ParameterList
class torch.nn.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):
          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
