code: def _gen_shuffle_chunks(cls, op, chunks):
      # generate map chunks
      map_chunks = []
      chunk_shape = (len(chunks), 1)
      for chunk in chunks:
          # no longer consider as_index=False for the intermediate phases,
          # will do reset_index at last if so
          map_op = DataFrameGroupByOperand(
              stage=OperandStage.map,
              shuffle_size=chunk_shape[0],
              output_types=[OutputType.dataframe_groupby],
          )
          map_chunks.append(
              map_op.new_chunk(
                  [chunk],
                  shape=(np.nan, np.nan),
                  index=chunk.index,
                  index_value=op.outputs[0].index_value,
              )
          )
  
      proxy_chunk = DataFrameShuffleProxy(
          output_types=[OutputType.dataframe]
      ).new_chunk(map_chunks, shape=())
  
      # generate reduce chunks
      reduce_chunks = []
      out_indices = list(
          itertools.product(*(range(s) for s in chunk_shape))
      )
      for out_idx in out_indices:
          reduce_op = DataFrameGroupByOperand(
              stage=OperandStage.reduce,
              output_types=[OutputType.dataframe_groupby],
              n_reducers=len(out_indices),
          )
          reduce_chunks.append(
              reduce_op.new_chunk(
                  [proxy_chunk],
                  shape=(np.nan, np.nan),
                  index=out_idx,
                  index_value=None,
              )
          )
      return reduce_chunks
  
imports: import functools
  import itertools
  import logging
  import uuid
  from typing import Callable, Dict, List, Union
  import numpy
  import pandas
  from ...None import opcodes
  from ...config import options
  from ...core import ENTITY_TYPE, OutputType
  from ...core.custom_log import redirect_custom_log
  from ...core.context import get_context
  from ...core.operand import OperandStage
  from ...serialization.serializables import Int32Field, Int64Field, AnyField, BoolField, StringField, ListField, DictField
  from ...typing import ChunkType, TileableType
  from ...utils import enter_current_session, lazy_import, pd_release_version, estimate_pandas_size
  from ..arrays import ArrowArray
  from ..core import GROUPBY_TYPE
  from ..merge import DataFrameConcat
  from ..operands import DataFrameOperand, DataFrameOperandMixin, DataFrameShuffleProxy
  from ..reduction.core import ReductionCompiler, ReductionSteps, ReductionAggStep
  from ..reduction.aggregation import is_funcs_aggregate, normalize_reduction_funcs
  from ..utils import parse_index, build_concatenated_rows_frame, is_cudf, concat_on_columns
  from .core import DataFrameGroupByOperand
  from .custom_aggregation import custom_agg_functions
  from .sort import DataFramePSRSGroupbySample, DataFrameGroupbyConcatPivot, DataFrameGroupbySortShuffle
label_desc: Use image node_id 11 for calling the DataFrameGroupByAgg obj's underlying member method code with example usage: obj._gen_shuffle_chunks(cls, op, chunks) and returns: reduce_chunks