Handle dynamo function without input (#5565) (#5577)

Author: JackCaoG

test/dynamo/test_dynamo.py

@@ -123,6 +123,20 @@ def test_simple_model(self):
     res_cpu_3 = self.fn_simple(x + y, y * 3)
     self.assertTrue(torch.allclose(res_cpu_3, res_xla_dynamo_3.cpu()))
 
+  def test_fn_without_input(self):
+
+    def fn_without_input(device):
+      constant = 0.835
+      expanded = torch.full((4, 4), constant, device=device)
+      arange = torch.arange(16, device=device).reshape(4, 4)
+      return expanded + arange
+
+    device = xm.xla_device()
+    compiled_fn = torch.compile(fn_without_input, backend='openxla')
+    res_cpu = fn_without_input('cpu')
+    res_xla_dynamo = compiled_fn(device)
+    self.assertTrue(torch.allclose(res_cpu, res_xla_dynamo.cpu()))
+
   def test_simple_model_with_in_place_ops(self):
 
     class TestModel(nn.Module):

torch_xla/core/dynamo_bridge.py

@@ -368,7 +368,6 @@ def optimized_mod(*args):
     if len(args_and_out) == 0:
       return ()
 
-    assert len(args) > 0  # can not handle no args case for now
     graph_input = graph_input_matcher(args)
     start_ts = time.time()
     res = torch_xla._XLAC._run_cached_graph(graph_hash, graph_input)