[Experimental] Likelihood fit with autograd#127
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Improving minimization algorithm, using autograd instead of iminuit. The code keeps the possibility of running both iminuit or the new autograd implementation.
The PR is validated with running
Likelihood.py ../configs/unbinned/unbinned_2016.yaml --overwrite fit[--minuit]`I'm seeing an speed up of a factor of 15 with the autograd implementation, and the resulting uncertainties are the same, to the second decimal point.
The only caveat is that we cannot run minos in this implementation. I don't think we are using it much, but we can implement something similar, if it's necessary.