code: def test_run_floating_forward():
      knn = KNeighborsClassifier()
      sfs = SFS(
          estimator=knn,
          k_features=3,
          forward=True,
          floating=True,
          fixed_features=(0, 1),
          verbose=0,
      )
      sfs.fit(X_iris, y_iris)
      for k in sfs.subsets_:
          assert 0 in sfs.subsets_[k]["feature_idx"]
          assert 1 in sfs.subsets_[k]["feature_idx"]
  
file_path: mlxtend/mlxtend/feature_selection/tests/test_sequential_feature_selector_fixed_features.py
imports: import pandas
  from sklearn.datasets import load_iris
  from sklearn.neighbors import KNeighborsClassifier
  from mlxtend.feature_selection import SequentialFeatureSelector
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 2 for calling a global function with example usage: test_run_floating_forward() without return types