mirror of
https://github.com/k2-fsa/icefall.git
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ece728d895
* add init files * fix bug, apply delay penalty * fix decoding code and getting timestamps * add option applying delay penalty on ctc log-prob * fix bug of streaming decoding * minor change for bpe-based case * add test_model.py * add README.md * add CI
95 lines
2.9 KiB
Python
95 lines
2.9 KiB
Python
# Copyright 2021 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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from pathlib import Path
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from typing import List, Union
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import k2
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import sentencepiece as spm
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import torch
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class BpeCtcTrainingGraphCompiler(object):
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def __init__(
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self,
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lang_dir: Path,
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device: Union[str, torch.device] = "cpu",
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sos_token: str = "<sos/eos>",
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eos_token: str = "<sos/eos>",
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) -> None:
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"""
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Args:
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lang_dir:
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This directory is expected to contain the following files:
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- bpe.model
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- words.txt
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device:
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It indicates CPU or CUDA.
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sos_token:
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The word piece that represents sos.
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eos_token:
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The word piece that represents eos.
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"""
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lang_dir = Path(lang_dir)
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model_file = lang_dir / "bpe.model"
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sp = spm.SentencePieceProcessor()
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sp.load(str(model_file))
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self.sp = sp
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self.word_table = k2.SymbolTable.from_file(lang_dir / "words.txt")
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self.device = device
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self.sos_id = self.sp.piece_to_id(sos_token)
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self.eos_id = self.sp.piece_to_id(eos_token)
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assert self.sos_id != self.sp.unk_id()
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assert self.eos_id != self.sp.unk_id()
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def texts_to_ids(self, texts: List[str]) -> List[List[int]]:
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"""Convert a list of texts to a list-of-list of piece IDs.
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Args:
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texts:
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It is a list of strings. Each string consists of space(s)
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separated words. An example containing two strings is given below:
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['HELLO ICEFALL', 'HELLO k2']
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Returns:
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Return a list-of-list of piece IDs.
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"""
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return self.sp.encode(texts, out_type=int)
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def compile(
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self,
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piece_ids: List[List[int]],
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modified: bool = False,
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) -> k2.Fsa:
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"""Build a ctc graph from a list-of-list piece IDs.
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Args:
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piece_ids:
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It is a list-of-list integer IDs.
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modified:
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See :func:`k2.ctc_graph` for its meaning.
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Return:
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Return an FsaVec, which is the result of composing a
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CTC topology with linear FSAs constructed from the given
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piece IDs.
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"""
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graph = k2.ctc_graph(piece_ids, modified=modified, device=self.device)
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return graph
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