Delete dataset.py

dataset.py

@@ -1,191 +0,0 @@
-# coding=utf-8
-"""
-new_dataset_stt_audio dataset.
-
-This dataset consists of audio files stored in tar archives and transcript files in TSV format.
-The dataset structure is as follows:
-
-new_dataset_stt_audio/
-├── audio/
-│   └── uz/
-│       ├── train/
-│       │   └── train.tar
-│       ├── validation/
-│       │   └── validation.tar
-│       └── test/
-│           └── test.tar
-└── transcript/
-    └── uz/
-        ├── train/
-        │   └── train.tsv
-        ├── validation/
-        │   └── validation.tsv
-        └── test/
-             └── test.tsv
-
-Each transcript TSV file has columns:
-id, path, sentence, duration, age, gender, accents, locale.
-
-The audio field is loaded using a tar URI, allowing streaming from the tar archive.
-"""
-
-import csv
-import os
-import tarfile
-from typing import Iterator, Tuple
-
-import datasets
-
-_CITATION = """\
-@misc{yourcitation2023,
-  title={Your Dataset Title},
-  author={Your Name},
-  year={2023},
-  url={https://huggingface.co/datasets/Elyordev/new_dataset_stt_audio}
-}
-"""
-
-_DESCRIPTION = """\
-This dataset consists of audio files and corresponding transcripts for speech-to-text tasks.
-The audio files are stored in tar archives under the audio/uz folder for each split (train, validation, test),
-and the transcripts are stored as TSV files under transcript/uz for each split.
-The transcript TSV files have the following columns:
-id, path, sentence, duration, age, gender, accents, locale.
-The audio is loaded using a tar URI to enable streaming.
-"""
-
-_HOMEPAGE = "https://huggingface.co/datasets/Elyordev/new_dataset_stt_audio"
-_LICENSE = "MIT"
-
-class NewDatasetSTTAudioConfig(datasets.BuilderConfig):
-    """Builder config for new_dataset_stt_audio."""
-    def __init__(self, language="uz", **kwargs):
-        super(NewDatasetSTTAudioConfig, self).__init__(**kwargs)
-        self.language = language
-
-class NewDatasetSTTAudio(datasets.GeneratorBasedBuilder):
-    """New Dataset STT Audio builder."""
-    VERSION = datasets.Version("1.0.0")
-    BUILDER_CONFIGS = [
-        NewDatasetSTTAudioConfig(
-            name="default",
-            version=VERSION,
-            description="STT dataset with audio tar archives and transcript TSV files for Uzbek language",
-            language="uz",
-        ),
-    ]
-
-    def _info(self):
-        features = datasets.Features({
-            "id": datasets.Value("string"),
-            "path": datasets.Value("string"),
-            "sentence": datasets.Value("string"),
-            "duration": datasets.Value("float"),
-            "age": datasets.Value("string"),
-            "gender": datasets.Value("string"),
-            "accents": datasets.Value("string"),
-            "locale": datasets.Value("string"),
-            "audio": datasets.Audio(sampling_rate=16000),
-        })
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """
-        Returns SplitGenerators.
-        Expects the dataset to be provided manually via the repository.
-        The manual_dir should contain the following structure:
-        
-        new_dataset_stt_audio/
-          audio/uz/{train, validation, test}/*.tar
-          transcript/uz/{train, validation, test}/*.tsv
-        """
-        manual_dir = dl_manager.manual_dir if dl_manager.manual_dir is not None else ""
-        language = self.config.language
-
-        splits = {
-            "train": {
-                "transcript": os.path.join(manual_dir, "transcript", language, "train", "train.tsv"),
-                "audio": os.path.join(manual_dir, "audio", language, "train", "train.tar")
-            },
-            "validation": {
-                "transcript": os.path.join(manual_dir, "transcript", language, "validation", "validation.tsv"),
-                "audio": os.path.join(manual_dir, "audio", language, "validation", "validation.tar")
-            },
-            "test": {
-                "transcript": os.path.join(manual_dir, "transcript", language, "test", "test.tsv"),
-                "audio": os.path.join(manual_dir, "audio", language, "test", "test.tar")
-            }
-        }
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "transcript_path": splits["train"]["transcript"],
-                    "audio_tar_path": splits["train"]["audio"],
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "transcript_path": splits["validation"]["transcript"],
-                    "audio_tar_path": splits["validation"]["audio"],
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "transcript_path": splits["test"]["transcript"],
-                    "audio_tar_path": splits["test"]["audio"],
-                },
-            ),
-        ]
-
-    def _generate_examples(self, transcript_path: str, audio_tar_path: str) -> Iterator[Tuple[str, dict]]:
-        """
-        Yields examples as (key, example) tuples.
-
-        Args:
-            transcript_path (str): Path to the transcript TSV file.
-            audio_tar_path (str): Path to the audio tar archive.
-        """
-        # 1. Read the transcript TSV file into a dictionary mapping file name to metadata.
-        metadata_map = {}
-        with open(transcript_path, encoding="utf-8") as f:
-            reader = csv.DictReader(f, delimiter="\t")
-            for row in reader:
-                file_name = row["path"].strip()
-                if not file_name.endswith(".mp3"):
-                    file_name += ".mp3"
-                metadata_map[file_name] = row
-
-        # 2. Create a base audio URI for streaming from the tar archive.
-        base_audio_uri = f"tar://{audio_tar_path}#"
-        
-        # 3. Open the tar archive and iterate through its members.
-        id_ = 0
-        with tarfile.open(audio_tar_path, "r") as tar:
-            for member in tar.getmembers():
-                file_name = os.path.basename(member.name)
-                if file_name in metadata_map:
-                    row = metadata_map[file_name]
-                    audio_uri = base_audio_uri + file_name
-                    yield str(id_), {
-                        "id": row["id"],
-                        "path": row["path"],
-                        "sentence": row["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_uri,
-                    }
-                    id_ += 1