# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from time import perf_counter from argparse import ArgumentParser from fun_text_processing.text_normalization.en.graph_utils import generator_main def parse_args(): parser = ArgumentParser() parser.add_argument( "--language", help="language", choices=['de', 'en', 'es', 'fr', 'id', 'ja', 'ko', 'pt', 'ru', 'vi', 'zh'], default="en", type=str ) parser.add_argument( "--token_and_classify_and_verbalize", help="export the single token&classify and verbalize or combined", choices=['single', 'combine'], default="single", type=str ) parser.add_argument( "--export_dir", help="path to export directory. Default to current directory.", default="./", type=str, ) return parser.parse_args() def get_grammars(lang: str='en'): if lang=='de': from fun_text_processing.inverse_text_normalization.de.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.de.verbalizers.verbalize_final import VerbalizeFinalFst elif lang=='en': from fun_text_processing.inverse_text_normalization.en.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.en.verbalizers.verbalize_final import VerbalizeFinalFst elif lang=='es': from fun_text_processing.inverse_text_normalization.es.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.es.verbalizers.verbalize_final import VerbalizeFinalFst elif lang=='fr': from fun_text_processing.inverse_text_normalization.fr.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.fr.verbalizers.verbalize_final import VerbalizeFinalFst elif lang=='id': from fun_text_processing.inverse_text_normalization.id.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.id.verbalizers.verbalize_final import VerbalizeFinalFst elif lang=='ja': from fun_text_processing.inverse_text_normalization.ja.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.ja.verbalizers.verbalize_final import VerbalizeFinalFst elif lang=='ko': from fun_text_processing.inverse_text_normalization.ko.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.ko.verbalizers.verbalize_final import VerbalizeFinalFst elif lang=='pt': from fun_text_processing.inverse_text_normalization.pt.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.pt.verbalizers.verbalize_final import VerbalizeFinalFst elif lang=='ru': from fun_text_processing.inverse_text_normalization.ru.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.ru.verbalizers.verbalize_final import VerbalizeFinalFst elif lang=='vi': from fun_text_processing.inverse_text_normalization.vi.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.vi.verbalizers.verbalize_final import VerbalizeFinalFst elif lang=='zh': from fun_text_processing.inverse_text_normalization.zh.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.zh.verbalizers.verbalize_final import VerbalizeFinalFst else: from fun_text_processing.inverse_text_normalization.en.taggers.tokenize_and_classify import ClassifyFst from fun_text_processing.inverse_text_normalization.en.verbalizers.verbalize_final import VerbalizeFinalFst return ClassifyFst().fst, VerbalizeFinalFst().fst if __name__ == "__main__": args = parse_args() export_dir = args.export_dir os.makedirs(export_dir, exist_ok=True) tagger_far_file = os.path.join(export_dir, args.language + "_itn_tagger.far") verbalizer_far_file = os.path.join(export_dir, args.language + "_itn_verbalizer.far") tager_and_verbalizer_far_file = os.path.join(export_dir, args.language, "model.far" ) start_time = perf_counter() tagger_fst, verbalizer_fst = get_grammars(args.language) if args.token_and_classify_and_verbalize == 'single': generator_main(tagger_far_file, {"tokenize_and_classify": tagger_fst}) generator_main(verbalizer_far_file, {"verbalize": verbalizer_fst}) elif args.token_and_classify_and_verbalize == 'combine': if not os.path.exists(os.path.join(export_dir, args.language)): os.makedirs(os.path.join(export_dir, args.language)) generator_main(tager_and_verbalizer_far_file, {"tokenize_and_classify": tagger_fst, "verbalize": verbalizer_fst}) print(f'Time to generate graph: {round(perf_counter() - start_time, 2)} sec')