code: def setup(self):
      # We fix the random state here to demonstrate that the model will
      # successfully remove "unnecessary" states.  In practice,
      # one should not set the random_state, and perform multiple
      # training steps, and take the model with the best lower-bound
      self.n_components = 3
      self.implementations = ["scaling", "log"]
  
file_path: hmmlearn/lib/hmmlearn/tests/test_variational_categorical.py
imports: import numpy
  import pytest
  from sklearn.utils import check_random_state
  from hmmlearn import hmm, vhmm
  from .None import assert_log_likelihood_increasing, compare_variational_and_em_models, vi_uniform_startprob_and_transmat
label_desc: Use image node_id 1 for calling the TestVariationalCategorical obj's underlying member method code with example usage: obj.setup() without return types