code: def __init__(
      self,
      axes=None,
      seeds=None,
      output_types=None,
      reduce_sizes=None,
      **kw,
  ):
      super().__init__(
          _axes=axes,
          _seeds=seeds,
          _output_types=output_types,
          _reduce_sizes=reduce_sizes,
          **kw,
      )
  
imports: import itertools
  from collections import defaultdict
  from collections.abc import Iterable
  from functools import reduce
  import numpy
  import pandas
  from ...None import opcodes
  from ...core import get_output_types, recursive_tile
  from ...core.operand import OperandStage, MapReduceOperand
  from ...dataframe.utils import parse_index
  from ...lib import sparse
  from ...serialization.serializables import FieldTypes, TupleField, KeyField
  from ...tensor.utils import validate_axis, check_random_state, gen_random_seeds, decide_unify_split
  from ...tensor.array_utils import get_array_module
  from ...utils import tokenize, lazy_import, has_unknown_shape
  from ...core import ExecutableTuple
  from ..operands import LearnOperandMixin, OutputType, LearnShuffleProxy
  from ..utils import convert_to_tensor_or_dataframe
label_desc: Use image node_id 1 to create a new LearnShuffle object from inherited base classes: MapReduceOperand, LearnOperandMixin with example: obj = LearnShuffle(axes, seeds, output_types, reduce_sizes)