docstr: Fit the encoder to X, then transform X. Equivalent to fit(X).transform(X).
  
  Parameters
  ----------
  X : Dask cuDF DataFrame or CuPy backed Dask Array
      The data to encode.
  delayed : bool (default = True)
      Whether to execute as a delayed task or eager.
  
  Returns
  -------
  out : Dask cuDF DataFrame or CuPy backed Dask Array
      Distributed object containing the transformed data
docstr_tok: ["Fit","the","encoder","to","X",",","then","transform","X",".","Equivalent","to","fit","(","X",")",".transform","(","X",")",".","Parameters","--","--","--","--","--","X",":","Dask","cuDF","DataFrame","or","CuPy","backed","Dask","Array","The","data","to","encode",".","delayed",":","bool","(","default","=","True",")","Whether","to","execute","as","a","delayed","task","or","eager",".","Returns","--","--","--","-","out",":","Dask","cuDF","DataFrame","or","CuPy","backed","Dask","Array","Distributed","object","containing","the","transformed","data"]
code: def fit_transform(self, X, delayed=True):
      """Fit the encoder to X, then transform X. Equivalent to fit(X).transform(X).
  
      Parameters
      ----------
      X : Dask cuDF DataFrame or CuPy backed Dask Array
          The data to encode.
      delayed : bool (default = True)
          Whether to execute as a delayed task or eager.
  
      Returns
      -------
      out : Dask cuDF DataFrame or CuPy backed Dask Array
          Distributed object containing the transformed data
      """
      return self.fit(X).transform(X, delayed=delayed)
  
imports: from collections.abc import Sequence
  from cuml.common import with_cupy_rmm
  from cuml.dask.common.base import BaseEstimator, DelayedInverseTransformMixin, DelayedTransformMixin
  from cuml.internals.safe_imports import gpu_only_import_from, gpu_only_import
  from dask_cudf.core import Series
  from toolz import first
label_desc: Use image node_id 1 for calling the DelayedFitTransformMixin obj's underlying member method code with example usage: obj.fit_transform(X, delayed) and returns: self