- class torch.nn.ModuleList(modules=None)[source]¶
Holds submodules in a list.
ModuleList can be indexed like a regular Python list, butmodules it contains are properly registered, and will be visible by all
Modulemethods.- Parameters
modules (iterable, optional) – an iterable of modules to add
Example:
class MyModule(nn.Module): def __init__(self): super().__init__() self.linears = nn.ModuleList([nn.Linear(10, 10) for i in range(10)]) def forward(self, x): # ModuleList can act as an iterable, or be indexed using ints for i, l in enumerate(self.linears): x = self.linears[i // 2](x) + l(x) return x
- append(module)[source]¶
Append a given module to the end of the list.
- Parameters
module (nn.Module) – module to append
- Return type
ModuleList
- extend(modules)[source]¶
Append modules from a Python iterable to the end of the list.
- Parameters
modules (iterable) – iterable of modules to append
- Return type
Self
