How to return parameters and names of finetuned model

vision
1

Hi, I am trying to return the names of the parameters of a finetuned pretrained resnet18 model and I get an empty list. Basically what i want to do is for

                               model = resnet18(pretrained=True)
                               params = []
                               params += [n for n, p in model.named_parameters() if 'layer' in n]
                               print(params)

I get the parameter names printed out as [‘layer1.0.conv1.weight’, layer1.0.bn1.weight’…]
but after finetuning and saving my model and loading, I get an empty list when i try to return a similar list as above.
model = torch.load(‘finetuned_resnet’)
params = []
params += [n for n, p in model.named_parameters() if ‘layer’ in n]
print(params)
Can anyone help explain why this is so?
Thanks

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2

I think I found my problem. Given that i redefined my model as:

class ModifiedResNet18Model(torch.nn.Module):
def init(self):
super(ModifiedResNet18Model, self).init()

model = models.resnet18(pretrained=True)#squeezenet1_1
modules = list(model.children())[:-1]      # delete the last fc layer.
        model = nn.Sequential(*modules)
self.features = model
print("start pruning:")
for param in self.features.parameters():
	param.requires_grad = False

self.fc = nn.Sequential(
	nn.Dropout(),
	nn.Linear(512,400),
	nn.ReLU(inplace=True),
                nn.Dropout(),
	nn.Linear(400,256),
	nn.ReLU(inplace=True),
	nn.Linear(256, 256))

def forward(self, x):
x = self.features(x)
x = x.view(x.size(0), -1)
x = self.fc(x)#self.classifier(x)
return x

I needed to add features when i return it as:

model = torch.load(‘finetuned_resnet’)
params = []
params += [n for n, p in model.features.named_parameters() if ‘layer’ in n]
print(params)

Thanks

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