mindspore.nn.Metric
- class mindspore.nn.Metric[source]
Base class of metric.
Note
For examples of subclasses, please refer to the definition of class MAE, Recall etc.
- abstract clear()[source]
An interface describes the behavior of clearing the internal evaluation result.
Note
All subclasses must override this interface.
- abstract eval()[source]
An interface describes the behavior of computing the evaluation result.
Note
All subclasses must override this interface.
- property indexes
The _indexes is a private attributes, and you can retrieve it by self.indexes.
- set_indexes(indexes)[source]
The _indexes is a private attributes, and you can modify it by this function. This allows you to determine the order of logits and labels to be calculated in the inputs, specially when you call the method update within this metrics.
Note
It has been applied in subclass of Metric, eg. Accuracy, BleuScore, ConfusionMatrix, CosineSimilarity, MAE, and MSE.
- Parameters
indexes (List(int)) – The order of logits and labels to be rearranged.
- Outputs:
Metric, its original Class instance.
Examples
>>> import numpy as np >>> from mindspore import nn, Tensor >>> >>> x = Tensor(np.array([[0.2, 0.5], [0.3, 0.1], [0.9, 0.6]])) >>> y = Tensor(np.array([1, 0, 1])) >>> y2 = Tensor(np.array([0, 0, 1])) >>> metric = nn.Accuracy('classification').set_indexes([0, 2]) >>> metric.clear() >>> metric.update(x, y, y2) >>> accuracy = metric.eval() >>> print(accuracy) 0.3333333333333333