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https://github.com/modelscope/FunASR
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嘉渊
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funasr/bin/asr_test.py
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226
funasr/bin/asr_test.py
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import argparse
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import logging
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import os
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import sys
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from funasr.utils import config_argparse
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from funasr.utils.cli_utils import get_commandline_args
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from funasr.utils.types import str2bool
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from funasr.utils.types import str2triple_str
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from funasr.utils.types import str_or_none
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def get_parser():
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parser = config_argparse.ArgumentParser(
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description="ASR Decoding",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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)
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# Note(kamo): Use '_' instead of '-' as separator.
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# '-' is confusing if written in yaml.
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parser.add_argument(
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"--log_level",
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type=lambda x: x.upper(),
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default="INFO",
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choices=("CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG", "NOTSET"),
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help="The verbose level of logging",
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)
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parser.add_argument("--output_dir", type=str, required=True)
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parser.add_argument(
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"--ngpu",
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type=int,
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default=0,
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help="The number of gpus. 0 indicates CPU mode",
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)
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parser.add_argument(
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"--njob",
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type=int,
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default=1,
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help="The number of jobs for each gpu",
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)
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parser.add_argument(
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"--gpuid_list",
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type=str,
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default="",
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help="The visible gpus",
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)
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parser.add_argument("--seed", type=int, default=0, help="Random seed")
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parser.add_argument(
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"--dtype",
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default="float32",
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choices=["float16", "float32", "float64"],
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help="Data type",
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)
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parser.add_argument(
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"--num_workers",
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type=int,
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default=1,
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help="The number of workers used for DataLoader",
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)
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group = parser.add_argument_group("Input data related")
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group.add_argument(
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"--data_path_and_name_and_type",
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type=str2triple_str,
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required=True,
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action="append",
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)
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group.add_argument("--key_file", type=str_or_none)
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group.add_argument("--allow_variable_data_keys", type=str2bool, default=False)
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group = parser.add_argument_group("The model configuration related")
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group.add_argument(
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"--vad_infer_config",
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type=str,
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help="VAD infer configuration",
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)
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group.add_argument(
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"--vad_model_file",
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type=str,
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help="VAD model parameter file",
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)
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group.add_argument(
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"--cmvn_file",
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type=str,
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help="Global CMVN file",
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)
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group.add_argument(
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"--asr_train_config",
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type=str,
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help="ASR training configuration",
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)
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group.add_argument(
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"--asr_model_file",
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type=str,
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help="ASR model parameter file",
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)
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group.add_argument(
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"--lm_train_config",
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type=str,
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help="LM training configuration",
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)
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group.add_argument(
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"--lm_file",
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type=str,
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help="LM parameter file",
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)
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group.add_argument(
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"--word_lm_train_config",
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type=str,
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help="Word LM training configuration",
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)
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group.add_argument(
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"--word_lm_file",
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type=str,
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help="Word LM parameter file",
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)
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group.add_argument(
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"--ngram_file",
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type=str,
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help="N-gram parameter file",
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)
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group.add_argument(
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"--model_tag",
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type=str,
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help="Pretrained model tag. If specify this option, *_train_config and "
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"*_file will be overwritten",
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)
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group = parser.add_argument_group("Beam-search related")
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group.add_argument(
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"--batch_size",
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type=int,
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default=1,
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help="The batch size for inference",
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)
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group.add_argument("--nbest", type=int, default=5, help="Output N-best hypotheses")
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group.add_argument("--beam_size", type=int, default=20, help="Beam size")
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group.add_argument("--penalty", type=float, default=0.0, help="Insertion penalty")
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group.add_argument(
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"--maxlenratio",
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type=float,
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default=0.0,
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help="Input length ratio to obtain max output length. "
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"If maxlenratio=0.0 (default), it uses a end-detect "
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"function "
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"to automatically find maximum hypothesis lengths."
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"If maxlenratio<0.0, its absolute value is interpreted"
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"as a constant max output length",
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)
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group.add_argument(
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"--minlenratio",
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type=float,
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default=0.0,
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help="Input length ratio to obtain min output length",
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)
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group.add_argument(
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"--ctc_weight",
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type=float,
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default=0.0,
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help="CTC weight in joint decoding",
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)
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group.add_argument("--lm_weight", type=float, default=1.0, help="RNNLM weight")
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group.add_argument("--ngram_weight", type=float, default=0.9, help="ngram weight")
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group.add_argument("--streaming", type=str2bool, default=False)
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group = parser.add_argument_group("Text converter related")
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group.add_argument(
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"--token_type",
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type=str_or_none,
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default=None,
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choices=["char", "bpe", None],
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help="The token type for ASR model. "
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"If not given, refers from the training args",
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)
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group.add_argument(
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"--bpemodel",
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type=str_or_none,
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default=None,
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help="The model path of sentencepiece. "
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"If not given, refers from the training args",
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)
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group.add_argument("--token_num_relax", type=int, default=1, help="")
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group.add_argument("--decoding_ind", type=int, default=0, help="")
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group.add_argument("--decoding_mode", type=str, default="model1", help="")
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group.add_argument(
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"--ctc_weight2",
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type=float,
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default=0.0,
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help="CTC weight in joint decoding",
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)
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return parser
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def main(cmd=None):
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print(get_commandline_args(), file=sys.stderr)
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parser = get_parser()
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parser.add_argument(
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"--mode",
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type=str,
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default="asr",
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help="The decoding mode",
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)
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args = parser.parse_args(cmd)
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kwargs = vars(args)
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kwargs.pop("config", None)
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# set logging messages
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logging.basicConfig(
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level=args.log_level,
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format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s",
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)
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logging.info("Decoding args: {}".format(kwargs))
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# gpu setting
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if args.ngpu > 0:
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jobid = int(args.output_dir.split(".")[-1])
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gpuid = args.gpuid_list.split(",")[(jobid - 1) // args.njob]
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os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
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os.environ["CUDA_VISIBLE_DEVICES"] = gpuid
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# inference_launch_funasr(**kwargs)
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if __name__ == "__main__":
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main()
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