code: def optimize_slices(dsk):
      """Optimize slices
  
      1.  Fuse repeated slices, like x[5:][2:6] -> x[7:11]
      2.  Remove full slices, like         x[:] -> x
  
      See also:
          fuse_slice_dict
      """
      fancy_ind_types = (list, np.ndarray)
      dsk = dsk.copy()
      for k, v in dsk.items():
          if a_task := _is_getter_task(v):
              get, a, a_index, a_asarray, a_lock = a_task
  
              while b_task := _is_getter_task(a):
                  f2, b, b_index, b_asarray, b_lock = b_task
  
                  if a_lock and a_lock is not b_lock:
                      break
                  if (type(a_index) is tuple) != (
                      type(b_index) is tuple
                  ):
                      break
                  if type(a_index) is tuple:
                      indices = b_index + a_index
                      if len(a_index) != len(b_index) and any(
                          i is None for i in indices
                      ):
                          break
                      if f2 is getter_nofancy and any(
                          isinstance(i, fancy_ind_types)
                          for i in indices
                      ):
                          break
                  elif f2 is getter_nofancy and (
                      type(a_index) in fancy_ind_types
                      or type(b_index) in fancy_ind_types
                  ):
                      break
                  try:
                      c_index = fuse_slice(b_index, a_index)
                      # rely on fact that nested gets never decrease in
                      # strictness e.g. `(getter_nofancy, (getter, ...))` never
                      # happens
                      get = getter if f2 is getter_inline else f2
                  except NotImplementedError:
                      break
                  a, a_index, a_lock = b, c_index, b_lock
                  a_asarray |= b_asarray
  
              # Skip the get call if not from from_array and nothing to do
              if get not in GETNOREMOVE and (
                  (
                      type(a_index) is slice
                      and not a_index.start
                      and a_index.stop is None
                      and a_index.step is None
                  )
                  or (
                      type(a_index) is tuple
                      and all(
                          type(s) is slice
                          and not s.start
                          and s.stop is None
                          and s.step is None
                          for s in a_index
                      )
                  )
              ):
                  dsk[k] = a
              elif get is getitem or (a_asarray and not a_lock):
                  # default settings are fine, drop the extra parameters Since we
                  # always fallback to inner `get` functions, `get is getitem`
                  # can only occur if all gets are getitem, meaning all
                  # parameters must be getitem defaults.
                  dsk[k] = (get, a, a_index)
              else:
                  dsk[k] = (get, a, a_index, a_asarray, a_lock)
  
      return dsk
  
imports: from __future__ import annotations
  from collections.abc import Callable
  from itertools import zip_longest
  from numbers import Integral
  from typing import Any
  import numpy
  from dask import config
  from dask.array.chunk import getitem
  from dask.array.core import getter, getter_inline, getter_nofancy
  from dask.blockwise import fuse_roots, optimize_blockwise
  from dask.core import flatten, reverse_dict
  from dask.highlevelgraph import HighLevelGraph
  from dask.optimization import SubgraphCallable, fuse, inline_functions
  from dask.utils import ensure_dict
label_desc: Use image node_id 4 for calling a global function with example usage: optimize_slices(dsk) and returns: dsk