code: def forward(self, t, h):
      # t has shape ()
      # h has shape (batch_size, hidden_size)
      t = t.expand(h.size(0), 1)
      th = torch.cat([t, h], dim=1)
      return self._module(th).view(
          h.size(0), self._hidden_size, 1 + self._data_size
      )
  
imports: import fire
  import matplotlib.pyplot
  import torch
  import torch.optim.swa_utils
  import torchcde
  import torchsde
  import tqdm
label_desc: Use image node_id 2 for calling the DiscriminatorFunc obj's underlying member method code with example usage: obj.forward(t, h) and returns: self