Error when loading weights for large model

[Vladislav Artemyev]

Code:

net_large.load_state_dict(torch.load('pretrained/mobilenetv3-large-657e7b3d.pth'))

Error:

RuntimeError: Error(s) in loading state_dict for MobileNetV3:
	Missing key(s) in state_dict: "classifier.0.weight", "classifier.0.bias", "classifier.3.weight", "classifier.3.bias". 
	Unexpected key(s) in state_dict: "classifier.1.weight", "classifier.1.bias", "classifier.5.weight", "classifier.5.bias". 

[Duo Li]

just change keys in the checkpoint to expected

[feiyun1265]

Code:

net_large.load_state_dict(torch.load('pretrained/mobilenetv3-large-657e7b3d.pth'))

Error:

RuntimeError: Error(s) in loading state_dict for MobileNetV3:
	Missing key(s) in state_dict: "classifier.0.weight", "classifier.0.bias", "classifier.3.weight", "classifier.3.bias". 
	Unexpected key(s) in state_dict: "classifier.1.weight", "classifier.1.bias", "classifier.5.weight", "classifier.5.bias". 

---

state_dict = torch.load("mobilenetv3-large-657e7b3d.pth")
new_state_dict = OrderedDict()
for k, v in state_dict.items():
if k=="classifier.1.weight":
k = "classifier.0.weight"
if k=="classifier.1.bias":
k = "classifier.0.bias"
if k=="classifier.5.weight":
k = "classifier.3.weight"
if k=="classifier.5.bias":
k = "classifier.3.bias"
new_state_dict[k] = v

model.load_state_dict(new_state_dict)

[E1eMenta]

If you need only conv part, you can use
net_large.load_state_dict(torch.load('pretrained/mobilenetv3-large-657e7b3d.pth'), strict=False)