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 _preprocess(self, X, **kwargs):
      X = super()._preprocess(X=X, **kwargs)
      if not isinstance(X, np.ndarray):
          X = X.toarray()
      return X
  
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 3 for calling the LinearRapidsModel obj's underlying member method code with example usage: obj._preprocess(X) and returns: X