class_docstr: A distributed Dask DataFrame where the backing dataframe is a
  :class:`cuDF DataFrame <cudf:cudf.DataFrame>`.
  
  Typically you would not construct this object directly, but rather
  use one of Dask-cuDF's IO routines.
  
  Most operations on :doc:`Dask DataFrames <dask:dataframe>` are
  supported, with many of the same caveats.
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code: def sort_values(
      self,
      by,
      ignore_index=False,
      max_branch=None,
      divisions=None,
      set_divisions=False,
      ascending=True,
      na_position="last",
      sort_function=None,
      sort_function_kwargs=None,
      shuffle_method=None,
      **kwargs,
  ):
      if kwargs:
          raise ValueError(
              f"Unsupported input arguments passed : {list(kwargs.keys())}"
          )
  
      df = sorting.sort_values(
          self,
          by,
          max_branch=max_branch,
          divisions=divisions,
          set_divisions=set_divisions,
          ignore_index=ignore_index,
          ascending=ascending,
          na_position=na_position,
          shuffle_method=shuffle_method,
          sort_function=sort_function,
          sort_function_kwargs=sort_function_kwargs,
      )
  
      if ignore_index:
          return df.reset_index(drop=True)
      return df
  
imports: import math
  import textwrap
  import warnings
  import numpy
  import pandas
  from tlz import partition_all
  from dask import dataframe
  from dask.base import normalize_token, tokenize
  from dask.dataframe.core import Scalar, handle_out, make_meta, map_partitions
  from dask.dataframe.utils import raise_on_meta_error
  from dask.highlevelgraph import HighLevelGraph
  from dask.utils import M, OperatorMethodMixin, apply, derived_from, funcname
  import cudf
  from cudf import _lib
  from cudf.utils.nvtx_annotation import _dask_cudf_nvtx_annotate
  from dask_cudf import sorting
  from dask_cudf.accessors import ListMethods, StructMethods
  from dask_cudf.sorting import _deprecate_shuffle_kwarg, _get_shuffle_method
label_desc: Use image node_id 6 for calling the DataFrame obj's underlying member method code with example usage: obj.sort_values(by, ignore_index, max_branch, divisions, set_divisions, ascending, na_position, sort_function, sort_function_kwargs, shuffle_method) and returns: df, df