code: def posterior_predictive(self, model, posterior, **kwargs):
      n = model.response_component.response_term.data.sum(1).astype(int)
      dont_reshape = ["n"]
      return super().posterior_predictive(
          model, posterior, n=n, dont_reshape=dont_reshape
      )
  
imports: import numpy
  import pytensor.tensor
  import xarray
  from bambi.families.family import Family
  from bambi.transformations import transformations_namespace
  from bambi.utils import extract_argument_names, get_aliased_name
label_desc: Use image node_id 3 for calling the Multinomial obj's underlying member method code with example usage: obj.posterior_predictive(model, posterior) and returns: super