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https://github.com/k2-fsa/icefall.git
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80 lines
2.1 KiB
Python
Executable File
80 lines
2.1 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2022 Xiaomi Corp. (authors: Fangjun Kuang)
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#
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# See ../../../../LICENSE for clarification regarding multiple authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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To run this file, do:
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cd icefall/egs/librispeech/ASR
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python ./local/test_compile_lg.py
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"""
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from pathlib import Path
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from typing import List
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import k2
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import sentencepiece as spm
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import torch
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lang_dir = Path("./data/lang_bpe_500")
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def get_word_ids(word_table: k2.SymbolTable, s: str) -> List[int]:
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"""
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Args:
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word_table:
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Word symbol table.
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s:
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A string consisting of space(s) separated words.
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Returns:
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Return a list of word IDs.
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"""
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ans = []
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for w in s.split():
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ans.append(word_table[w])
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return ans
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def main():
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assert lang_dir.exists(), f"{lang_dir} does not exist!"
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LG = k2.Fsa.from_dict(torch.load(f"{lang_dir}/LG.pt", map_location="cpu"))
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sp = spm.SentencePieceProcessor()
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sp.load(f"{lang_dir}/bpe.model")
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word_table = k2.SymbolTable.from_file(f"{lang_dir}/words.txt")
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s = "HELLO WORLD"
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token_ids = sp.encode(s)
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token_fsa = k2.linear_fsa(token_ids)
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fsa = k2.intersect(LG, token_fsa)
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fsa = k2.connect(fsa)
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print(k2.to_dot(fsa))
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print(fsa.properties_str)
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print(LG.properties_str)
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# You can use https://dreampuf.github.io/GraphvizOnline/
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# to visualize the output.
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#
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# You can see that the resulting fsa is not deterministic
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# Note: LG is non-deterministic
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#
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# See https://shorturl.at/uIL69
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# for visualization of the above fsa.
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if __name__ == "__main__":
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main()
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