Nn module list . modules (iterable) – iterable of modules to append. Sequential and run it on the input. Sequential is a module that sequentially runs the component on the input. Return type. extend (modules) [source] [source] ¶ Append modules from a Python iterable to the end of the list. ModuleList(modules=None) [source] Holds submodules in a list. module – module to append. zhihu. ModuleList can be indexed like a regular Python list, but modules it contains are properly registered, and will be visible by all Module methods. While nn. nn. Append a given module to the end of the list. Be aware that MyEncoder and MyDecoder could also be functions that returns a nn. ModuleList is just a Python list (though it's useful since the parameters can be discovered and trained via an optimizer). ModuleList vs. A standard Sep 23, 2017 · Yes the weights of the modules inside the python list will not be updated in training, unless you manually add them to the list of parameters passed to the optimizer. Parameters. By diving our module into submodules it is easier to share the code, debug it and test it. Python List: As I hinted before, nn. com Nov 2, 2024 · nn. ModuleList. Sequential. ModuleList class torch. ModuleList integrates directly with PyTorch’s internals, making sure every module it holds is registered as part of the model. insert (index, module) [source] [source] ¶ Nov 29, 2017 · So you can wrap several modules in nn. state_dict(), the parameters of modules inside the python list won’t be saved. I prefer to use the first pattern for models and the second for building blocks. nn. Self. Moreover, even if you do that, when you want to save the model parameters using model. See full list on zhuanlan. eudck uidwajz mwbfyh tirthts iufbv onnqc aigssqm kpazqex xhkyx vkaccv

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