mighty.monitor.accuracy.AccuracyArgmax¶
- class mighty.monitor.accuracy.AccuracyArgmax[source]¶
Softmax accuracy.
The predicted labels are simply
output.argmax(dim=-1)
.Methods
__init__
()extra_repr
()partial_fit
(outputs_batch, labels_batch)If the accuracy measure is not argmax (if the model's last layer isn't a softmax), the output is an embedding vector, which has to be stored and retrieved at prediction.
predict
(outputs_test)Predict the labels, given model output.
predict_proba
(outputs_test)Compute label probabilities, given model output.
reset
()Resets all cached predicted and ground truth data.
Resets predicted and ground truth labels.
- partial_fit(outputs_batch, labels_batch)[source]¶
If the accuracy measure is not argmax (if the model’s last layer isn’t a softmax), the output is an embedding vector, which has to be stored and retrieved at prediction.
- Parameters:
- outputs_batchtorch.Tensor or tuple
The output of a model.
- labels_batchtorch.Tensor
True labels.
- predict(outputs_test)[source]¶
Predict the labels, given model output.
- Parameters:
- outputs_testtorch.Tensor or tuple
The output of a model.
- Returns:
- torch.Tensor
Predicted labels.
- predict_proba(outputs_test)[source]¶
Compute label probabilities, given model output.
- Parameters:
- outputs_testtorch.Tensor or tuple
The output of a model.
- Returns:
- torch.Tensor
The probabilities of assigning to each class of shape (., C), where C is the number of classes.
- reset()¶
Resets all cached predicted and ground truth data.
- reset_labels()¶
Resets predicted and ground truth labels.