Upload dataset.py

dataset.py

@@ -1,222 +1,48 @@
-# coding=utf-8
-# Copyright 2023
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Ushbu fayl Common Voice uslubidagi dataset loading script bo'lib,
-# audio/uz/<split>/<split>.tar va transcript/uz/<split>/<split>.tsv
-# fayllarni yuklab, audio+transkriptsiyani birlashtiradi.
-
 import os
 import csv
-import json
-
-import datasets
-from datasets.utils.py_utils import size_str
-
-
-# ------------------ 1. Metadata va sozlamalar ------------------
-_CITATION = """\
-@misc{yourcitation,
-  title  = {Your STT dataset title},
-  author = {You or your org},
-  year   = {2023},
-  url    = {https://huggingface.co/datasets/Elyordev/new_dataset_stt_audio}
-}
-"""
-
-_DESCRIPTION = """\
-Bu dataset mp3 formatdagi audio fayllar va tsv metadata fayllardan iborat.
-Papka tuzilishi Common Voice uslubiga o'xshash:
-audio/uz/[train|validation|test]/*.tar va transcript/uz/[train|validation|test]/*.tsv
-"""
-
-_HOMEPAGE = "https://huggingface.co/datasets/Elyordev/new_dataset_stt_audio"
-_LICENSE = "Apache License 2.0"
-
-# Bitta til: "uz" (xohlasangiz ko'paytirishingiz mumkin)
-LANGUAGES = {
-    "uz": {
-        "language_name": "Uzbek",
-        "num_clips": None,      # Agar xohlasangiz, taxminiy klip sonini kiriting
-        "num_speakers": None,
-        "validated_hr": None,
-        "total_hr": None,
-        "size_bytes": None,
-    },
-}
-
-# Bizda har bir splitda 1 dona tar shard bor deb faraz qilamiz
-N_SHARDS = {
-    "uz": {
-        "train": 1,
-        "validation": 1,
-        "test": 1,
-    }
-}
-
-# Asosiy URL: repodagi fayllarni resolve qilish uchun
-_BASE_URL = "https://huggingface.co/datasets/Elyordev/new_dataset_stt_audio/resolve/main/"
-
-# Audio fayl yo'li: audio/uz/<split>/<split>.tar
-_AUDIO_URL = _BASE_URL + "audio/{lang}/{split}/{split}.tar"
-
-# Transcript fayl yo'li: transcript/uz/<split>/<split>.tsv
-_TRANSCRIPT_URL = _BASE_URL + "transcript/{lang}/{split}/{split}.tsv"
-
-
-# ------------------ 2. Config klassi ------------------
-class NewDatasetSTTAudioConfig(datasets.BuilderConfig):
-    """Bitta config (masalan, 'uz') - xohlasangiz ko'proq tillarni ham qo'shishingiz mumkin."""
-    def __init__(self, language, **kwargs):
-        super().__init__(**kwargs)
-        self.language = language
-        self.num_clips = LANGUAGES[language]["num_clips"]
-        self.num_speakers = LANGUAGES[language]["num_speakers"]
-        self.validated_hr = LANGUAGES[language]["validated_hr"]
-        self.total_hr = LANGUAGES[language]["total_hr"]
-        self.size_bytes = LANGUAGES[language]["size_bytes"]
-        self.size_human = size_str(self.size_bytes) if self.size_bytes else None
-
-
-# ------------------ 3. Asosiy dataset builder ------------------
-class NewDatasetSTTAudio(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        # Masalan, faqat "uz" config
-        NewDatasetSTTAudioConfig(
-            name="uz",
-            version=datasets.Version("1.0.0"),
-            description="Uzbek STT dataset with Common Voice-like structure",
-            language="uz",
-        ),
-    ]
-    DEFAULT_WRITER_BATCH_SIZE = 1000
-
-    def _info(self):
-        lang = self.config.language
-        # O'zingiz xohlagancha izoh tuzishingiz mumkin
-        description = (
-            f"Common Voice uslubidagi dataset: til = {lang}. "
-            f"{_DESCRIPTION}"
-        )
-        features = datasets.Features(
-            {
-                "id": datasets.Value("string"),
-                "path": datasets.Value("string"),
-                "audio": datasets.features.Audio(sampling_rate=16000),  # agar 16kHz bo'lsa
-                "sentence": datasets.Value("string"),
-                "age": datasets.Value("string"),
-                "gender": datasets.Value("string"),
-                "accents": datasets.Value("string"),
-                "locale": datasets.Value("string"),
-                "duration": datasets.Value("float"),  # agar tsv da float bo'lsa
-            }
-        )
-        return datasets.DatasetInfo(
-            description=description,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-            version=self.config.version,
-        )
-
-    def _split_generators(self, dl_manager):
-        """
-        Common Voice misolida bo'lgani kabi:
-        train, validation, test splitlari uchun tar va tsv fayllarni yuklaymiz.
-        """
-        lang = self.config.language
-        n_shards = N_SHARDS[lang]  # {'train':1, 'validation':1, 'test':1}
-        split_generators = []
-
-        # Bizda splits = ["train", "validation", "test"]
-        for split in ["train", "validation", "test"]:
-            # Audio (tar) URL lar ro'yxati (har bir splitda bitta shard)
-            audio_urls = [
-                _AUDIO_URL.format(lang=lang, split=split, shard_idx=i)
-                for i in range(n_shards[split])
-            ]
-            # .tar fayllarni yuklab olamiz
-            audio_paths = dl_manager.download(audio_urls)
-
-            # .tar fayllarni streaming yoki to'liq extract qilamiz
-            # Common Voice 'iter_archive' orqali stream qiladi, lekin biz local_extracted qilsak ham bo'ladi
-            local_extracted_archive_paths = []
-            if not dl_manager.is_streaming:
-                local_extracted_archive_paths = dl_manager.extract(audio_paths)
-
-            # Transcript (tsv) URL
-            transcript_url = _TRANSCRIPT_URL.format(lang=lang, split=split)
-            transcript_path = dl_manager.download_and_extract(transcript_url)
-
-            split_generators.append(
-                datasets.SplitGenerator(
-                    name=getattr(datasets.Split, split.upper()),
-                    gen_kwargs={
-                        "archives": [
-                            dl_manager.iter_archive(path) for path in audio_paths
-                        ],
-                        "local_extracted_archive_paths": local_extracted_archive_paths,
-                        "meta_path": transcript_path,
-                    },
-                )
-            )
-
-        return split_generators
-
-    def _generate_examples(self, archives, local_extracted_archive_paths, meta_path):
-        """
-        Har bir split uchun:
-        1) transcript .tsv faylni o'qish
-        2) audio tar ichidagi fayllarni "archives" orqali iteratsiya qilish
-        3) tsv'dagi 'path' bilan audio fayl nomini bog'lash
-        4) natijada (key, example) qaytarish
-        """
-        # Tsv fayl (meta_path) ni o'qib, metadata lug'atini tuzamiz
-        # formati: { "filename.mp3": { ... ustunlar ... } }
-        metadata = {}
-        with open(meta_path, encoding="utf-8") as f:
-            reader = csv.DictReader(f, delimiter="\t")
-            for row in reader:
-                # Ehtiyot chorasi: agar path .mp3 bilan tugamasa, qo'shamiz
-                if not row["path"].endswith(".mp3"):
-                    row["path"] += ".mp3"
-                metadata[row["path"]] = row
-
-        # Endi tar fayllarni o'qish
-        # Common Voice misolida bir splitda bir nechta shard bo'lishi mumkin, shuning uchun ro'yxat
-        for shard_idx, archive in enumerate(archives):
-            # archive = dl_manager.iter_archive(path) => (path_in_tar, fileobj) generator
-            for path_in_tar, fileobj in archive:
-                # Masalan, path_in_tar = "common_voice_uz_12345.mp3"
-                _, filename = os.path.split(path_in_tar)
-                if filename in metadata:
-                    # Metadata qatorini olish
-                    row = metadata[filename]
-                    # local_extracted_archive_paths[shard_idx] => .tar fayl extract qilingan joy
-                    # Agar to'liq extract bo'lmagan bo'lsa, to'g'ridan-to'g'ri bytes bilan ham ishlasa bo'ladi
-                    # Common Voice rasmiy misolida 'result["audio"] = {"path": path, "bytes": file.read()}' qilingan
-
-                    example = dict(row)
-                    # "id" ustuni bo'lmasa, idx sifatida path_in_tar dan foydalansa bo'ladi
-                    if "id" not in example:
-                        example["id"] = filename
-
-                    # Audio: tar fayl ichidan o'qilgan bytes
-                    # Datasets "Audio" featuri "bytes" ni o'z-o'zidan tan olmaydi,
-                    # lekin "path" + "bytes" berish uslubi Common Voice scriptida ishlatilgan
-                    # Keyingi bosqichda decode qilinadi
-                    example["audio"] = {
-                        "path": path_in_tar,
-                        "bytes": fileobj.read(),
-                    }
-
-                    # Qo'shimcha ustunlarni ham row dan olamiz:
-                    # sentence, age, gender, accents, locale, duration, ...
-                    # Agar bo'lmasa, bo'sh qiymat kiritiladi
-                    # Biz "metadata"dan oldin dict(row) deb oldik, demak "example"da hamma ustun bor.
-
-                    yield path_in_tar, example
+import tarfile
+
+def _generate_examples(self, prompts_path, audio_tar_path):
+    """
+    Yields examples as (key, example) tuples.
+
+    Args:
+        prompts_path (str): transcript/uz/<split>/<split>.tsv – metadata fayl yo'li.
+        audio_tar_path (str): audio/uz/<split>/<split>.tar – tar arxiv yo'li (ichida *.mp3).
+    """
+    # 1. TSV fayldan metadata ni o'qish
+    metadata_map = {}
+    with open(prompts_path, encoding="utf-8") as f:
+        reader = csv.DictReader(f, delimiter="\t")
+        for row in reader:
+            # "path" ustunida fayl nomi bo'lishi kutiladi, masalan: "H3H38EY38D8.mp3"
+            file_name = row["path"].strip()
+            if not file_name.endswith(".mp3"):
+                file_name += ".mp3"
+            metadata_map[file_name] = row
+
+    # 2. Tar arxiv ichidan audio fayllarni o'qish
+    id_ = 0
+    with tarfile.open(audio_tar_path, "r") as tar:
+        for member in tar.getmembers():
+            # Tar ichidagi fayl nomidan faqat fayl nomini olish
+            file_name = os.path.basename(member.name)
+            if file_name in metadata_map:
+                row = metadata_map[file_name]
+                audio_file = tar.extractfile(member)
+                if audio_file is None:
+                    continue  # Agar fayl ochilmasa, o'tkazib yuboramiz
+                audio_bytes = audio_file.read()
+                audio = {"path": file_name, "bytes": audio_bytes}
+                yield id_, {
+                    "id": row.get("id", file_name),
+                    "path": row.get("path", file_name),
+                    "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", ""),
+                    "audio": audio,
+                }
+                id_ += 1