From cc2c1d1d53dea5d2c45f858d1baa5bd279f47987 Mon Sep 17 00:00:00 2001
From: nichongjia-2007 <nichongjia@gmail.com>
Date: 星期三, 31 五月 2023 14:39:25 +0800
Subject: [PATCH] Merge branch 'main' of https://github.com/alibaba-damo-academy/FunASR

---
 egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/finetune.py |   70 +++++++++++++++++++++++++++++++++++
 1 files changed, 70 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
new file mode 100644
index 0000000..0393212
--- /dev/null
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch/finetune.py
@@ -0,0 +1,70 @@
+import os
+<<<<<<< HEAD
+
+from modelscope.metainfo import Trainers
+from modelscope.trainers import build_trainer
+
+from funasr.datasets.ms_dataset import MsDataset
+from funasr.utils.modelscope_param import modelscope_args
+
+
+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_path)
+    kwargs = dict(
+        model=params.model,
+        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)
+=======
+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.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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