# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. # # 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. """Evaluation for U2 model.""" import cProfile from yacs.config import CfgNode from paddlespeech.s2t.training.cli import default_argument_parser from paddlespeech.s2t.utils.dynamic_import import dynamic_import from paddlespeech.s2t.utils.utility import print_arguments model_test_alias = { "u2": "paddlespeech.s2t.exps.u2.model:U2Tester", "u2_kaldi": "paddlespeech.s2t.exps.u2_kaldi.model:U2Tester", } def main_sp(config, args): class_obj = dynamic_import(args.model_name, model_test_alias) exp = class_obj(config, args) with exp.eval(): exp.setup() if args.run_mode == 'test': exp.run_test() elif args.run_mode == 'export': exp.run_export() elif args.run_mode == 'align': exp.run_align() def main(config, args): main_sp(config, args) if __name__ == "__main__": parser = default_argument_parser() parser.add_argument( '--model-name', type=str, default='u2_kaldi', help='model name, e.g: deepspeech2, u2, u2_kaldi, u2_st') parser.add_argument( '--run-mode', type=str, default='test', help='run mode, e.g. test, align, export') parser.add_argument( '--dict-path', type=str, default=None, help='dict path.') # save asr result to parser.add_argument( "--result-file", type=str, help="path of save the asr result") # save jit model to parser.add_argument( "--export-path", type=str, help="path of the jit model to save") args = parser.parse_args() print_arguments(args, globals()) config = CfgNode() config.set_new_allowed(True) config.merge_from_file(args.config) if args.opts: config.merge_from_list(args.opts) config.freeze() print(config) if args.dump_config: with open(args.dump_config, 'w') as f: print(config, file=f) # Setting for profiling pr = cProfile.Profile() pr.runcall(main, config, args) pr.dump_stats('test.profile')