Add class weights to the EnsembleVotingClassifier

I used gradient boosting classifier to build a classification model. I am trying to improve the model by using a stack up model. I want to ensemble 3 different models, let's say, gbm, randomforests, logistic regression (except for gbm, other models subject to change). In my GBM model, I used weights in the fit function by giving higher weights to positive target variable. I want too try the same thing in ensemble, but I am unable to figure out how to implement weights in the source code of the ensemblevotingclassifier. I am new to this, so would like to receive suggestions regarding implementation of weights

Thanks

Start at the EnsembleVotingClassifier entry point and compare its fitting behavior with the gradient boosting classifier's weighted fit behavior. Determine how class weights should be represented and passed across the three constituent models, including models that may change. Done means the ensemble supports the requested weighting behavior consistently and its expected usage is documented or tested.