From c9f1b4e8a2e903f74de20d019e70307c26e93c3e Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期四, 23 十一月 2023 20:39:52 +0800
Subject: [PATCH] update
---
funasr/bin/asr_inference_launch.py | 307 ++++----------------------------------------------
1 files changed, 29 insertions(+), 278 deletions(-)
diff --git a/funasr/bin/asr_inference_launch.py b/funasr/bin/asr_inference_launch.py
index 61113e9..e1a32c5 100644
--- a/funasr/bin/asr_inference_launch.py
+++ b/funasr/bin/asr_inference_launch.py
@@ -462,18 +462,18 @@
def inference_paraformer_vad_punc(
- maxlenratio: float,
- minlenratio: float,
- batch_size: int,
- beam_size: int,
- ngpu: int,
- ctc_weight: float,
- lm_weight: float,
- penalty: float,
- log_level: Union[int, str],
+ maxlenratio: float=0.0,
+ minlenratio: float=0.0,
+ batch_size: int=1,
+ beam_size: int=1,
+ ngpu: int=1,
+ ctc_weight: float=0.0,
+ lm_weight: float=0.0,
+ penalty: float=0.0,
+ log_level: Union[int, str]=logging.ERROR,
# data_path_and_name_and_type,
- asr_train_config: Optional[str],
- asr_model_file: Optional[str],
+ asr_train_config: Optional[str]=None,
+ asr_model_file: Optional[str]=None,
cmvn_file: Optional[str] = None,
lm_train_config: Optional[str] = None,
lm_file: Optional[str] = None,
@@ -487,7 +487,7 @@
seed: int = 0,
ngram_weight: float = 0.9,
nbest: int = 1,
- num_workers: int = 1,
+ num_workers: int = 0,
vad_infer_config: Optional[str] = None,
vad_model_file: Optional[str] = None,
vad_cmvn_file: Optional[str] = None,
@@ -675,11 +675,13 @@
beg_idx = end_idx
batch = {"speech": speech_j, "speech_lengths": speech_lengths_j}
batch = to_device(batch, device=device)
- # print("batch: ", speech_j.shape[0])
+
beg_asr = time.time()
results = speech2text(**batch)
end_asr = time.time()
- # print("time cost asr: ", end_asr - beg_asr)
+ if speech2text.device != "cpu":
+ print("batch: ", speech_j.shape[0])
+ print("time cost asr: ", end_asr - beg_asr)
if len(results) < 1:
results = [["", [], [], [], [], [], []]]
@@ -815,8 +817,7 @@
format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s",
)
- if sv_model_file is None:
- sv_model_file = "{}/damo/speech_paraformer-large-vad-punc-spk_asr_nat-zh-cn/campplus_cn_common.bin".format(get_cache_dir(None))
+ sv_model_file = asr_model_file.replace("model.pb", "campplus_cn_common.bin")
if param_dict is not None:
hotword_list_or_file = param_dict.get('hotword')
@@ -1099,18 +1100,18 @@
def inference_paraformer_online(
- maxlenratio: float,
- minlenratio: float,
- batch_size: int,
- beam_size: int,
- ngpu: int,
- ctc_weight: float,
- lm_weight: float,
- penalty: float,
- log_level: Union[int, str],
+ maxlenratio: float=0.0,
+ minlenratio: float=0.0,
+ batch_size: int=1,
+ beam_size: int=1,
+ ngpu: int=1,
+ ctc_weight: float=0.0,
+ lm_weight: float=0.0,
+ penalty: float=0.0,
+ log_level: Union[int, str]=logging.ERROR,
# data_path_and_name_and_type,
- asr_train_config: Optional[str],
- asr_model_file: Optional[str],
+ asr_train_config: Optional[str]=None,
+ asr_model_file: Optional[str]=None,
cmvn_file: Optional[str] = None,
lm_train_config: Optional[str] = None,
lm_file: Optional[str] = None,
@@ -2219,259 +2220,9 @@
logging.info("Unknown decoding mode: {}".format(mode))
return None
-
-def get_parser():
- parser = config_argparse.ArgumentParser(
- description="ASR Decoding",
- formatter_class=argparse.ArgumentDefaultsHelpFormatter,
- )
-
- # Note(kamo): Use '_' instead of '-' as separator.
- # '-' is confusing if written in yaml.
- parser.add_argument(
- "--log_level",
- type=lambda x: x.upper(),
- default="INFO",
- choices=("CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG", "NOTSET"),
- help="The verbose level of logging",
- )
-
- parser.add_argument("--output_dir", type=str, required=True)
- parser.add_argument(
- "--ngpu",
- type=int,
- default=0,
- help="The number of gpus. 0 indicates CPU mode",
- )
- parser.add_argument(
- "--njob",
- type=int,
- default=1,
- help="The number of jobs for each gpu",
- )
- parser.add_argument(
- "--gpuid_list",
- type=str,
- default="",
- help="The visible gpus",
- )
- parser.add_argument("--seed", type=int, default=0, help="Random seed")
- parser.add_argument(
- "--dtype",
- default="float32",
- choices=["float16", "float32", "float64"],
- help="Data type",
- )
- parser.add_argument(
- "--num_workers",
- type=int,
- default=1,
- help="The number of workers used for DataLoader",
- )
-
- group = parser.add_argument_group("Input data related")
- group.add_argument(
- "--data_path_and_name_and_type",
- type=str2triple_str,
- required=True,
- action="append",
- )
- group.add_argument("--key_file", type=str_or_none)
- parser.add_argument(
- "--hotword",
- type=str_or_none,
- default=None,
- help="hotword file path or hotwords seperated by space"
- )
- group.add_argument("--allow_variable_data_keys", type=str2bool, default=False)
- group.add_argument(
- "--mc",
- type=bool,
- default=False,
- help="MultiChannel input",
- )
-
- group = parser.add_argument_group("The model configuration related")
- group.add_argument(
- "--vad_infer_config",
- type=str,
- help="VAD infer configuration",
- )
- group.add_argument(
- "--vad_model_file",
- type=str,
- help="VAD model parameter file",
- )
- group.add_argument(
- "--punc_infer_config",
- type=str,
- help="PUNC infer configuration",
- )
- group.add_argument(
- "--punc_model_file",
- type=str,
- help="PUNC model parameter file",
- )
- group.add_argument(
- "--cmvn_file",
- type=str,
- help="Global CMVN file",
- )
- group.add_argument(
- "--asr_train_config",
- type=str,
- help="ASR training configuration",
- )
- group.add_argument(
- "--asr_model_file",
- type=str,
- help="ASR model parameter file",
- )
- group.add_argument(
- "--sv_model_file",
- type=str,
- help="SV model parameter file",
- )
- group.add_argument(
- "--lm_train_config",
- type=str,
- help="LM training configuration",
- )
- group.add_argument(
- "--lm_file",
- type=str,
- help="LM parameter file",
- )
- group.add_argument(
- "--word_lm_train_config",
- type=str,
- help="Word LM training configuration",
- )
- group.add_argument(
- "--word_lm_file",
- type=str,
- help="Word LM parameter file",
- )
- group.add_argument(
- "--ngram_file",
- type=str,
- help="N-gram parameter file",
- )
- group.add_argument(
- "--model_tag",
- type=str,
- help="Pretrained model tag. If specify this option, *_train_config and "
- "*_file will be overwritten",
- )
- group.add_argument(
- "--beam_search_config",
- default={},
- help="The keyword arguments for transducer beam search.",
- )
-
- group = parser.add_argument_group("Beam-search related")
- group.add_argument(
- "--batch_size",
- type=int,
- default=1,
- help="The batch size for inference",
- )
- group.add_argument("--nbest", type=int, default=5, help="Output N-best hypotheses")
- group.add_argument("--beam_size", type=int, default=20, help="Beam size")
- group.add_argument("--penalty", type=float, default=0.0, help="Insertion penalty")
- group.add_argument(
- "--maxlenratio",
- type=float,
- default=0.0,
- help="Input length ratio to obtain max output length. "
- "If maxlenratio=0.0 (default), it uses a end-detect "
- "function "
- "to automatically find maximum hypothesis lengths."
- "If maxlenratio<0.0, its absolute value is interpreted"
- "as a constant max output length",
- )
- group.add_argument(
- "--minlenratio",
- type=float,
- default=0.0,
- help="Input length ratio to obtain min output length",
- )
- group.add_argument(
- "--ctc_weight",
- type=float,
- default=0.0,
- help="CTC weight in joint decoding",
- )
- group.add_argument("--lm_weight", type=float, default=1.0, help="RNNLM weight")
- group.add_argument("--ngram_weight", type=float, default=0.9, help="ngram weight")
- group.add_argument("--streaming", type=str2bool, default=False)
- group.add_argument("--fake_streaming", type=str2bool, default=False)
- group.add_argument("--full_utt", type=str2bool, default=False)
- group.add_argument("--chunk_size", type=int, default=16)
- group.add_argument("--left_context", type=int, default=16)
- group.add_argument("--right_context", type=int, default=0)
- group.add_argument(
- "--display_partial_hypotheses",
- type=bool,
- default=False,
- help="Whether to display partial hypotheses during chunk-by-chunk inference.",
- )
-
- group = parser.add_argument_group("Dynamic quantization related")
- group.add_argument(
- "--quantize_asr_model",
- type=bool,
- default=False,
- help="Apply dynamic quantization to ASR model.",
- )
- group.add_argument(
- "--quantize_modules",
- nargs="*",
- default=None,
- help="""Module names to apply dynamic quantization on.
- The module names are provided as a list, where each name is separated
- by a comma (e.g.: --quantize-config=[Linear,LSTM,GRU]).
- Each specified name should be an attribute of 'torch.nn', e.g.:
- torch.nn.Linear, torch.nn.LSTM, torch.nn.GRU, ...""",
- )
- group.add_argument(
- "--quantize_dtype",
- type=str,
- default="qint8",
- choices=["float16", "qint8"],
- help="Dtype for dynamic quantization.",
- )
-
- group = parser.add_argument_group("Text converter related")
- group.add_argument(
- "--token_type",
- type=str_or_none,
- default=None,
- choices=["char", "bpe", None],
- help="The token type for ASR model. "
- "If not given, refers from the training args",
- )
- group.add_argument(
- "--bpemodel",
- type=str_or_none,
- default=None,
- help="The model path of sentencepiece. "
- "If not given, refers from the training args",
- )
- group.add_argument("--token_num_relax", type=int, default=1, help="")
- group.add_argument("--decoding_ind", type=int, default=0, help="")
- group.add_argument("--decoding_mode", type=str, default="model1", help="")
- group.add_argument(
- "--ctc_weight2",
- type=float,
- default=0.0,
- help="CTC weight in joint decoding",
- )
- return parser
-
-
def main(cmd=None):
print(get_commandline_args(), file=sys.stderr)
+ from funasr.bin.argument import get_parser
parser = get_parser()
parser.add_argument(
"--mode",
--
Gitblit v1.9.1