You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
66 lines
2.0 KiB
66 lines
2.0 KiB
# 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.
|
|
"""Trainer for U2 model."""
|
|
import cProfile
|
|
import os
|
|
|
|
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_train_alias = {
|
|
"u2": "paddlespeech.s2t.exps.u2.model:U2Trainer",
|
|
"u2_kaldi": "paddlespeech.s2t.exps.u2_kaldi.model:U2Trainer",
|
|
}
|
|
|
|
|
|
def main_sp(config, args):
|
|
class_obj = dynamic_import(args.model_name, model_train_alias)
|
|
exp = class_obj(config, args)
|
|
exp.setup()
|
|
exp.run()
|
|
|
|
|
|
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')
|
|
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(os.path.join(args.output, 'train.profile'))
|