use functional datapipe as introduced in SQuAD1 refactor.

Author: erip

torchtext/datasets/squad2.py

@@ -1,11 +1,17 @@
-from torchtext.utils import download_from_url
+from torchtext._internal.module_utils import is_module_available
+from typing import Union, Tuple
+
+if is_module_available("torchdata"):
+    from torchdata.datapipes.iter import FileOpener, HttpReader, IterableWrapper
+
 from torchtext.data.datasets_utils import (
-    _RawTextIterableDataset,
     _wrap_split_argument,
     _add_docstring_header,
     _create_dataset_directory,
-    _create_data_from_json,
-)
+g)
+
+import os
+
 URL = {
     'train': "https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v2.0.json",
     'dev': "https://rajpurkar.github.io/SQuAD-explorer/dataset/dev-v2.0.json",
@@ -28,7 +34,17 @@
 @_add_docstring_header(num_lines=NUM_LINES)
 @_create_dataset_directory(dataset_name=DATASET_NAME)
 @_wrap_split_argument(('train', 'dev'))
-def SQuAD2(root, split):
-    extracted_files = download_from_url(URL[split], root=root, hash_value=MD5[split], hash_type='md5')
-    return _RawTextIterableDataset(DATASET_NAME, NUM_LINES[split],
-                                   _create_data_from_json(extracted_files))
+def SQuAD2(root: str, split: Union[Tuple[str], str]):
+    if not is_module_available("torchdata"):
+        raise ModuleNotFoundError("Package `torchdata` not found. Please install following instructions at `https://github.com/pytorch/data`")
+
+    url_dp = IterableWrapper([URL[split]])
+    # cache data on-disk with sanity check
+    cache_dp = url_dp.on_disk_cache(
+        filepath_fn=lambda x: os.path.join(root, os.path.basename(x)),
+        hash_dict={os.path.join(root, os.path.basename(URL[split])): MD5[split]},
+        hash_type="md5",
+    )
+    cache_dp = HttpReader(cache_dp).end_caching(mode="wb", same_filepath_fn=True)
+    cache_dp = FileOpener(cache_dp, mode="b")
+    return cache_dp.parse_json_files().read_squad()