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ParameterList
class torch.nn.ParameterList(values=None)
[source]-
Holds parameters in a list.
ParameterList
can be used like a regular Python list, but Tensors that areParameter
are properly registered, and will be visible by allModule
methods.Note that the constructor, assigning an element of the list, the
append()
method and theextend()
method will convert anyTensor
intoParameter
.- Parameters
-
parameters (iterable, optional) – an iterable of elements to add to the list.
Example:
class MyModule(nn.Module): def __init__(self): 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)
[source]-
Appends a given value at the end of the list.
- Parameters
-
value (Any) – value to append
- Return type
extend(values)
[source]-
Appends values from a Python iterable to the end of the list.
- Parameters
-
values (iterable) – iterable of values to append
- Return type
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https://pytorch.org/docs/2.1/generated/torch.nn.ParameterList.html