mean_absolute_error

allennlp.training.metrics.mean_absolute_error

[SOURCE]

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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
 | ) -> 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) -> Dict[str, float]

Returns

• The accumulated mean absolute error.
  

reset

class MeanAbsoluteError(Metric):
 | ...
 | def reset(self) -> None