The branch of computer science dealing with the reproduction, or mimicking of human-level intelligence, self-awareness, knowledge, conscience, and thought in computer programs.
Currently, when entering epic mode the README is frozen in the last level of the tower. When you're trying to fine-tune the score for a level other than the last one, it would be helpful if we had the README for that level available. The proposal is that when entering epic mode, the README is updated with all levels, one following the other.
Example:
# Starbolt - beginner
Create the metric MulticlassAUROC to allow for the AUROC metric to be used in multi-class problem settings. Or,
Expand the AUROC metric to support multi-class data, which would also directly solve this AUROC bug that instead gives a random value when used in multi-class problems: https://github.com/PyTorchLightning/
At this moment relu_layer op doesn't allow threshold configuration, and legacy RELU op allows that.
We should add configuration option to relu_layer.