models/spatial/attncnf.py [240:250]:
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        if not self.initialized:
            with torch.no_grad():
                # compute batch statistics
                x_ = x.reshape(-1, x.shape[-1])
                batch_mean = torch.mean(x_, dim=0)
                batch_var = torch.var(x_, dim=0)

                # for numerical issues
                batch_var = torch.max(batch_var, torch.tensor(0.2).to(batch_var))

                self.bias.data.copy_(-batch_mean)
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models/temporal/neural.py [399:409]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        if not self.initialized:
            with torch.no_grad():
                # compute batch statistics
                x_ = x.reshape(-1, x.shape[-1])
                batch_mean = torch.mean(x_, dim=0)
                batch_var = torch.var(x_, dim=0)

                # for numerical issues
                batch_var = torch.max(batch_var, torch.tensor(0.2).to(batch_var))

                self.bias.data.copy_(-batch_mean)
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