code: def all_tensors_numel_except_for_step(dct):
      """Compute the sum of numel from all tensors from a dict, except when the key is `step`."""
      ret = 0
      for k, v in dct.items():
          if k != "step" and torch.is_tensor(v):
              ret += v.numel()
      return ret
  
imports: import copy
  import functools
  from time import time
  import unittest
  from parameterized import parameterized
  import torch
  from torch import nn
  from torch.optim import SGD, Adadelta, Adam
  from fairscale.fair_dev.testing.testing import dist_init, objects_are_equal, spawn_for_all_world_sizes
  from fairscale.internal.params import recursive_copy_to_device
  from fairscale.nn.data_parallel import FullyShardedDataParallel, get_fsdp_instances
  from fairscale.nn.data_parallel.fsdp_optim_utils import is_singleton_tensor
  from .test_fsdp import DistributedTest, DummyProcessGroup, MixtureOfExperts, TransformerWithSharedParams, rename_test, spawn_and_init
label_desc: Use image node_id 1 for calling a global function with example usage: all_tensors_numel_except_for_step(dct) and returns: ret