ParameterList¶
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class torch.nn.ParameterList(parameters=None)[source]¶
- Holds parameters in a list. - ParameterListcan be indexed like a regular Python list, but parameters it contains are properly registered, and will be visible by all- Modulemethods.- Parameters
- parameters (iterable, optional) – an iterable of - Parameterto 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