Upload my_stt_dataset.py

my_stt_dataset.py

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+import os
+import tarfile
+import csv
+
+import datasets
+from datasets import Audio
+
+
+class MySTTDatasetConfig(datasets.BuilderConfig):
+    """Config klass (kerak bo'lsa turli versiya yoki param qo'yish uchun)."""
+
+
+class MySTTDataset(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        MySTTDatasetConfig(name="default", version=datasets.Version("1.0.0")),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="STT dataset .tar ichida audio, .tsv ichida transkript",
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "audio": Audio(sampling_rate=None),  # Audio turi
+                    "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,
+        )
+
+    def _split_generators(self, dl_manager):
+        """
+          dl_manager.download_and_extract() bilan remote fayllarni yuklaysiz
+          yoki local path bersangiz bo'ladi.
+          Masalan: 
+            https://huggingface.co/datasets/Elyordev/new_dataset_stt/resolve/main/Dataset_STT/audio/uz/train/train.tar
+            https://huggingface.co/datasets/Elyordev/new_dataset_stt/resolve/main/Dataset_STT/transcript/uz/train/train.tsv
+        """
+        train_tar = dl_manager.download_and_extract("URL_train_tar")  # masalan
+        train_tsv = dl_manager.download("URL_train_tsv")
+
+        val_tar = dl_manager.download_and_extract("URL_val_tar")
+        val_tsv = dl_manager.download("URL_val_tsv")
+
+        test_tar = dl_manager.download_and_extract("URL_test_tar")
+        test_tsv = dl_manager.download("URL_test_tsv")
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "archive_path": train_tar,
+                    "tsv_path": train_tsv,
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "archive_path": val_tar,
+                    "tsv_path": val_tsv,
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "archive_path": test_tar,
+                    "tsv_path": test_tsv,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, archive_path, tsv_path):
+        """
+         Har bir tar faylni ochib, TSV dagi id + sentence boshqariladi.
+        """
+        # `archive_path` bu dl_manager.download_and_extract qilgan manzil
+        # lekin e’tibor bering: .extract automatik ravishda chiqarib yuboradi.
+        # Agar `.tar` ochilmasin desangiz, download() deyish kifoya, 
+        # lekin streaming qilish uchun biroz boshqacha yo'l tutish kerak.
+
+        # Keling, bu yerda tar fayl allaqachon extract qilingan deb faraz qilamiz:
+        #  train.tar -> train/ (ichida mp3 fayllar paydo bo'lgan bo'ladi).
+        #  Agar real .tar ichidan "on-the-fly" o'qimoqchi bo'lsak, 
+        #  dl_manager.download() + tarfile.open(...) da ishlash lozim.
+
+        # Shunchaki misol tariqasida:
+        audio_base_path = archive_path  # extract bo'lgach papka manzili
+        # Ehtimol, audio_base_path = os.path.join(archive_path, "train") bo'lishi ham mumkin
+        # chunki tar ichida "train/" deb nomlangan ichki papka bo'lishi mumkin.
+
+        with open(tsv_path, "r", encoding="utf-8") as f:
+            reader = csv.DictReader(f, delimiter="\t")
+            for n, row in enumerate(reader):
+                audio_id = row["id"]  # masalan '009f0d56-c7db-4de3-bd3e-92a37d6f0cb9'
+                audio_file = audio_id + ".mp3"
+                
+                # to'liq path
+                audio_path = os.path.join(audio_base_path, audio_file)
+
+                # Agar audio fayl topilsa:
+                if os.path.isfile(audio_path):
+                    yield n, {
+                        "id": audio_id,
+                        "audio": audio_path,  # Audio typeda faqat path bersak, HF o'zi o'qiydi
+                        "sentence": row["sentence"],
+                        "duration": float(row["duration"]),
+                        "age": row["age"],
+                        "gender": row["gender"],
+                        "accents": row["accents"],
+                        "locale": row["locale"],
+                    }
+                else:
+                    # Agar mp3 topilmasa, o'ziz xato signal qilishingiz mumkin
+                    # yoki continue qilishingiz mumkin
+                    pass