ParameterList

class torch.nn.modules.container.ParameterList(values=None)

Holds parameters in a list.

ParameterList can be used like a regular Python list, but Tensors that are Parameter are properly registered, and will be visible by all Module methods.

Note that the constructor, assigning an element of the list, the append() method and the extend() method will convert any Tensor into Parameter.

Parameters

parameters (iterable, optional) – an iterable of elements to add to the list.

Example:

class MyModule(nn.Module):
    def __init__(self) -> None:
        super().__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(value)

Append a given value at the end of the list.

Parameters

value (Any) – value to append

Return type

Self

extend(values)

Append values from a Python iterable to the end of the list.

Parameters

values (iterable) – iterable of values to append

Return type

Self

extra_repr()

Return the extra representation of the module.

Return type

str