add

dataloaders/beat_sep_lower_single.py

@@ -65,7 +65,7 @@ class CustomDataset(Dataset):
             num_expression_coeffs=100, 
             ext='npz',
             use_pca=False,
-        ).cuda().eval()
+        ).eval()
 
         split_rule = pd.read_csv(args.data_path+"train_test_split.csv")
         self.selected_file = split_rule.loc[(split_rule['type'] == loader_type) & (split_rule['id'].str.split("_").str[0].astype(int).isin(self.args.training_speakers))]
@@ -265,10 +265,10 @@ class CustomDataset(Dataset):
             n, c = poses.shape[0], poses.shape[1]
             betas = betas.reshape(1, 300)
             betas = np.tile(betas, (n, 1))
-            betas = torch.from_numpy(betas).cuda().float()
-            poses = torch.from_numpy(poses.reshape(n, c)).cuda().float()
-            exps = torch.from_numpy(exps.reshape(n, 100)).cuda().float()
-            trans = torch.from_numpy(trans.reshape(n, 3)).cuda().float()
+            betas = torch.from_numpy(betas).float()
+            poses = torch.from_numpy(poses.reshape(n, c)).float()
+            exps = torch.from_numpy(exps.reshape(n, 100)).float()
+            trans = torch.from_numpy(trans.reshape(n, 3)).float()
             max_length = 128    # 为什么这里需要一个max_length
             s, r = n//max_length, n%max_length
             #print(n, s, r)