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def forward(self, dgz, d_hid): r"""Computes the loss for the given input. Args: dgz (torch.Tensor) : Output of the Discriminator with generated data. It must have the dimensions (N, \*) where \* means any number of additional dimensions. d_hid (torch.Tensor): The embeddings generated by the discriminator. Returns: scalar. """ return self.pt_ratio * energy_based_pulling_away_term(d_hid)