class_docstr: RAPIDS KNearestNeighbors model : https://rapids.ai/start.html
  
  NOTE: This code is experimental, it is recommend to not use this unless you are a developer.
  This was tested on rapids-21.06 via:
  
  conda create -n rapids-21.06 -c rapidsai -c nvidia -c conda-forge rapids=21.06 python=3.8 cudatoolkit=11.2
  conda activate rapids-21.06
  pip install --pre autogluon.tabular[all]
code: def _get_model_type(self):
      try_import_rapids_cuml()
      from cuml.neighbors import (
          KNeighborsClassifier,
          KNeighborsRegressor,
      )
  
      if self.problem_type == REGRESSION:
          return KNeighborsRegressor
      else:
          return KNeighborsClassifier
  
file_path: autogluon/tabular/src/autogluon/tabular/models/knn/knn_rapids_model.py
imports: import logging
  from autogluon.common.utils.try_import import try_import_rapids_cuml
  from autogluon.core.constants import REGRESSION
  from .._utils.rapids_utils import RapidsModelMixin
  from .knn_model import KNNModel
label_desc: Use image node_id 1 for calling the KNNRapidsModel obj's underlying member method code with example usage: obj._get_model_type() and returns: KNeighborsRegressor, KNeighborsClassifier