code: def test_GaussianHMM_wrapper():
      """Verify that the wrapped GaussianHMM estimator agrees with hmmlearn."""
      # moved all potential soft dependency import inside the test:
      from hmmlearn.hmm import GaussianHMM as _GaussianHMM
  
      from sktime.annotation.hmm_learn import GaussianHMM
  
      data = piecewise_normal(
          means=[2, 4, 1], lengths=[10, 35, 40], random_state=7
      ).reshape((-1, 1))
      hmmlearn_model = _GaussianHMM(n_components=3, random_state=7)
      sktime_model = GaussianHMM(n_components=3, random_state=7)
      hmmlearn_model.fit(X=data)
      sktime_model.fit(X=data)
      hmmlearn_predict = hmmlearn_model.predict(X=data)
      sktime_predict = sktime_model.predict(X=data)
      assert array_equal(hmmlearn_predict, sktime_predict)
  
imports: import pytest
  from numpy import array_equal
  from sktime.annotation.datagen import piecewise_normal, piecewise_poisson
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 1 for calling a global function with example usage: test_GaussianHMM_wrapper() without return types