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PaddleSpeech/deepspeech/exps/u2_kaldi/bin/test.py

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2.5 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.
"""Evaluation for U2 model."""
import cProfile
from yacs.config import CfgNode
from deepspeech.training.cli import default_argument_parser
from deepspeech.utils.dynamic_import import dynamic_import
from deepspeech.utils.utility import print_arguments
model_test_alias = {
"u2": "deepspeech.exps.u2.model:U2Tester",
"u2_kaldi": "deepspeech.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)
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')