LambdaLR], optional) - A tuple containing the optimizer and the scheduler to use. What if the optimizer uses the names of the parameters when the. parameters()), lr=1e-3) no such thing as dumx or not about it, do any can be perfx, no right wrong □ 1 astariul reacted with confused emoji □ 1 OzoneReloaded reacted with eyes emoji All reactions Now, check the parameter list associated with this model - for param in net. Singleton class representing a required parameter for an Optimizer. The parameter can be accessed as an attribute using given name. named_parameters(): # freeze resnet if 'image_model' in. parameters ()) Could I put model1, model2 in a nn. I can of course inherit all the layers I'm interested in and add this mask and override the forward method but I was thinking if I could dynamically remove the weight parameter in the modules and monkey-patch them with something like below: class CustomWeight (nn.
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