class_docstr: RAPIDS Linear 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):
      penalty = self.params.get("penalty", "L2")
      try_import_rapids_cuml()
      from cuml.linear_model import Lasso, LogisticRegression, Ridge
  
      if self.problem_type == REGRESSION:
          if penalty == "L2":
              model_type = Ridge
          elif penalty == "L1":
              model_type = Lasso
          else:
              raise AssertionError(
                  f'Unknown value for penalty "{penalty}" - supported types are ["L1", "L2"]'
              )
      else:
          model_type = LogisticRegression
      return model_type
  
file_path: autogluon/tabular/src/autogluon/tabular/models/lr/lr_rapids_model.py
imports: import logging
  import numpy
  from autogluon.common.utils.try_import import try_import_rapids_cuml
  from autogluon.core.constants import REGRESSION
  from .._utils.rapids_utils import RapidsModelMixin
  from .hyperparameters.parameters import get_param_baseline
  from .lr_model import LinearModel
label_desc: Use image node_id 1 for calling the LinearRapidsModel obj's underlying member method code with example usage: obj._get_model_type() and returns: model_type