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5a0b9bcb23
* Fix an error in TDNN-LSTM training. * WIP: Refactoring * Refactor transformer.py * Remove unused code. * Minor fixes.
60 lines
1.5 KiB
Python
Executable File
60 lines
1.5 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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This script takes as input "data/lang/bpe/train.txt"
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and generates "data/lang/bpe/bep.model".
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"""
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# You can install sentencepiece via:
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#
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# pip install sentencepiece
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#
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# Due to an issue reported in
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# https://github.com/google/sentencepiece/pull/642#issuecomment-857972030
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#
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# Please install a version >=0.1.96
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import shutil
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from pathlib import Path
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import sentencepiece as spm
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def main():
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model_type = "unigram"
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vocab_size = 5000
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model_prefix = f"data/lang_bpe/{model_type}_{vocab_size}"
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train_text = "data/lang_bpe/train.txt"
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character_coverage = 1.0
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input_sentence_size = 100000000
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user_defined_symbols = ["<blk>", "<sos/eos>"]
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unk_id = len(user_defined_symbols)
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# Note: unk_id is fixed to 2.
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# If you change it, you should also change other
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# places that are using it.
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model_file = Path(model_prefix + ".model")
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if not model_file.is_file():
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spm.SentencePieceTrainer.train(
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input=train_text,
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vocab_size=vocab_size,
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model_type=model_type,
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model_prefix=model_prefix,
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input_sentence_size=input_sentence_size,
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character_coverage=character_coverage,
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user_defined_symbols=user_defined_symbols,
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unk_id=unk_id,
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bos_id=-1,
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eos_id=-1,
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)
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sp = spm.SentencePieceProcessor(model_file=str(model_file))
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vocab_size = sp.vocab_size()
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shutil.copyfile(model_file, "data/lang_bpe/bpe.model")
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if __name__ == "__main__":
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main()
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