From c2dee5e3c29eba79e591d9e9caebaef15ea4e56b Mon Sep 17 00:00:00 2001
From: hnluo <haoneng.lhn@alibaba-inc.com>
Date: 星期四, 29 六月 2023 11:09:28 +0800
Subject: [PATCH] Merge pull request #687 from alibaba-damo-academy/dev_lhn

---
 egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/finetune.py |   34 ++++++++++++++++++++++++++++++++++
 1 files changed, 34 insertions(+), 0 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 4e31379..0393212 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
@@ -1,4 +1,5 @@
 import os
+<<<<<<< HEAD
 
 from modelscope.metainfo import Trainers
 from modelscope.trainers import build_trainer
@@ -20,11 +21,33 @@
         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
@@ -33,4 +56,15 @@
     params.max_epoch = 50                           # 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)

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