update

app.py

@@ -45,7 +45,7 @@ model = ResNet_CSRA(num_heads=1, lam=0.1, num_classes=20)
 normalize = transforms.Normalize(mean=[0, 0, 0], std=[1, 1, 1])
 model.to(DEVICE)
 print("Loading weights from {}".format("./models/msl_c_voc.pth"))
-model.load_state_dict(torch.load("./models/msl_c_voc.pth"))
+model.load_state_dict(torch.load("./models/msl_c_voc.pth"), map_location=torch.device('cpu'))
 
 # Inference!
 def inference(img_path):

pipeline/timm_utils/tuple.py

@@ -3,8 +3,8 @@
 Hacked together by / Copyright 2020 Ross Wightman
 """
 from itertools import repeat
-import collections.abc as container_abcs
-#from torch._six import container_abcs
+#import collections.abc as container_abcs
+from torch._six import container_abcs
 
 # From PyTorch internals
 def _ntuple(n):