
 
 class PandasArrowExtractor(BaseArrowExtractor[pd.DataFrame, pd.Series, pd.DataFrame]):