I would do something like:

` from clearml import Logger

def forward(...):
    self.iteration += 1 
    weights = self.compute_weights(...)
    m = (weights * (target-preds)).mean()
    Logger.current_logger().report_scalar(title="debug", series="mean_weight", value=m, iteration=self.iteration)
    return m `

Awesome AgitatedDove14 Thanks a lot 🙌

GrievingTurkey78 I'm not sure I follow, are you asking how to add additional scalars ?

AgitatedDove14 Well I have a loss function which is something like:
class MyLoss(...): def forward(...): weights = self.compute_weights(...) return (weights * (target-preds)).mean()There seems to be a problem on certain batch when computing the weights. What would be the best way to log the batch that causes the problem, along with the weights being computed.