sync ms

model.py

@@ -2,7 +2,8 @@ import torch
 import torch.nn as nn
 import torchvision.models as models
 from modelscope.msdatasets import MsDataset
-from utils import MODEL_DIR
+from datasets import load_dataset
+from utils import MODEL_DIR, EN_US
 
 
 class EvalNet:
@@ -17,7 +18,7 @@ class EvalNet:
         self.m_type, self.input_size = self._model_info(m_ver)
 
         if not hasattr(models, m_ver):
-            raise Exception("不支持的模型")
+            raise ValueError("不支持的模型")
 
         self.model = eval("models.%s()" % m_ver)
         linear_output = self._set_outsize()
@@ -38,9 +39,10 @@ class EvalNet:
         return backbone_list[0]
 
     def _model_info(self, m_ver: str):
-        backbone_list = MsDataset.load(
-            "monetjoe/cv_backbones",
-            split="v1",
+        backbone_list = (
+            load_dataset("monetjoe/cv_backbones", split="train")
+            if EN_US
+            else MsDataset.load("monetjoe/cv_backbones", split="v1")
         )
         backbone = self._get_backbone(m_ver, backbone_list)
         m_type = str(backbone["type"])

requirements.txt

@@ -4,4 +4,4 @@ torchvision==0.21.0+cu118
 -f https://download.pytorch.org/whl/torchvision
 librosa
 matplotlib
-modelscope[framework]==1.24.0
+modelscope[framework]==1.21.0