update script

README.md

@@ -28,10 +28,10 @@ dataset_info:
   config_name: plain_text
   splits:
   - name: train
-    num_bytes: 39769494896
+    num_bytes: 39769491688
     num_examples: 8013769
-  download_size: 12880027468
-  dataset_size: 39769494896
+  download_size: 12880189440
+  dataset_size: 39769491688
 ---
 
 # Dataset Card for "openwebtext"

openwebtext.py

@@ -14,10 +14,9 @@
 # limitations under the License.
 """The Open WebText Corpus"""
 
-
 import os
 import re
-from itertools import chain
+import tarfile
 
 import datasets
 
@@ -35,7 +34,25 @@ _DESCRIPTION = """\
 An open-source replication of the WebText dataset from OpenAI.
 """
 
-_URL = "https://zenodo.org/record/3834942/files/openwebtext.tar.xz"
+_N_DATA_FILES = 21
+_DATA_FILES = ["subsets/urlsf_subset{:02d}.tar".format(i) for i in range(_N_DATA_FILES)]
+
+
+def _iter_tar(f):
+    stream = tarfile.open(fileobj=f, mode="r|*")
+    for tarinfo in stream:
+        file_path = tarinfo.name
+        if not tarinfo.isreg():
+            continue
+        if file_path is None:
+            continue
+        if os.path.basename(file_path).startswith((".", "__")):
+            # skipping hidden files
+            continue
+        file_obj = stream.extractfile(tarinfo)
+        yield file_path, file_obj
+        stream.members = []
+    del stream
 
 
 class Openwebtext(datasets.GeneratorBasedBuilder):
@@ -58,29 +75,23 @@ class Openwebtext(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        dl_dir = dl_manager.download_and_extract(_URL)
-        owt_dir = os.path.join(dl_dir, "openwebtext")
-        subset_xzs = [
-            os.path.join(owt_dir, file_name)
-            for file_name in sorted(os.listdir(owt_dir))
-            if file_name.endswith("xz")  # filter out ...xz.lock
-        ]
-        ex_dirs = dl_manager.extract(subset_xzs, num_proc=round(os.cpu_count() * 0.75))
-        nested_txt_files = [
-            [
-                os.path.join(ex_dir, txt_file_name)
-                for txt_file_name in sorted(os.listdir(ex_dir))
-                if txt_file_name.endswith("txt")
-            ]
-            for ex_dir in ex_dirs
-        ]
-        txt_files = chain(*nested_txt_files)
+        archives = dl_manager.download(_DATA_FILES)
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"txt_files": txt_files}),
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={
+                "archive_iterators": [
+                    dl_manager.iter_archive(archive) for archive in archives
+                ]
+            }),
         ]
 
-    def _generate_examples(self, txt_files):
+    def _generate_examples(self, archive_iterators):
         """Yields examples."""
-        for idx, filepath in enumerate(txt_files):
-            with open(filepath, encoding="utf-8") as f:
-                yield idx, {"text": re.sub("\n\n\n+", "\n\n", f.read()).strip()}
+        for archive_iterator in archive_iterators:
+            for xz_filepath, xz_f in archive_iterator:
+                if not xz_filepath.endswith(".xz"):
+                    continue
+                for txt_filepath, txt_f in _iter_tar(xz_f):
+                    if not txt_filepath.endswith(".txt"):
+                        continue
+                    idx = f"{xz_filepath}/{txt_filepath}"
+                    yield idx, {"text": re.sub("\n\n\n+", "\n\n", txt_f.read().decode("utf-8")).strip()}