[DataPipe] Adding a 's' to the functional names of open/list DataPipes

test/test_fsspec.py

@@ -94,10 +94,10 @@ def test_fsspec_file_loader_iterdatapipe(self):
         # Reset Test: Ensure the resulting streams are still readable after the DataPipe is reset/exhausted
         self._write_text_files()
         lister_dp = FileLister(self.temp_dir.name, "*.text")
-        fsspec_file_loader_dp = FSSpecFileOpener(lister_dp, mode="rb")
+        fsspec_file_opener_dp = lister_dp.open_files_by_fsspec(mode="rb")
 
         n_elements_before_reset = 2
-        res_before_reset, res_after_reset = reset_after_n_next_calls(fsspec_file_loader_dp, n_elements_before_reset)
+        res_before_reset, res_after_reset = reset_after_n_next_calls(fsspec_file_opener_dp, n_elements_before_reset)
         self.assertEqual(2, len(res_before_reset))
         self.assertEqual(3, len(res_after_reset))
         for _name, stream in res_before_reset:

test/test_local_io.py

@@ -684,10 +684,10 @@ def test_io_path_file_loader_iterdatapipe(self):
         # Reset Test: Ensure the resulting streams are still readable after the DataPipe is reset/exhausted
         self._write_text_files()
         lister_dp = FileLister(self.temp_dir.name, "*.text")
-        iopath_file_loader_dp = IoPathFileOpener(lister_dp, mode="rb")
+        iopath_file_opener_dp = lister_dp.open_files_by_iopath(mode="rb")
 
         n_elements_before_reset = 2
-        res_before_reset, res_after_reset = reset_after_n_next_calls(iopath_file_loader_dp, n_elements_before_reset)
+        res_before_reset, res_after_reset = reset_after_n_next_calls(iopath_file_opener_dp, n_elements_before_reset)
         self.assertEqual(2, len(res_before_reset))
         self.assertEqual(3, len(res_after_reset))
         for _name, stream in res_before_reset:

torchdata/datapipes/iter/load/README.md

@@ -35,8 +35,8 @@ Note: refer to the official documentation for detailed installtion instructions
 
 ### S3FileLister
 
-`S3FileLister` accepts a list of S3 prefixes and iterates all matching s3 urls. The functional API is `list_file_by_s3`.
-Acceptable prefixes include `s3://bucket-name`, `s3://bucket-name/`, `s3://bucket-name/folder`,
+`S3FileLister` accepts a list of S3 prefixes and iterates all matching s3 urls. The functional API is
+`list_files_by_s3`. Acceptable prefixes include `s3://bucket-name`, `s3://bucket-name/`, `s3://bucket-name/folder`,
 `s3://bucket-name/folder/`, and `s3://bucket-name/prefix`. You may also set `length`, `request_timeout_ms` (default 3000
 ms in aws-sdk-cpp), and `region`. Note that:
 
@@ -48,7 +48,7 @@ ms in aws-sdk-cpp), and `region`. Note that:
 ### S3FileLoader
 
 `S3FileLoader` accepts a list of S3 URLs and iterates all files in `BytesIO` format with `(url, BytesIO)` tuples. The
-functional API is `load_file_by_s3`. You may also set `request_timeout_ms` (default 3000 ms in aws-sdk-cpp), `region`,
+functional API is `load_files_by_s3`. You may also set `request_timeout_ms` (default 3000 ms in aws-sdk-cpp), `region`,
 `buffer_size` (default 120Mb), and `multi_part_download` (default to use multi-part downloading). Note that:
 
 1. Input **must** be a list and S3 URLs must be valid.

torchdata/datapipes/iter/load/fsspec.py

@@ -101,11 +101,11 @@ def __iter__(self) -> Iterator[str]:
                             yield abs_path
 
 
-@functional_datapipe("open_file_by_fsspec")
+@functional_datapipe("open_files_by_fsspec")
 class FSSpecFileOpenerIterDataPipe(IterDataPipe[Tuple[str, StreamWrapper]]):
     r"""
     Opens files from input datapipe which contains `fsspec` paths and yields a tuple of
-    pathname and opened file stream (functional name: ``open_file_by_fsspec``).
+    pathname and opened file stream (functional name: ``open_files_by_fsspec``).
 
     Args:
         source_datapipe: Iterable DataPipe that provides the pathnames or URLs
@@ -114,7 +114,7 @@ class FSSpecFileOpenerIterDataPipe(IterDataPipe[Tuple[str, StreamWrapper]]):
     Example:
         >>> from torchdata.datapipes.iter import FSSpecFileLister
         >>> datapipe = FSSpecFileLister(root=dir_path)
-        >>> file_dp = datapipe.open_file_by_fsspec()
+        >>> file_dp = datapipe.open_files_by_fsspec()
     """
 
     def __init__(self, source_datapipe: IterDataPipe[str], mode: str = "r") -> None:
@@ -133,6 +133,10 @@ def __len__(self) -> int:
         return len(self.source_datapipe)
 
 
+# Register for functional API for backward compatibility
+IterDataPipe.register_datapipe_as_function("open_file_by_fsspec", FSSpecFileOpenerIterDataPipe)
+
+
 @functional_datapipe("save_by_fsspec")
 class FSSpecSaverIterDataPipe(IterDataPipe[str]):
     r"""

torchdata/datapipes/iter/load/iopath.py

@@ -96,11 +96,11 @@ def __iter__(self) -> Iterator[str]:
                         yield os.path.join(path, file_name)
 
 
-@functional_datapipe("open_file_by_iopath")
+@functional_datapipe("open_files_by_iopath")
 class IoPathFileOpenerIterDataPipe(IterDataPipe[Tuple[str, StreamWrapper]]):
     r"""
     Opens files from input datapipe which contains pathnames or URLs,
-    and yields a tuple of pathname and opened file stream (functional name: ``open_file_by_iopath``).
+    and yields a tuple of pathname and opened file stream (functional name: ``open_files_by_iopath``).
 
     Args:
         source_datapipe: Iterable DataPipe that provides the pathnames or URLs
@@ -114,7 +114,7 @@ class IoPathFileOpenerIterDataPipe(IterDataPipe[Tuple[str, StreamWrapper]]):
     Example:
         >>> from torchdata.datapipes.iter import IoPathFileLister
         >>> datapipe = IoPathFileLister(root=S3URL)
-        >>> file_dp = datapipe.open_file_by_iopath()
+        >>> file_dp = datapipe.open_files_by_iopath()
     """
 
     def __init__(self, source_datapipe: IterDataPipe[str], mode: str = "r", pathmgr=None) -> None:
@@ -141,6 +141,10 @@ def __len__(self) -> int:
         return len(self.source_datapipe)
 
 
+# Register for functional API for backward compatibility
+IterDataPipe.register_datapipe_as_function("open_file_by_iopath", IoPathFileOpenerIterDataPipe)
+
+
 @functional_datapipe("save_by_iopath")
 class IoPathSaverIterDataPipe(IterDataPipe[str]):
 

torchdata/datapipes/iter/load/s3io.py

@@ -13,10 +13,10 @@
 from torchdata.datapipes.utils import StreamWrapper
 
 
-@functional_datapipe("list_file_by_s3")
+@functional_datapipe("list_files_by_s3")
 class S3FileListerIterDataPipe(IterDataPipe[str]):
     r"""
-    Iterable DataPipe that lists Amazon S3 file URLs with the given prefixes (functional name: ``list_file_by_s3``).
+    Iterable DataPipe that lists Amazon S3 file URLs with the given prefixes (functional name: ``list_files_by_s3``).
     Acceptable prefixes include ``s3://bucket-name``, ``s3://bucket-name/``, ``s3://bucket-name/folder``,
     ``s3://bucket-name/folder/``, and ``s3://bucket-name/prefix``. You may also set ``length``, ``request_timeout_ms``
     (default 3000 ms in aws-sdk-cpp), and ``region``.
@@ -72,10 +72,10 @@ def __len__(self) -> int:
         return self.length
 
 
-@functional_datapipe("load_file_by_s3")
+@functional_datapipe("load_files_by_s3")
 class S3FileLoaderIterDataPipe(IterDataPipe[Tuple[str, StreamWrapper]]):
     r"""
-    Iterable DataPipe that loads Amazon S3 files from the given S3 URLs (functional name: ``load_file_by_s3``).
+    Iterable DataPipe that loads Amazon S3 files from the given S3 URLs (functional name: ``load_files_by_s3``).
     ``S3FileLoader`` iterates all given S3 URLs in ``BytesIO`` format with ``(url, BytesIO)`` tuples.
     You may also set ``request_timeout_ms`` (default 3000 ms in aws-sdk-cpp), ``region``,
     ``buffer_size`` (default 120Mb), and ``multi_part_download`` (default to use multi-part downloading).