code: def test_no_grad(self):
      def fn1(a, b):
          x = a + 1
          # redundant no_grad should get ignored
          with torch.no_grad():
              x = x + b
          x = x + 2
          return x
  
      def fn2(a, b):
          x = a + 1
          with torch.set_grad_enabled(False):
              x = x + b
          x = x + 2
          return x
  
      def fn3(a, b):
          x = a + 1
          with torch.enable_grad():
              x = x + b
          x = x + 2
          return x
  
      def fn4(a, b):
          x = a + 1
          with torch.set_grad_enabled(True):
              if torch.is_grad_enabled():
                  x = x + b
          x = x + 2
          return x
  
      with torch.no_grad():
          torch._dynamo.testing.standard_test(
              self, fn=fn1, nargs=2, expected_ops=3
          )  # coalesced noop
          torch._dynamo.testing.standard_test(
              self, fn=fn2, nargs=2, expected_ops=3
          )  # coalesced noop
          torch._dynamo.testing.standard_test(
              self, fn=fn3, nargs=2, expected_ops=5
          )
          torch._dynamo.testing.standard_test(
              self, fn=fn4, nargs=2, expected_ops=5
          )
      with torch.enable_grad():
          torch._dynamo.testing.standard_test(
              self, fn=fn1, nargs=2, expected_ops=5
          )
          torch._dynamo.testing.standard_test(
              self, fn=fn2, nargs=2, expected_ops=5
          )
          torch._dynamo.testing.standard_test(
              self, fn=fn3, nargs=2, expected_ops=3
          )  # coalesced noop
          torch._dynamo.testing.standard_test(
              self, fn=fn4, nargs=2, expected_ops=3
          )
  
imports: import unittest
  import torch
  import torch._dynamo.test_case
  import torch._dynamo.testing
  import torch.onnx.operators
  from torch._dynamo.testing import EagerAndRecordGraphs, normalize_gm, same
  from torch.nn import functional
  from torch.testing._internal.common_cuda import PLATFORM_SUPPORTS_FLASH_ATTENTION
  from torch.testing._internal.common_utils import TEST_WITH_ROCM
label_desc: Use image node_id 1 for calling the CtxManagerTests obj's underlying member method code with example usage: obj.test_no_grad() and returns: x, x, x, x