class_docstr: Helper class to make use of optimized parameters in both FIL and
  experimental FIL through a uniform interface
code: def predict(self, X):
      if self.infer_type == "per_tree":
          return self.fil_model.predict_per_tree(
              X, **self.predict_kwargs
          )
      return self.fil_model.predict(X, **self.predict_kwargs)
  
imports: from cuml.manifold import UMAP
  from cuml.benchmark import datagen
  from cuml.common.device_selection import using_device_type
  from cuml.internals.device_type import DeviceType
  from cuml.internals.global_settings import GlobalSettings
  from cuml.internals.safe_imports import cpu_only_import, gpu_only_import, gpu_only_import_from, safe_import
  import sklearn.ensemble
  import pickle
  import os
  import cuml
  from cuml.internals import input_utils
  from time import perf_counter
label_desc: Use image node_id 2 for calling the OptimizedFilWrapper obj's underlying member method code with example usage: obj.predict(X) and returns: self, self