fbc57241b529ce921d664d86685935c4d3219feb,gpytorch/likelihoods/noise_models.py,HomoskedasticNoise,forward,#HomoskedasticNoise#Any#,18

Before Change

        log_noise = self.log_noise
        p = params[0] if isinstance(params, list) else params
        n = p.shape[-2] if len(p.shape) > 1 else p.shape[-1]
        log_noise_diag = log_noise.repeat(n, 1)
        return DiagLazyTensor(log_noise_diag)


class MultitaskHomoskedasticNoise(HomoskedasticNoise):

After Change

        )

    def forward(self, params):
        log_noise = self.log_noise.squeeze(0).exp()
        p = params[0] if isinstance(params, list) else params
        shape = p.shape if len(p.shape) == 1 else p.shape[:-1]
        if log_noise.ndimension() > len(shape):
            raise RuntimeError("Must provide batched input if in batch mode")
        if log_noise.shape[-1] > 1:  // deal with multi-task case
            shape = shape + torch.Size([log_noise.shape[-1]])
        log_noise_diag = log_noise.expand(shape)
        return DiagLazyTensor(log_noise_diag)

Instances