code: def hash_storage_kernel(x):
      # The randint calls are carefully written to hit things we
      # have lowerings for in inductor.  Lack of unsigned 32-bit integer
      # is a pain.
      a = torch.randint(
          -(2**31),
          2**31,
          x.shape,
          device=x.device,
          dtype=torch.int32,
      ).abs()
      a = ((a % (2**31 - 1)) + 1).long()
      b = (
          torch.randint(
              -(2**31),
              2**31,
              x.shape,
              device=x.device,
              dtype=torch.int32,
          )
          .abs()
          .long()
      )
      # This is a standard shift-multiply universal hash family
      # plus xor sum hash, using Philox to generate random numbers.
      # Our Philox RNG is not deterministic across devices so
      # don't use this for stable hashing.
      #
      # This assumes fixed length so you're also obligated to bucket
      # by the length of tensor as well
      return prims.xor_sum((a * x + b).int(), [0])
  
imports: import ctypes
  import functools
  import hashlib
  import os.path
  import struct
  from collections import defaultdict
  from typing import Dict, Optional, Set
  import torch
  import torch._prims
  import torch._utils
  import torch.nn.functional
  from torch._C import default_generator
  from torch.multiprocessing.reductions import StorageWeakRef
label_desc: Use image node_id 2 for calling a global function with example usage: hash_storage_kernel(x) and returns: prims