docstr: Check that ZeroRedundancyOptimizer properly exposes the
  ``step(closure)`` interface.
docstr_tok: ["Check","that","ZeroRedundancyOptimizer","properly","exposes","the","``","step","(","closure",")","``","interface","."]
code: def test_step_with_closure(self):
      """Check that ZeroRedundancyOptimizer properly exposes the
      ``step(closure)`` interface."""
      self.dist_init(self.rank, world_size=self.world_size)
  
      with self.context:
          for bucket_view in [False, True]:
              x_val = self.rank + 1
              weight = 1.0
              bias = 2.0
              error = 1.0
              target = torch.tensor(
                  [x_val * weight + bias + error],
                  device=self.device,
              )
              loss_fn = torch.nn.L1Loss()
  
              x = torch.tensor([float(x_val)], device=self.device)
              m = torch.nn.Linear(1, 1)
              m.weight.data = torch.tensor([[weight]])
              m.bias.data = torch.tensor([bias])
              m.to(self.device)
  
              o = ZeroRedundancyOptimizer(
                  m.parameters(),
                  optimizer_class=SGD,
                  parameters_as_bucket_view=bucket_view,
                  lr=0.1,
              )
  
              y = m(x)
              y.backward(x)
              for p in m.parameters():
                  dist.all_reduce(p.grad.data, op=dist.ReduceOp.SUM)
                  p.grad.data /= self.world_size
  
              def closure():
                  o.zero_grad()
                  output = m(x)
                  loss = loss_fn(output, target)
                  loss.backward()
                  return loss
  
              loss = o.step(closure=closure)
  
              self.assertEqual(loss, torch.tensor(error))
              self.assertEqual(m.weight, torch.tensor([[1.1]]))
              self.assertEqual(m.bias, torch.tensor([2.1]))
  
imports: import copy
  import os
  import sys
  import unittest
  from contextlib import nullcontext
  from typing import Any, cast, List
  import numpy
  import torch
  import torch.distributed
  from torch.distributed.algorithms.ddp_comm_hooks.ddp_zero_hook import hook_with_zero_step, hook_with_zero_step_interleaved
  from torch.distributed.algorithms.ddp_comm_hooks.default_hooks import allreduce_hook
  from torch.distributed.algorithms.join import Join, Joinable, JoinHook
  from torch.distributed.optim import ZeroRedundancyOptimizer
  from torch.distributed.optim.zero_redundancy_optimizer import _broadcast_object
  from torch.nn.parallel import DistributedDataParallel
  from torch.optim import AdamW, SGD
  from torch.testing._internal import common_distributed
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, IS_WINDOWS, parametrize, run_tests, TEST_WITH_ASAN, TEST_WITH_DEV_DBG_ASAN
label_desc: Use image node_id 6 for calling the TestZeroRedundancyOptimizerDistributed obj's underlying member method code with example usage: obj.test_step_with_closure() and returns: loss