code: def deserialize(cls, header, frames):
      names = pickle.loads(header["names"])
      _named_columns = pickle.loads(header["_named_columns"])
      key_columns = cudf.core.column.deserialize_columns(
          header["columns"], frames[: -header["__bin_labels_count"]]
      )
      out = _ResampleGrouping.__new__(_ResampleGrouping)
      out.names = names
      out._named_columns = _named_columns
      out._key_columns = key_columns
      out.bin_labels = cudf.core.index.Index.deserialize(
          header["__bin_labels"],
          frames[-header["__bin_labels_count"] :],
      )
      out._freq = header["_freq"]
      return out
  
imports: import pickle
  import numpy
  import pandas
  import cudf
  import cudf._lib.labeling
  import cudf.core.index
  from cudf._typing import DataFrameOrSeries
  from cudf.core.groupby.groupby import DataFrameGroupBy, GroupBy, SeriesGroupBy, _Grouping
  from cudf.core.tools.datetimes import _offset_alias_to_code, _unit_dtype_map
label_desc: Use image node_id 5 for calling the _ResampleGrouping obj's underlying member method code with example usage: obj.deserialize(cls, header, frames) and returns: out