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import os |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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datasets.logging.set_verbosity(20) |
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_speaker_names = [ |
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'ariana_Male2', |
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'moujeze_Female1', |
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'ariana_Male1', |
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'ariana_Female1' |
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] |
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class ParsiGoo(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.0.0") |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"text": datasets.Value("string"), |
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"audio_file": datasets.Value("string"), |
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"speaker_name": datasets.Value("string"), |
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"root_path": datasets.Value("string") |
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} |
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) |
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return datasets.DatasetInfo( |
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description="ParsiGoo dataset", |
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features=features, |
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homepage="https://example.com", |
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citation="", |
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) |
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def _split_generators(self, dl_manager): |
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logger.info("| > ") |
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print("4544444") |
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print(dl_manager.manual_dir) |
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data_dir = dl_manager.download("datasets") |
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print(data_dir) |
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meta_files = [] |
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speaker_names = _speaker_names |
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root_path = "" |
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for speaker_name in speaker_names: |
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root_path = os.path.join(data_dir, speaker_name) |
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meta_files.append(os.path.join(root_path, "metadata.csv")) |
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return [datasets.SplitGenerator( |
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name="train", |
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gen_kwargs={ |
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"txt_files": meta_files, |
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"speaker_names": speaker_names, |
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"root_path": root_path |
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} |
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)] |
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def _generate_examples(self, txt_files, speaker_names, root_path): |
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print(txt_files) |
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id=-1 |
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for ind,txt_file in enumerate(txt_files): |
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with open(txt_file, "r", encoding="utf-8") as ttf: |
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for i, line in enumerate(ttf): |
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cols = line.split("|") |
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wav_file = cols[1].strip() |
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text = cols[0].strip() |
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wav_file = os.path.join(root_path, "wavs", wav_file) |
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id+=1 |
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yield id, {"text": text, "audio_file": wav_file, "speaker_name": speaker_names[ind], "root_path": root_path} |
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