code: def unify_nsplits(*tensor_axes):
      tensor_splits = [
          dict(
              (a, split)
              for a, split in zip(axes, t.nsplits)
              if split != (1,)
          )
          for t, axes in tensor_axes
          if t.nsplits
      ]
      common_axes = (
          reduce(
              operator.and_, [set(ts.keys()) for ts in tensor_splits]
          )
          if tensor_splits
          else set()
      )
      axes_unified_splits = dict(
          (ax, decide_unify_split(*(t[ax] for t in tensor_splits)))
          for ax in common_axes
      )
  
      if len(common_axes) == 0:
          return tuple(t[0] for t in tensor_axes)
  
      res = []
      for t, axes in tensor_axes:
          new_chunk = dict(
              (i, axes_unified_splits[ax])
              for ax, i in zip(axes, range(t.ndim))
              if ax in axes_unified_splits
          )
          t = yield from recursive_tile(t.rechunk(new_chunk))
          res.append(t)
  
      return tuple(res)
  
imports: import inspect
  import itertools
  import operator
  from collections import OrderedDict
  from collections.abc import Iterable
  from functools import lru_cache, reduce, wraps
  from math import ceil
  from numbers import Integral
  from typing import Dict, List, Union
  import numpy
  from ..core import ExecutableTuple, recursive_tile
  from ..utils import lazy_import
  from ..lib.mmh3 import hash_from_buffer
label_desc: Use image node_id 20 for calling a global function with example usage: unify_nsplits() and returns: tuple, tuple