class_docstr: Superclass for DataFrame and Series
  
  Parameters
  ----------
  dsk : dict
      The dask graph to compute this DataFrame
  name : str
      The key prefix that specifies which keys in the dask comprise this
      particular DataFrame / Series
  meta : cudf.DataFrame, cudf.Series, or cudf.Index
      An empty cudf object with names, dtypes, and indices matching the
      expected output.
  divisions : tuple of index values
      Values along which we partition our blocks on the index
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code: def _is_partition_type(self, meta):
      return isinstance(meta, self._partition_type)
  
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 1 for calling the _Frame obj's underlying member method code with example usage: obj._is_partition_type(meta) and returns: isinstance