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https://github.com/k2-fsa/icefall.git
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103 lines
2.8 KiB
Python
Executable File
103 lines
2.8 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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This script takes as input an FST in k2 format and convert it
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to an FST in OpenFST format.
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The generated FST is saved into a binary file and its type is
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StdVectorFst.
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Usage examples:
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(1) Convert an acceptor
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./convert-k2-to-openfst.py in.pt binary.fst
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(2) Convert a transducer
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./convert-k2-to-openfst.py --olabels aux_labels in.pt binary.fst
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"""
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import argparse
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import logging
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from pathlib import Path
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import k2
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import kaldifst.utils
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import torch
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def get_args():
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--olabels",
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type=str,
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default=None,
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help="""If not empty, the input FST is assumed to be a transducer
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and we use its attribute specified by "olabels" as the output labels.
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""",
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)
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parser.add_argument(
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"input_filename",
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type=str,
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help="Path to the input FST in k2 format",
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)
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parser.add_argument(
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"output_filename",
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type=str,
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help="Path to the output FST in OpenFst format",
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)
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return parser.parse_args()
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def main():
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args = get_args()
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logging.info(f"{vars(args)}")
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input_filename = args.input_filename
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output_filename = args.output_filename
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olabels = args.olabels
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if Path(output_filename).is_file():
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logging.info(f"{output_filename} already exists - skipping")
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return
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assert Path(input_filename).is_file(), f"{input_filename} does not exist"
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logging.info(f"Loading {input_filename}")
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k2_fst = k2.Fsa.from_dict(torch.load(input_filename))
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if olabels:
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assert hasattr(k2_fst, olabels), f"No such attribute: {olabels}"
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p = Path(output_filename).parent
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if not p.is_dir():
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logging.info(f"Creating {p}")
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p.mkdir(parents=True)
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logging.info("Converting (May take some time if the input FST is large)")
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fst = kaldifst.utils.k2_to_openfst(k2_fst, olabels=olabels)
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logging.info(f"Saving to {output_filename}")
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fst.write(output_filename)
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if __name__ == "__main__":
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formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
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logging.basicConfig(format=formatter, level=logging.INFO)
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main()
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