ParameterList¶

class torch.nn.ParameterList(parameters: Optional[Iterable[Parameter]] = None)[source]¶

Holds parameters in a list.

ParameterList can be indexed like a regular Python list, but parameters it contains are properly registered, and will be visible by all Module methods.

Parameters

parameters (iterable, optional) – an iterable of Parameter to add

Example:

class MyModule(nn.Module):
    def __init__(self):
        super(MyModule, self).__init__()
        self.params = nn.ParameterList([nn.Parameter(torch.randn(10, 10)) for i in range(10)])

    def forward(self, x):
        # ParameterList can act as an iterable, or be indexed using ints
        for i, p in enumerate(self.params):
            x = self.params[i // 2].mm(x) + p.mm(x)
        return x

append(parameter: Parameter) → T[source]¶

Appends a given parameter at the end of the list.

Parameters

parameter (nn.Parameter) – parameter to append

extend(parameters: Iterable[Parameter]) → T[source]¶

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

Parameters

parameters (iterable) – iterable of parameters to append