code: def __init__(
      self,
      n_components=None,
      *,
      copy=True,
      whiten=False,
      svd_solver="auto",
      tol=0.0,
      iterated_power="auto",
      n_oversamples=10,
      power_iteration_normalizer="auto",
      random_state=None,
  ):
      super().__init__(
          n_components,
          copy=copy,
          whiten=whiten,
          svd_solver=svd_solver,
          tol=tol,
          iterated_power=iterated_power,
          n_oversamples=n_oversamples,
          power_iteration_normalizer=power_iteration_normalizer,
          random_state=random_state,
      )
      self._init_shape = None
  
imports: from sklearn.decomposition import PCA
  from sklearn.linear_model import LinearRegression
  import geomstats.backend
label_desc: Use image node_id 1 to create a new WrappedPCA object from inherited base classes: PCA with example: obj = WrappedPCA(n_components)