Update dataset script (#3)

- Update dataset script (38fe0f1ec51a4f0f978c28cece0cc559238d8cd6)

multilingual_librispeech.py

@@ -16,12 +16,9 @@
 # Lint as: python3
 """Multilingual Librispeech automatic speech recognition dataset."""
 
-
-from functools import partial
 import os
 
 import datasets
-from datasets.utils.streaming_download_manager import xopen
 
 
 _CITATION = """\
@@ -62,7 +59,7 @@ class MultilingualLibrispeechConfig(datasets.BuilderConfig):
             version=datasets.Version("2.1.0", ""), name=name, **kwargs
         )
         # relative path to full data inside a repo (for example `data/mls_german`)
-        self.data_root_dir = _DL_URL_FORMAT.format(name=name)
+        self.data_root_url = _DL_URL_FORMAT.format(name=name)
 
 
 class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
@@ -98,46 +95,68 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        download_kwargs = {
-            "dl_manager": dl_manager,
-            "root_dir": self.config.data_root_dir
-        }
-        download_transcript = partial(
-            download_extract_transcript, **download_kwargs
-        )
-        download_audio_non_streaming = partial(
-            download_extract_audio_archives, **download_kwargs
-        )
-        download_audio_streaming = partial(
-            download_audio_archives, **download_kwargs
-        )
-        download_limited_ids = partial(
-            download_extract_limited_ids, **download_kwargs
+        
+        transcripts = dl_manager.download({
+            "train": self.config.data_root_url + "/train/transcripts.txt",
+            "dev": self.config.data_root_url + "/dev/transcripts.txt",
+            "test": self.config.data_root_url + "/test/transcripts.txt",
+        })
+
+        # Download handles.txt files containing ids for limited supervision train sets
+        limited_supervision_9h = dl_manager.download(
+            [self.config.data_root_url + "/train/limited_supervision/9hr/handles.txt"],
         )
-
-        train_kwargs = {
-            "transcript_path": download_transcript(split="train"),
-            "audio_archives": download_audio_streaming(split="train"),
-            "local_audio_archives_paths": download_audio_non_streaming(split="train")
-                if not dl_manager.is_streaming else None
-        }
+        # in our case of 1 hour limited supervision ("train.1h") there are always 6 subfolders like:
+        # "limited_supervision/1h/0/handles.txt", "limited_supervision/1h/1/handles.txt", ...
+        limited_supervision_1h = dl_manager.download([
+            self.config.data_root_url + f"/train/limited_supervision/1hr/{i}/handles.txt" for i in range(6)
+        ])
+        
+        # each split contains many .tar.gz archives with its audio files
+        # audio_filenames.txt contains the names of these archives
+        audio_filenames_paths = dl_manager.download({
+            "train": self.config.data_root_url + "/train/audio_filenames.txt",
+            "dev": self.config.data_root_url + "/dev/audio_filenames.txt",
+            "test": self.config.data_root_url + "/test/audio_filenames.txt",
+        })
+
+        audio_archives = {}
+        for split in audio_filenames_paths:
+            with open(audio_filenames_paths[split], encoding="utf-8") as f:
+                audio_filenames = [line.strip() for line in f.readlines()]
+                audio_archives[split] = dl_manager.download([
+                    self.config.data_root_url + "/" + split + "/audio/" + filename
+                    for filename in audio_filenames
+                ])
+
+        # (Optional) In non-streaming mode, we can extract the archive locally to have actual local audio files:
+        local_extracted_archives = dl_manager.extract(audio_archives) if not dl_manager.is_streaming else {}
 
         train_splits = [
             datasets.SplitGenerator(
-                name=datasets.Split.TRAIN, gen_kwargs=train_kwargs
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "transcript_path": transcripts["train"],
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["train"]],
+                    "local_extracted_archive": local_extracted_archives.get("train"),
+                }
             ),
             datasets.SplitGenerator(
                 name="train.9h",
                 gen_kwargs={
-                    **train_kwargs,
-                    "limited_ids_paths": download_limited_ids(sub_folder="limited_supervision/9hr"),
+                    "transcript_path": transcripts["train"],
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["train"]],
+                    "local_extracted_archive": local_extracted_archives.get("train"),
+                    "limited_ids_paths": limited_supervision_9h,
                 },
             ),
             datasets.SplitGenerator(
                 name="train.1h",
                 gen_kwargs={
-                    **train_kwargs,
-                    "limited_ids_paths": download_limited_ids(sub_folder="limited_supervision/1hr"),
+                    "transcript_path": transcripts["train"],
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["train"]],
+                    "local_extracted_archive": local_extracted_archives.get("train"),
+                    "limited_ids_paths": limited_supervision_1h,
                 },
             ),
         ]
@@ -145,23 +164,21 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
         return train_splits + [
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION, gen_kwargs={
-                    "transcript_path": download_transcript(split="dev"),
-                    "audio_archives": download_audio_streaming(split="dev"),
-                    "local_audio_archives_paths": download_audio_non_streaming(split="dev")
-                        if not dl_manager.is_streaming else None
+                    "transcript_path": transcripts["dev"],
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["dev"]],
+                    "local_extracted_archive": local_extracted_archives.get("dev"),
                 }
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST, gen_kwargs={
-                    "transcript_path": download_transcript(split="test"),
-                    "audio_archives": download_audio_streaming(split="test"),
-                    "local_audio_archives_paths": download_audio_non_streaming(split="test")
-                        if not dl_manager.is_streaming else None
+                    "transcript_path": transcripts["test"],
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_archives["test"]],
+                    "local_extracted_archive": local_extracted_archives.get("test"),
                 }
             ),
         ]
 
-    def _generate_examples(self, transcript_path, audio_archives, local_audio_archives_paths, limited_ids_paths=None):
+    def _generate_examples(self, transcript_path, audio_archives, local_extracted_archive, limited_ids_paths=None):
         """Generate examples from a Multilingual LibriSpeech data dir."""
         transcripts = dict()
         with open(transcript_path, "r", encoding="utf-8") as file:
@@ -192,76 +209,18 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
                     # this only can be true in limited supervision sets ("train.9h" and "train.1h")
                     continue
 
-                path = os.path.join(local_audio_archives_paths[archive_idx], audio_filename)\
-                    if local_audio_archives_paths else audio_filename
+                local_audio_file_path = os.path.join(
+                    local_extracted_archive[archive_idx], audio_filename
+                ) if local_extracted_archive else None
+
                 yield audio_filename, {
-                    "file": path if local_audio_archives_paths else None,
-                    "audio": {"path": path, "bytes": file.read()},
+                    "file": local_audio_file_path,
+                    "audio": {
+                        "path": local_audio_file_path if local_audio_file_path else audio_filename,
+                        "bytes": file.read()
+                    },
                     "text": audio_transcript,
                     "speaker_id": speaker_id,
                     "chapter_id": chapter_id,
                     "id": audio_id
                 }
-
-
-def download_extract_limited_ids(dl_manager, root_dir, sub_folder):
-    """Download handles.txt files containing ids for limited supervision train sets. """
-
-    sub_path = os.path.join(root_dir, "train", sub_folder)
-
-    if sub_folder.endswith("9hr"):
-        limited_ids_paths = [os.path.join(sub_path, "handles.txt")]
-    else:  # => sub_folder.endswith("1hr")
-        # in case of 1 hour limited supervision ("train.1h") there are always 6 subfolders like:
-        # "limited_supervision/1h/0/handles.txt", "limited_supervision/1h/1/handles.txt", ...
-        limited_ids_paths = [os.path.join(sub_path, str(i), "handles.txt") for i in range(6)]
-
-    limited_ids_paths = dl_manager.download(limited_ids_paths)
-
-    return limited_ids_paths
-
-
-def download_extract_transcript(dl_manager, root_dir, split):
-    """
-    Download file with audio transcriptions.
-
-    Return:
-        path (str): path to locally extracted `transcripts.txt` file
-    """
-    transcript_path = os.path.join(root_dir, split, "transcripts.txt")
-    return dl_manager.download(transcript_path)
-
-
-def download_audio_archive_paths(dl_manager, root_dir, split):
-    # each split contains many .tar.gz archives with its audio files
-    # audio_filenames.txt contains the names of these archives
-    split_dir = os.path.join(root_dir, split)
-    audio_filenames_path = dl_manager.download(os.path.join(split_dir, "audio_filenames.txt"))
-
-    with open(audio_filenames_path, "r", encoding="utf-8") as file:
-        audio_filenames = [line.strip() for line in file.readlines()]
-
-    return dl_manager.download([os.path.join(split_dir, "audio", filename) for filename in audio_filenames])
-
-
-# for non-streaming case
-def download_extract_audio_archives(dl_manager, root_dir, split):
-    """
-    Download and extract audio archives locally.
-
-    Return:
-         archive_paths (List `str`): paths to locally extracted archives
-    """
-    archive_paths = download_audio_archive_paths(dl_manager, root_dir, split)
-    return [dl_manager.extract(archive_path) for archive_path in archive_paths]
-
-
-# for streaming case
-def download_audio_archives(dl_manager, root_dir, split):
-    """Prepare archives with audio files for iterating over them.
-
-    Return:
-        audio_archives (List `Generator`): list of generators to iterate over files in each audio archive.
-    """
-    archive_paths = download_audio_archive_paths(dl_manager, root_dir, split)
-    return [dl_manager.iter_archive(archive_path) for archive_path in archive_paths]