1. Both nn.ModuleList and nn.Sequential are containers that contains pytorch nn modules. nn.ModuleList just stores a list nn.Modules and it does not have a forward() method.
When you ask for model.parameters(), the parameters of layers inside nn.ModuleList will be returned. But if it is regular list, we dont look inside the list for nn.Module layers. In your example, if you do
nn.ModuleList is just like a Python list. It was designed to store any desired number of nn.Module’s. It may be useful, for instance, if you want to design a neural network whose number of layers is passed...
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Holds submodules in a list. ModuleList can be indexed like a regular Python list, but modules it contains are properly registered, and will be visible by all Module methods. Parameters
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In this section, we will learn about how to create the PyTorch nn.linear module list in python. PyTorch nn.linear module list is defined as a list that can be indexed like a systematic Python list...