class_docstr: A Multi-Node Multi-GPU implementation of OneHotEncoder
  
  Refer to the Dask OneHotEncoder implementation
  in `cuml.dask.preprocessing.encoders`.
class_docstr_tok: ["A","Multi-Node","Multi-GPU","implementation","of","OneHotEncoder","Refer","to","the","Dask","OneHotEncoder","implementation","in","`","cuml.dask.preprocessing.encoders","`","."]
docstr: Helper function to check input of fit within the multi-gpu model
docstr_tok: ["Helper","function","to","check","input","of","fit","within","the","multi-gpu","model"]
code: def _check_input_fit(self, X, is_categories=False):
      """Helper function to check input of fit within the multi-gpu model"""
      if isinstance(X, (dask.array.core.Array, cp.ndarray)):
          self._set_input_type("array")
          if is_categories:
              X = X.transpose()
          if isinstance(X, cp.ndarray):
              return DataFrame(X)
          else:
              return to_dask_cudf(X, client=self.client)
      else:
          self._set_input_type("df")
          return X
  
file_path: cuml/python/cuml/preprocessing/onehotencoder_mg.py
imports: from cuml.dask.common.dask_arr_utils import to_dask_cudf
  from cuml.internals.safe_imports import gpu_only_import_from
  from cuml.preprocessing.encoders import OneHotEncoder
  import dask
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 2 for calling the OneHotEncoderMG obj's underlying member method code with example usage: obj._check_input_fit(X, is_categories) and returns: X, DataFrame, to_dask_cudf