code: def _safe_rechunk(tileable, ax_nsplit):
      do_rechunk = False
      for ax, nsplit in ax_nsplit.items():
          if ax >= tileable.ndim:
              continue
          if tuple(tileable.nsplits[ax]) != tuple(nsplit):
              do_rechunk = True
      if do_rechunk:
          return (
              yield from recursive_tile(tileable.rechunk(ax_nsplit))
          )
      else:
          return tileable
  
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 12 for calling the LearnShuffle obj's underlying member method code with example usage: obj._safe_rechunk(tileable, ax_nsplit) and returns: unknown, tileable