docstr: The unnormalized log posterior components (the quantity we want to approximate)
  RAO-BLACKWELLIZED!
docstr_tok: ["The","unnormalized","log","posterior","components","(","the","quantity","we","want","to","approximate",")","RAO-BLACKWELLIZED","!"]
code: def log_p(self, z):
      """
      The unnormalized log posterior components (the quantity we want to approximate)
      RAO-BLACKWELLIZED!
      """
      return np.array([self.log_p_blanket(i) for i in z])
  
imports: import sys
  import numpy
  import scipy.stats
  from .stoch_optim import RMSProp, ADAM
  from .bbvi_routines import alpha_recursion, log_p_posterior, mb_log_p_posterior
label_desc: Use image node_id 2 for calling the CBBVI obj's underlying member method code with example usage: obj.log_p(z) and returns: np