class_docstr: Prefer single-proc test runner for basic tests as it is easier to work with.
docstr: It's probably not that common to need backwards support for collectives.
  
  However, I wanted to at least see if it was possible to support it as a design goal.
docstr_tok: ["It","'s","probably","not","that","common","to","need","backwards","support","for","collectives",".","However",",","I","wanted","to","at","least","see","if","it","was","possible","to","support","it","as","a","design","goal","."]
code: def test_backwards(self):
      """
      It's probably not that common to need backwards support for collectives.
  
      However, I wanted to at least see if it was possible to support it as a design goal.
      """
  
      def func(inp, *, tag, ranks, group_size):
          ar = _functional_collectives.all_reduce(
              inp, "sum", ranks, tag
          )
          return ar
  
      input = torch.ones(4, 4, device="cuda", requires_grad=True)
      # TODO implement backwards
      with self.assertRaisesRegex(
          RuntimeError,
          "element 0 of tensors does not require grad and does not have a grad_fn",
      ):
          compiled = torch.compile(
              func, backend="aot_eager"
          )  # inductor bug with single-op allreduce graph
          out = compiled(input, **self.get_world_trs())
          out.sum().backward()
  
          correct_input = input.clone().detach().requires_grad_()
          correct = func(correct_input, **self.get_world_trs())
          correct.sum().backward()
          self.assertTrue(same(out, correct))
          self.assertTrue(same(input.grad, correct_input.grad))
  
imports: import functools
  import unittest
  from unittest.mock import patch
  import torch
  from torch._C import FileCheck
  import torch.distributed._functional_collectives
  import torch._dynamo
  import torch._dynamo.test_case
  from torch._dynamo.utils import same
  from torch._dynamo.testing import CompileCounter
  from torch.distributed.distributed_c10d import GroupMember
  from torch.fx.experimental.proxy_tensor import make_fx
  from torch.testing._internal.common_distributed import DynamoDistributedSingleProcTestCase, DynamoDistributedMultiProcTestCase, _dynamo_dist_per_rank_init, requires_nccl, skip_if_lt_x_gpu
  from torch._inductor.compile_fx import compile_fx
  from torch.utils._triton import has_triton
  from torch._inductor.utils import run_and_get_triton_code
  import torch._dynamo.logging
label_desc: Use image node_id 17 for calling the TestCollectivesInductor obj's underlying member method code with example usage: obj.test_backwards() and returns: ar