code: def calculate_reallocate_info(
      order: Sequence[Apply],
      fgraph: "FunctionGraph",
      storage_map: "StorageMapType",
      compute_map_re: "ComputeMapType",
      dependencies: dict[Variable, list[Variable]],
  ) -> dict[Variable, list[Variable]]:
      """Finds pairs of computed variables that can share a storage cell.
  
      This apparently reduces memory allocations, but its scope is very limited
      (e.g. only scalars, only used by the Python VMs without lazy computations).
  
      Parameters
      ----------
      order
          List of nodes in compute order.
      fgraph
          The `FunctionGraph`.
      storage_map
          Map from variables to their storage cells.
      compute_map_re
          Reallocation map.  TODO
      dependencies
          Map from variables to the variables that depend on them.
  
      """
      reallocated_info = {}
      viewed_by: dict[Variable, list[Variable]] = {}
      for var in fgraph.variables:
          viewed_by[var] = []
      view_of: dict[Variable, Variable] = {}
      pre_allocated = set()
      allocated = set()
  
      for idx in range(len(order)):
          node = order[idx]
          dmap = node.op.destroy_map
          vmap = node.op.view_map
  
          idx_o = 0
          for out in node.outputs:
              for var in node.outputs:
                  compute_map_re[var][0] = True
              ins = None
              if dmap and idx_o in dmap:
                  idx_v = dmap[idx_o]
                  assert (
                      len(idx_v) == 1
                  ), "Here we only support the possibility to destroy one input"
                  ins = node.inputs[idx_v[0]]
              if vmap and idx_o in vmap:
                  assert ins is None
                  idx_v = vmap[idx_o]
                  assert (
                      len(idx_v) == 1
                  ), "Here we only support the possibility to view one input"
                  ins = node.inputs[idx_v[0]]
              if ins is not None:
                  assert isinstance(ins, Variable)
                  origin = view_of.get(ins, ins)
                  view_of[out] = origin
                  viewed_by[origin].append(out)
              idx_o += 1
  
          for ins in node.inputs:
              assert not (ins in view_of and viewed_by[ins])
              if (
                  getattr(ins.type, "ndim", None) == 0
                  and not storage_map[ins][0]
                  and ins not in fgraph.outputs
                  and ins.owner
                  and all(
                      compute_map_re[v][0]
                      for v in dependencies.get(ins, [])
                  )
                  and ins not in allocated
              ):
                  # Constant memory cannot be changed
                  # Constant and shared variables' storage_map value is not empty
                  reuse_out = None
                  if ins not in view_of and not viewed_by.get(ins, []):
                      # where gc
                      for i in range(idx + 1, len(order)):
                          if reuse_out is not None:
                              break  # type: ignore
                          for out in order[i].outputs:
                              if (
                                  getattr(out.type, "ndim", None) == 0
                                  and out not in pre_allocated
                                  and out.type.in_same_class(ins.type)
                              ):
                                  reuse_out = out
                                  pre_allocated.add(out)
                                  allocated.add(ins)
                                  break
                  elif ins in view_of:
                      origin = view_of[ins]
                      if ins in viewed_by[origin]:
                          viewed_by[origin].remove(ins)
                      if (
                          not viewed_by[origin]
                          and origin not in fgraph.inputs
                          and not isinstance(origin, Constant)
                      ):
                          # where gc
                          for i in range(idx + 1, len(order)):
                              if reuse_out is not None:
                                  break
                              for out in order[i].outputs:
                                  if (
                                      getattr(out.type, "ndim", None)
                                      == 0
                                      and out not in pre_allocated
                                      and (
                                          out.type.in_same_class(
                                              ins.type
                                          )
                                      )
                                  ):
                                      reuse_out = out
                                      pre_allocated.add(out)
                                      allocated.add(ins)
                                      break
                  if reuse_out is not None:
                      reallocated_info[ins] = [ins, reuse_out]
  
      return reallocated_info
  
imports: import platform
  import sys
  import time
  import warnings
  from abc import ABC, abstractmethod
  from collections import defaultdict
  from collections.abc import Sequence
  from itertools import zip_longest
  from typing import TYPE_CHECKING, Any, Optional
  from pytensor.configdefaults import config
  from pytensor.graph.basic import Apply, Constant, Variable
  from pytensor.link.basic import Container, LocalLinker
  from pytensor.link.c.exceptions import MissingGXX
  from pytensor.link.utils import gc_helper, get_destroy_dependencies, map_storage, raise_with_op
label_desc: Use image node_id 1 for calling a global function with example usage: calculate_reallocate_info(order, fgraph, storage_map, compute_map_re, dependencies) and returns: reallocated_info