Bases: zfit.minimizers.baseminimizer.PushbackStrategy, zfit.minimizers.baseminimizer.ToyStrategyFail
Same as DefaultStrategy, but does not raise an error on full failure, instead return an invalid
This can be useful for toy studies, where multiple fits are done and a failure should simply be counted as a
failure instead of rising an error.
Pushback by adding nan_penalty * counter to the loss if NaNs are encountered.
The counter indicates how many NaNs occurred in a row. The nan_tolerance is the upper limit, if this is
exceeded, the fallback will be used and an error is raised.
nan_penalty (Union[float, int]) – Value to add to the previous loss in order to penalize the step taken.
nan_tolerance (int) – If the number of NaNs encountered in a row exceeds this number, the fallback is used.