


linear = nn.Linear(2, 2, bias=None).to(torch.cdouble)
         >>> linear.weight
         Parameter containing:
         tensor([[ 0.3741+0.j,  0.2382+0.j],
                 [ 0.5593+0.j, -0.4443+0.j]], dtype=torch.complex128)
         >>> linear(torch.ones(3, 2, dtype=torch.cdouble))
         tensor([[0.6122+0.j, 0.1150+0.j],
                 [0.6122+0.j, 0.1150+0.j],
                 [0.6122+0.j, 0.1150+0.j]], dtype=torch.complex128)



to_empty(*, device)
  Moves the parameters and buffers to the specified device without
  copying storage.

  Parameters:
     **device** ("torch.device") -- The desired device of the
     parameters and buffers in this module.

  Returns:
     self

  Return type:
     Module

train(mode=True)
  Sets the module in training mode.

  This has any effect only on certain modules. See documentations
  of particular modules for details of their behaviors in
