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mean_absolute_error

allennlp.training.metrics.mean_absolute_error

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MeanAbsoluteError#

@Metric.register("mean_absolute_error")
class MeanAbsoluteError(Metric):
 | def __init__(self) -> None

This Metric calculates the mean absolute error (MAE) between two tensors.

__call__#

class MeanAbsoluteError(Metric):
 | ...
 | def __call__(
 |     self,
 |     predictions: torch.Tensor,
 |     gold_labels: torch.Tensor,
 |     mask: Optional[torch.BoolTensor] = None
 | )

Parameters

  • predictions : torch.Tensor
    A tensor of predictions of shape (batch_size, ...).
  • gold_labels : torch.Tensor
    A tensor of the same shape as predictions.
  • mask : torch.BoolTensor, optional (default = None)
    A tensor of the same shape as predictions.

get_metric#

class MeanAbsoluteError(Metric):
 | ...
 | def get_metric(self, reset: bool = False)

Returns

  • The accumulated mean absolute error.

reset#

class MeanAbsoluteError(Metric):
 | ...
 | @overrides
 | def reset(self)