I’m not sure, what’s causing this error, as the notebook seems to show a standard resnet with your specified input shape, which works:
model = models.resnet50(pretrained=False)
num_ftrs = model.fc.in_features
model.fc = nn.Linear(num_ftrs, 10)

x = torch.randn(1, 3, 384, 384)
out = model(x)

Could you rerun the notebook from the beginning and make sure to call all cells in order?
Notebooks are prone to errors caused by a different execution order.