code: def __init__(self, steps, *, memory=None, verbose=False):
      super().__init__(steps, memory=memory, verbose=verbose)
      self._fit_vars = set()
      self._feature_names_in = None
      self._cache_full_transform = True
  
imports: import platform
  import warnings
  from copy import deepcopy
  from inspect import signature
  import imblearn.pipeline
  import sklearn.pipeline
  from sklearn.base import clone
  from sklearn.utils import _print_elapsed_time
  from sklearn.utils.metaestimators import available_if
  from sklearn.utils.validation import check_memory
  from pycaret.utils._show_versions import _get_deps_info
  from pycaret.utils.generic import get_all_object_vars_and_properties, variable_return
label_desc: Use image node_id 1 to create a new Pipeline object from inherited base classes: imblearn.pipeline with example: obj = Pipeline(steps)