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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def transform(self,x,inds=None,labels = None):
 """return a transformation of x using population outputs"""

        if inds:
            # return np.asarray(Parallel(n_jobs=10)(delayed(self.out)(I,x,labels,self.otype) 
            #                           for I in inds)).transpose()
            return np.asarray(
                [self.out(I,x,labels,self.otype) for I in inds]).transpose()
        elif self._best_inds:
            # return np.asarray(Parallel(n_jobs=10)(delayed(self.out)(I,x,labels,self.otype) 
            #                                   for I in self._best_inds)).transpose()
            return np.asarray(
                [self.out(I,x,labels,self.otype) for I in self._best_inds]).transpose()
        else:
            return x