From 6086ff54e3d93dd2e465e152e7214dce7695371d Mon Sep 17 00:00:00 2001
From: Chong Zhang <iriszhangchong@gmail.com>
Date: 星期四, 29 六月 2023 16:32:14 +0800
Subject: [PATCH] update speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch (#688)
---
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/infer.py | 33 ----------------
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/finetune.py | 38 +------------------
2 files changed, 3 insertions(+), 68 deletions(-)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/finetune.py
index 0393212..79fd34d 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/finetune.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/finetune.py
@@ -1,5 +1,4 @@
import os
-<<<<<<< HEAD
from modelscope.metainfo import Trainers
from modelscope.trainers import build_trainer
@@ -21,50 +20,17 @@
batch_bins=params.batch_bins,
max_epoch=params.max_epoch,
lr=params.lr)
-=======
-from modelscope.metainfo import Trainers
-from modelscope.trainers import build_trainer
-from funasr.datasets.ms_dataset import MsDataset
-
-
-def modelscope_finetune(params):
- if not os.path.exists(params["output_dir"]):
- os.makedirs(params["output_dir"], exist_ok=True)
- # dataset split ["train", "validation"]
- ds_dict = MsDataset.load(params["data_dir"])
- kwargs = dict(
- model=params["model"],
- model_revision=params["model_revision"],
- data_dir=ds_dict,
- dataset_type=params["dataset_type"],
- work_dir=params["output_dir"],
- batch_bins=params["batch_bins"],
- max_epoch=params["max_epoch"],
- lr=params["lr"])
->>>>>>> main
trainer = build_trainer(Trainers.speech_asr_trainer, default_args=kwargs)
trainer.train()
if __name__ == '__main__':
-<<<<<<< HEAD
params = modelscope_args(model="damo/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch", data_path="./data")
params.output_dir = "./checkpoint" # m妯″瀷淇濆瓨璺緞
params.data_path = "./example_data/" # 鏁版嵁璺緞
params.dataset_type = "small" # 灏忔暟鎹噺璁剧疆small锛岃嫢鏁版嵁閲忓ぇ浜�1000灏忔椂锛岃浣跨敤large
params.batch_bins = 2000 # batch size锛屽鏋渄ataset_type="small"锛宐atch_bins鍗曚綅涓篺bank鐗瑰緛甯ф暟锛屽鏋渄ataset_type="large"锛宐atch_bins鍗曚綅涓烘绉掞紝
- params.max_epoch = 50 # 鏈�澶ц缁冭疆鏁�
+ params.max_epoch = 20 # 鏈�澶ц缁冭疆鏁�
params.lr = 0.00005 # 璁剧疆瀛︿範鐜�
-=======
- params = {}
- params["output_dir"] = "./checkpoint"
- params["data_dir"] = "./data"
- params["batch_bins"] = 2000
- params["dataset_type"] = "small"
- params["max_epoch"] = 50
- params["lr"] = 0.00005
- params["model"] = "damo/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch"
- params["model_revision"] = None
->>>>>>> main
- modelscope_finetune(params)
+ modelscope_finetune(params)
\ No newline at end of file
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/infer.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/infer.py
index a0f0965..da8859e 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/infer.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/infer.py
@@ -1,33 +1,3 @@
-<<<<<<< HEAD
-import os
-import shutil
-import argparse
-from modelscope.pipelines import pipeline
-from modelscope.utils.constant import Tasks
-
-def modelscope_infer(args):
- os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpuid)
- inference_pipeline = pipeline(
- task=Tasks.auto_speech_recognition,
- model=args.model,
- output_dir=args.output_dir,
- batch_size=args.batch_size,
- param_dict={"decoding_model": args.decoding_mode, "hotword": args.hotword_txt}
- )
- inference_pipeline(audio_in=args.audio_in)
-
-if __name__ == "__main__":
- parser = argparse.ArgumentParser()
- parser.add_argument('--model', type=str, default="damo/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch")
- parser.add_argument('--audio_in', type=str, default="./data/test/wav.scp")
- parser.add_argument('--output_dir', type=str, default="./results/")
- parser.add_argument('--decoding_mode', type=str, default="normal")
- parser.add_argument('--hotword_txt', type=str, default=None)
- parser.add_argument('--batch_size', type=int, default=64)
- parser.add_argument('--gpuid', type=str, default="0")
- args = parser.parse_args()
- modelscope_infer(args)
-=======
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
@@ -40,5 +10,4 @@
output_dir=output_dir,
)
rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
- print(rec_result)
->>>>>>> main
+ print(rec_result)
\ No newline at end of file
--
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