Delete my_stt_dataset.py

my_stt_dataset.py

@@ -1,140 +0,0 @@
-import os
-import csv
-import datasets
-from datasets import Audio, BuilderConfig
-
-# Konfiguratsiya sinfi: til qisqartmasi va ma'lumotlar joylashgan papkani belgilaydi.
-class STTConfig(BuilderConfig):
-    def __init__(self, language_abbr, data_dir, **kwargs):
-        """
-        Args:
-            language_abbr (str): Masalan, "uz".
-            data_dir (str): Dataset joylashgan asosiy papka, masalan "Dataset_STT".
-            **kwargs: Qolgan parametrlar.
-        """
-        super().__init__(**kwargs)
-        self.language_abbr = language_abbr
-        self.data_dir = data_dir
-
-# Dataset yuklash skripti
-class MySTTDataset(datasets.GeneratorBasedBuilder):
-    """
-    Uzbek STT dataset yuklash skripti:
-      - 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")
-
-    BUILDER_CONFIGS = [
-        STTConfig(
-            name="uz",
-            version=datasets.Version("1.0.0"),
-            description="Uzbek subset of the STT dataset",
-            language_abbr="uz",
-            data_dir="Dataset_STT",  # Asosiy papka nomi
-        )
-    ]
-    DEFAULT_CONFIG_NAME = "uz"
-
-    def _info(self):
-        """
-        Dataset ustunlarini aniqlaydi.
-        "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 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),
-                "sentence": datasets.Value("string"),
-                "duration": datasets.Value("float"),
-                "age": datasets.Value("string"),
-                "gender": datasets.Value("string"),
-                "accents": datasets.Value("string"),
-                "locale": datasets.Value("string"),
-            }),
-            supervised_keys=None,
-            version=self.VERSION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """
-        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  # 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")
-        test_tar = os.path.join(base_dir, "audio", lang, "test.tar")
-        val_tar = os.path.join(base_dir, "audio", lang, "validation.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={"audio_files": train_audio_files, "tsv_path": train_tsv},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"audio_files": test_audio_files, "tsv_path": test_tsv},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"audio_files": val_audio_files, "tsv_path": val_tsv},
-            ),
-        ]
-
-    def _generate_examples(self, audio_files, tsv_path):
-        """
-        TSV faylini qatorma-qator o'qiydi va metadata lug'atini tuzadi.
-        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 row in reader:
-                filename = row["id"] + ".mp3"
-                metadata[filename] = row
-
-        # 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", ""),
-                }