Upload my_stt_dataset.py

my_stt_dataset.py

@@ -20,9 +20,12 @@ class STTConfig(BuilderConfig):
 class MySTTDataset(datasets.GeneratorBasedBuilder):
     """
     Uzbek STT dataset yuklash skripti:
-      - Audio fayllar .tar arxiv ichida joylashgan.
-      - Transkripsiya ma'lumotlari mos TSV faylda.
-      - "audio" ustuni Audio() tipida aniqlangan, shuning uchun Hub Viewer "play" tugmasini ko'rsatadi.
+      - Audio fayllar .tar arxiv ichida saqlangan.
+      - Transkripsiya ma'lumotlari TSV faylda joylashgan.
+      - Streaming rejimida, tar fayllar dl_manager.iter_archive() orqali o‘qiladi.
+      - "audio" ustuni Audio() tipida aniqlangan, ya'ni qiymat dictionary shaklida:
+            {"path": <tar ichidagi fayl nomi>, "bytes": <audio baytlari>}
+        bo‘lishi kerak, shunda Dataset Viewer "play" tugmasini ko‘rsatadi.
     """
     VERSION = datasets.Version("1.0.0")
 
@@ -40,13 +43,18 @@ class MySTTDataset(datasets.GeneratorBasedBuilder):
     def _info(self):
         """
         Dataset ustunlarini aniqlaydi.
-        "audio" ustuni Audio() tipida belgilangan – bu orqali Viewer audio faylni avtomatik dekodlaydi.
+        "audio" ustuni Audio(sampling_rate=None) tipida berilgan, shuning uchun
+        audio fayllar avtomatik dekodlanadi va resample qilinadi.
         """
         return datasets.DatasetInfo(
-            description="Uzbek STT dataset: audio fayllar .tar arxivda, transcriptions esa TSV faylda saqlanadi.",
+            description=(
+                "Uzbek STT dataset: audio fayllar tar arxivida saqlangan va "
+                "transcriptions esa TSV faylda mavjud. Streaming rejimi bilan tar "
+                "arxivdan audio fayllar o'qiladi."
+            ),
             features=datasets.Features({
                 "id": datasets.Value("string"),
-                "audio": Audio(sampling_rate=None),  # Asl sampling rate saqlanadi
+                "audio": Audio(sampling_rate=None),
                 "sentence": datasets.Value("string"),
                 "duration": datasets.Value("float"),
                 "age": datasets.Value("string"),
@@ -60,79 +68,73 @@ class MySTTDataset(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         """
-        Har bir split uchun: tar arxiv va mos TSV fayllarining yo'llari aniqlanadi,
-        va tar fayllar dl_manager.extract() orqali ochiladi.
+        Har bir split uchun: tar arxiv va mos TSV fayllarining yo'llari aniqlanadi.
+        Tar arxivlardan streaming rejimida o'qish uchun dl_manager.iter_archive() dan foydalanamiz.
         """
         config = self.config
-        base_dir = config.data_dir  # Misol: "Dataset_STT"
-        lang = config.language_abbr   # Misol: "uz"
+        base_dir = config.data_dir  # Masalan: "Dataset_STT"
+        lang = config.language_abbr   # Masalan: "uz"
 
+        # Tar arxiv fayllari (extract qilinmaydi, balki iter_archive orqali o'qiladi)
         train_tar = os.path.join(base_dir, "audio", lang, "train.tar")
-        train_tsv = os.path.join(base_dir, "transcript", lang, "train.tsv")
-
         test_tar = os.path.join(base_dir, "audio", lang, "test.tar")
-        test_tsv = os.path.join(base_dir, "transcript", lang, "test.tsv")
-
         val_tar = os.path.join(base_dir, "audio", lang, "validation.tar")
-        val_tsv = os.path.join(base_dir, "transcript", lang, "validation.tsv")
 
-        # Tar arxiv extract qilinadi:
-        train_tar_extracted = dl_manager.extract(train_tar)
-        test_tar_extracted = dl_manager.extract(test_tar)
-        val_tar_extracted = dl_manager.extract(val_tar)
+        train_audio_files = dl_manager.iter_archive(train_tar)
+        test_audio_files = dl_manager.iter_archive(test_tar)
+        val_audio_files = dl_manager.iter_archive(val_tar)
+
+        # TSV fayllar yo'li
+        train_tsv = os.path.join(base_dir, "transcript", lang, "train.tsv")
+        test_tsv = os.path.join(base_dir, "transcript", lang, "test.tsv")
+        val_tsv = os.path.join(base_dir, "transcript", lang, "validation.tsv")
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "archive_dir": train_tar_extracted,
-                    "tsv_path": train_tsv,
-                },
+                gen_kwargs={"audio_files": train_audio_files, "tsv_path": train_tsv},
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
-                gen_kwargs={
-                    "archive_dir": test_tar_extracted,
-                    "tsv_path": test_tsv,
-                },
+                gen_kwargs={"audio_files": test_audio_files, "tsv_path": test_tsv},
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "archive_dir": val_tar_extracted,
-                    "tsv_path": val_tsv,
-                },
+                gen_kwargs={"audio_files": val_audio_files, "tsv_path": val_tsv},
             ),
         ]
 
-    def _generate_examples(self, archive_dir, tsv_path):
+    def _generate_examples(self, audio_files, tsv_path):
         """
         TSV faylini qatorma-qator o'qiydi va metadata lug'atini tuzadi.
-        Keyin, archive papkasidan mos .mp3 faylni topib,
-        audio ustunini quyidagicha shakllantiradi:
-            {"path": <relative file name>, "bytes": <audio file baytlari>}
-        Bu shakl Dataset Viewer tomonidan Audio() sifatida aniqlanib, "play" tugmasini ko'rsatishga imkon beradi.
+        So'ng, tar arxividan kelayotgan audio fayllarni (streaming iteratori orqali)
+        mos metadata bilan birlashtiradi.
+        
+        Har bir audio ustuni qiymati quyidagicha shakllantiriladi:
+            {"path": <tar ichidagi fayl nomi>, "bytes": <audio fayl baytlari>}
+        Bu shakl Dataset Viewer tomonidan Audio() sifatida aniqlanadi.
         """
+        # TSV faylidan metadata lug'atini tuzamiz: kalit – fayl nomi (masalan, "ID.mp3")
+        metadata = {}
         with open(tsv_path, "r", encoding="utf-8") as f:
             reader = csv.DictReader(f, delimiter="\t")
-            for idx, row in enumerate(reader):
-                audio_id = row["id"]
-                mp3_file = audio_id + ".mp3"
-                full_path = os.path.join(archive_dir, mp3_file)
+            for row in reader:
+                filename = row["id"] + ".mp3"
+                metadata[filename] = row
 
-                if os.path.isfile(full_path):
-                    with open(full_path, "rb") as audio_file:
-                        audio_bytes = audio_file.read()
-                    # MUHIM: "path" qiymatini lokal extract qilingan papka o'rniga, faqat fayl nomi sifatida uzatamiz
-                    yield idx, {
-                        "id": audio_id,
-                        "audio": {"path": mp3_file, "bytes": audio_bytes},
-                        "sentence": row.get("sentence", ""),
-                        "duration": float(row.get("duration", 0.0)),
-                        "age": row.get("age", ""),
-                        "gender": row.get("gender", ""),
-                        "accents": row.get("accents", ""),
-                        "locale": row.get("locale", ""),
-                    }
-                else:
-                    continue
+        # Tar arxivdan streaming iterator orqali o'qilgan fayllar
+        for idx, (file_path, file_obj) in enumerate(audio_files):
+            # file_path: tar arxiv ichidagi nisbiy yo'l (masalan, "009f0d56-c7db-4de3-bd3e-92a37d6f0cb9.mp3")
+            if file_path in metadata:
+                row = metadata[file_path]
+                audio_bytes = file_obj.read()
+                yield idx, {
+                    "id": row["id"],
+                    "audio": {"path": file_path, "bytes": audio_bytes},
+                    "sentence": row.get("sentence", ""),
+                    "duration": float(row.get("duration", 0.0)),
+                    "age": row.get("age", ""),
+                    "gender": row.get("gender", ""),
+                    "accents": row.get("accents", ""),
+                    "locale": row.get("locale", ""),
+                }