ModuleList¶

class torch.nn.ModuleList(modules: Optional[Iterable[torch.nn.modules.module.Module]] = None)[source]¶

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

modules (iterable, optional) – an iterable of modules to add

Example:

class MyModule(nn.Module):
    def __init__(self):
        super(MyModule, self).__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: torch.nn.modules.module.Module) → T[source]¶

Appends a given module to the end of the list.

Parameters

module (nn.Module) – module to append

extend(modules: Iterable[torch.nn.modules.module.Module]) → T[source]¶

Appends modules from a Python iterable to the end of the list.

Parameters

modules (iterable) – iterable of modules to append

insert(index: int, module: torch.nn.modules.module.Module) → None[source]¶

Insert a given module before a given index in the list.

Parameters

• index (int) – index to insert.

• module (nn.Module) – module to insert