code: def test_init_priors(self, implementation):
      sequences, lengths = self.get_from_one_beal(7, 100, None)
      model = vhmm.VariationalCategoricalHMM(
          4,
          n_iter=500,
          random_state=1984,
          init_params="",
          implementation=implementation,
      )
      model.pi_prior_ = np.full((4,), 0.25)
      model.pi_posterior_ = np.full((4,), 7 / 4)
      model.transmat_prior_ = np.full((4, 4), 0.25)
      model.transmat_posterior_ = np.full((4, 4), 7 / 4)
      model.emissionprob_prior_ = np.full((4, 3), 1 / 3)
      model.emissionprob_posterior_ = np.asarray(
          [
              [0.3, 0.4, 0.3],
              [0.8, 0.1, 0.1],
              [0.2, 0.2, 0.6],
              [0.2, 0.6, 0.2],
          ]
      )
      assert_log_likelihood_increasing(model, sequences, lengths, 10)
  
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 4 for calling the TestVariationalCategorical obj's underlying member method code with example usage: obj.test_init_priors(implementation) without return types