implement Sofomore.active(kernel) method #4

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1. nikohansen

   added

   enhancementNew feature or requestNew feature or request

   questionFurther information is requestedFurther information is requested

   on Oct 27, 2021
2. nikohansen commented on Oct 27, 2021

   

   nikohansen

   on Oct 27, 2021

   Last edited by nikohansen

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   Another question: why don't we activate the kernel unconditionally?
3. nikohansen commented on Oct 27, 2021

   

   nikohansen

   on Oct 27, 2021

   Last edited by nikohansen

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   Tentative code:

       def activate(self, kernel, reset_termination=True, reset_stagnation=False):
           if reset_termination:
               kernel._stopdict.clear()
           if reset_stagnation:
               kernel.fit.histbest.clear()  # reset opts['tolstagnation']
               kernel.fit.histmedian.clear()  # ditto
           ikernel = self.kernels.index(kernel)  # kernel must be in self.kernels
           if ikernel in self._active_indices:
               return
           self._active_indices += [ikernel]
           # remove "turned off" status
           if kernel.opts['termination_callback']:
               kernel.opts['termination_callback'] = [c for c in kernel.opts['termination_callback']
                                                      if c(kernel) != 'kernel turned off']
4. cheikhToure commented on Oct 28, 2021

   

   cheikhToure

   on Oct 28, 2021

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   The Sofomore.activate method should be implemented, in order to be able to refine a kernel.

   • we probably want to call, maybe optionally, kernel._stopdict.clear() during activation

   • @cheikhToure I don't understand the tentative code (see above link)

          new_list = [callback for callback in self.kernels[ikernel].opts['termination_callback']\
                  if callback(kernel) == 'kernel turned off']
          kernel.opts['termination_callback'] = new_list

     Was the == mean to read != such that the turned off termination is removed?

   Yes it was meant to read !=.
5. cheikhToure commented on Oct 28, 2021

   

   cheikhToure

   on Oct 28, 2021

   Last edited by cheikhToure

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   Another question: why don't we activate the kernel unconditionally?

   The tentative code was meant to activate a kernel that we inactivated beforehand, mainly for budget allocation.

   When we do:

   import cma
   es = cma.CMAEvolutionStrategy(10 * [1], 0.2)
   es.optimize(cma.ff.sphere)

   The optimization is done in ~ 2000 function evaluations with a tolfun stopping criterion.
   If we then do

   es.optimize(lambda x: cma.ff.sphere(x - 1))

   The step-size of es increases for 1000 more function evaluations before decreasing for another 2000 function evaluations and we hit a tolstagnation criterion.

   The idea was to avoid this adaptive phase that costs 1000 function evaluations when activating a kernel that we did not turn off on purpose (mainly for budget allocation) during the optimization of a changing fitness.
6. nikohansen commented on Oct 29, 2021

   

   nikohansen

   on Oct 29, 2021

   Last edited by nikohansen

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   Maybe we want a method that checks for deactivation status, like

       def inactivated(self, kernel):
           """return `True` if kernel was deactivated with `Sofomore.inactivate`, else `False`
           """
           try:
               for c in kernel.opts['termination_callback']:
                   if c(kernel) == 'kernel turned off':
                       return True
           except TypeError: # termination callback options were not iterable
               pass
           return False
   # or:
       def inactivated(self, kernel):
           s = kernel.stop(check=False)
           for k in s:
               if k == 'callback' and 'kernel turned off' in s[k]:
                   return True
           return False

   which would allow to write

       moes.activate(kernel) if moes.inactivated(kernel) else None

   to activate the kernel only when it was inactivated before.
7. nikohansen

   self-assigned this

   on Jul 12, 2022