code: def test_fit_beal(self, implementation):
      rs = check_random_state(1984)
      m1, m2, m3 = self.get_beal_models()
      sequences = []
      lengths = []
      for i in range(7):
          for m in [m1, m2, m3]:
              sequences.append(m.sample(39, random_state=rs)[0])
              lengths.append(len(sequences[-1]))
      sequences = np.concatenate(sequences)
      model = vhmm.VariationalCategoricalHMM(
          12,
          n_iter=500,
          implementation=implementation,
          tol=1e-6,
          random_state=rs,
          verbose=False,
      )
  
      assert_log_likelihood_increasing(model, sequences, lengths, 100)
  
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 7 for calling the TestVariationalCategorical obj's underlying member method code with example usage: obj.test_fit_beal(implementation) without return types