code: def test_dropout():
      class MyModule(torch.nn.Module):
          def forward(self, x: Tensor) -> Tensor:
              return F.dropout(x, p=1.0, training=self.training)
  
      module = MyModule()
      graph_module = torch.fx.symbolic_trace(module)
      graph_module.recompile()
  
      x = torch.randn(4)
  
      graph_module.train()
      assert torch.allclose(graph_module(x), torch.zeros_like(x))
  
      # This is certainly undesired behavior due to tracing :(
      graph_module.eval()
      assert torch.allclose(graph_module(x), torch.zeros_like(x))
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_dropout() and returns: F