MeanSquaredLogError

class torch_uncertainty.metrics.regression.MeanSquaredLogError(squared=True, **kwargs)

MeanSquaredLogError (MSELog) regression metric.

\[\text{MSELog} = \frac{1}{N}\sum_i^N (\log \hat{y_i} - \log y_i)^2\]

where \(y\) is a tensor of target values, and \(\hat{y}\) is a

tensor of predictions.

As input to forward and update the metric accepts the following

input:

• preds (Tensor): Predictions from model

• target (Tensor): Ground truth values

As output of forward and compute the metric returns the

following output:

• mse_log (Tensor): A tensor with the

  relative mean absolute error over the state

Parameters:

• squared – If True returns MSELog value, if False returns EMSELog value.

• kwargs – Additional keyword arguments, see Advanced metric settings.

Reference:

As in e.g. From big to small: Multi-scale local planar guidance for

monocular depth estimation

update(pred, target)

Update state with predictions and targets.