migrate SQUAD1 to datapipes.

torchtext/data/datasets_utils.py

@@ -10,6 +10,7 @@
     extract_archive,
     unicode_csv_reader,
 )
+from torch.utils.data import IterDataPipe, functional_datapipe
 import codecs
 try:
     import defusedxml.ElementTree as ET
@@ -318,3 +319,26 @@ def pos(self):
 
     def __str__(self):
         return self.description
+
+
+@functional_datapipe("read_squad")
+class _ParseSQuADQAData(IterDataPipe):
+    r"""Iterable DataPipe to parse the contents of a stream of JSON objects
+    as provided by SQuAD QA. Used in SQuAD1 and SQuAD2.
+    """
+    def __init__(self, source_datapipe) -> None:
+        self.source_datapipe = source_datapipe
+
+    def __iter__(self):
+        for _, stream in self.source_datapipe:
+            raw_json_data = stream["data"]
+            for layer1 in raw_json_data:
+                for layer2 in layer1["paragraphs"]:
+                    for layer3 in layer2["qas"]:
+                        _context, _question = layer2["context"], layer3["question"]
+                        _answers = [item["text"] for item in layer3["answers"]]
+                        _answer_start = [item["answer_start"] for item in layer3["answers"]]
+                        if len(_answers) == 0:
+                            _answers = [""]
+                            _answer_start = [-1]
+                        yield _context, _question, _answers, _answer_start

torchtext/datasets/squad1.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,
 )
+
+import os
+
 URL = {
     'train': "https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json",
     'dev': "https://rajpurkar.github.io/SQuAD-explorer/dataset/dev-v1.1.json",
@@ -27,8 +33,18 @@
 
 @_add_docstring_header(num_lines=NUM_LINES)
 @_create_dataset_directory(dataset_name=DATASET_NAME)
-@_wrap_split_argument(('train', 'dev'))
-def SQuAD1(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))
+@_wrap_split_argument(("train", "dev"))
+def SQuAD1(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()