From 28a19dbc4e85d3b8a4ec2ef7483bba64d422b43f Mon Sep 17 00:00:00 2001
From: aky15 <ankeyu.aky@11.17.44.249>
Date: 星期三, 12 四月 2023 18:03:06 +0800
Subject: [PATCH] Merge remote-tracking branch 'origin/main' into dev_aky
---
funasr/bin/asr_inference_launch.py | 128 +++++++++++++++++++++++++++++++++++++++---
1 files changed, 117 insertions(+), 11 deletions(-)
diff --git a/funasr/bin/asr_inference_launch.py b/funasr/bin/asr_inference_launch.py
old mode 100755
new mode 100644
index 84e1422..53eee64
--- a/funasr/bin/asr_inference_launch.py
+++ b/funasr/bin/asr_inference_launch.py
@@ -76,6 +76,21 @@
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(
+ "--cmvn_file",
+ type=str,
+ help="Global CMVN file",
+ )
+ group.add_argument(
"--asr_train_config",
type=str,
help="ASR training configuration",
@@ -116,6 +131,11 @@
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(
@@ -147,12 +167,47 @@
group.add_argument(
"--ctc_weight",
type=float,
- default=0.5,
+ 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("--simu_streaming", 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(
@@ -182,17 +237,56 @@
return parser
-def set_parameters(language: str = None,
- sample_rate: Union[int, Dict[Any, int]] = None):
- if language is not None:
- global global_asr_language
- global_asr_language = language
- if sample_rate is not None:
- global global_sample_rate
- global_sample_rate = sample_rate
+def inference_launch(**kwargs):
+ if 'mode' in kwargs:
+ mode = kwargs['mode']
+ else:
+ logging.info("Unknown decoding mode.")
+ return None
+ if mode == "asr":
+ from funasr.bin.asr_inference import inference_modelscope
+ return inference_modelscope(**kwargs)
+ elif mode == "uniasr":
+ from funasr.bin.asr_inference_uniasr import inference_modelscope
+ return inference_modelscope(**kwargs)
+ elif mode == "uniasr_vad":
+ from funasr.bin.asr_inference_uniasr_vad import inference_modelscope
+ return inference_modelscope(**kwargs)
+ elif mode == "paraformer":
+ from funasr.bin.asr_inference_paraformer import inference_modelscope
+ return inference_modelscope(**kwargs)
+ elif mode == "paraformer_streaming":
+ from funasr.bin.asr_inference_paraformer_streaming import inference_modelscope
+ return inference_modelscope(**kwargs)
+ elif mode == "paraformer_vad":
+ from funasr.bin.asr_inference_paraformer_vad import inference_modelscope
+ return inference_modelscope(**kwargs)
+ elif mode == "paraformer_punc":
+ logging.info("Unknown decoding mode: {}".format(mode))
+ return None
+ elif mode == "paraformer_vad_punc":
+ from funasr.bin.asr_inference_paraformer_vad_punc import inference_modelscope
+ return inference_modelscope(**kwargs)
+ elif mode == "vad":
+ from funasr.bin.vad_inference import inference_modelscope
+ return inference_modelscope(**kwargs)
+ elif mode == "mfcca":
+ from funasr.bin.asr_inference_mfcca import inference_modelscope
+ return inference_modelscope(**kwargs)
+ elif mode == "rnnt":
+ from funasr.bin.asr_inference_rnnt import inference_modelscope
+ return inference_modelscope(**kwargs)
+ else:
+ logging.info("Unknown decoding mode: {}".format(mode))
+ return None
-def inference_launch(mode, **kwargs):
+def inference_launch_funasr(**kwargs):
+ if 'mode' in kwargs:
+ mode = kwargs['mode']
+ else:
+ logging.info("Unknown decoding mode.")
+ return None
if mode == "asr":
from funasr.bin.asr_inference import inference
return inference(**kwargs)
@@ -201,6 +295,18 @@
return inference(**kwargs)
elif mode == "paraformer":
from funasr.bin.asr_inference_paraformer import inference
+ return inference(**kwargs)
+ elif mode == "paraformer_vad_punc":
+ from funasr.bin.asr_inference_paraformer_vad_punc import inference
+ return inference(**kwargs)
+ elif mode == "vad":
+ from funasr.bin.vad_inference import inference
+ return inference(**kwargs)
+ elif mode == "mfcca":
+ from funasr.bin.asr_inference_mfcca import inference_modelscope
+ return inference_modelscope(**kwargs)
+ elif mode == "rnnt":
+ from funasr.bin.asr_inference_rnnt import inference
return inference(**kwargs)
else:
logging.info("Unknown decoding mode: {}".format(mode))
@@ -234,7 +340,7 @@
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = gpuid
- inference_launch(**kwargs)
+ inference_launch_funasr(**kwargs)
if __name__ == "__main__":
--
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