code: def test_type_call_sequal():
      h1 = relay.GlobalTypeVar("h1")
      h2 = relay.GlobalTypeVar("h2")
      t1 = relay.TensorType((1, 2), "float32")
      t2 = relay.TensorType((1, 2, 3), "float32")
      t3 = relay.TensorType((1, 2, 3, 4), "float32")
      t4 = relay.TensorType((), "float32")
  
      tc = relay.TypeCall(h1, [t1, t2, t3])
      same = relay.TypeCall(h1, [t1, t2, t3])
  
      different_func = relay.TypeCall(h2, [t1, t2, t3])
      different_arg = relay.TypeCall(h1, [t1, t2, t4])
      fewer_args = relay.TypeCall(h1, [t1, t2])
      more_args = relay.TypeCall(h1, [t1, t2, t3, t4])
      different_order_args = relay.TypeCall(h1, [t3, t2, t1])
  
      assert tc == same
      assert tc != different_func
      assert tc != fewer_args
      assert tc != more_args
      assert tc != different_order_args
  
imports: import numpy
  import tvm
  import tvm.testing
  from tvm import relay
  from tvm.relay.testing import run_opt_pass
label_desc: Use image node_id 8 for calling a global function with example usage: test_type_call_sequal() without return types