code: def _accumulate_sufficient_statistics(
      self, stats, X, framelogprob, posteriors, fwdlattice, bwdlattice
  ):
      super()._accumulate_sufficient_statistics(
          stats, X, framelogprob, posteriors, fwdlattice, bwdlattice
      )
      if "e" in self.params:
          stats["obs"] += posteriors.T @ X
  
imports: import functools
  import inspect
  import warnings
  import numpy
  from scipy import special
  from scipy.stats import multinomial, poisson
  from sklearn.utils import check_random_state
  from .base import BaseHMM, _AbstractHMM
  from .stats import log_multivariate_normal_density
  from .utils import fill_covars, log_normalize
label_desc: Use image node_id 6 for calling the BaseMultinomialHMM obj's underlying member method code with example usage: obj._accumulate_sufficient_statistics(stats, X, framelogprob, posteriors, fwdlattice, bwdlattice) without return types