code: def test_add_broadcast_op():
      """
      Program:
          fn (%x: Tensor[(10, 4), float32], %y: Tensor[(5, 10, 1), float32])
              -> Tensor[(5, 10, 4), float32] {
              %x + %y
          }
      """
      x = relay.var("x", shape=(10, 4))
      y = relay.var("y", shape=(5, 10, 1))
      z = x + y
      func = relay.Function([x, y], z)
      t1 = relay.TensorType((10, 4), "float32")
      t2 = relay.TensorType((5, 10, 1), "float32")
      t3 = relay.TensorType((5, 10, 4), "float32")
      expected_ty = relay.FuncType([t1, t2], t3)
      assert_has_type(func, expected_ty)
  
imports: import pytest
  import tvm
  from tvm import IRModule, parser, relay, te
  from tvm.relay import analysis, op, transform
  from tvm.relay.op import op
  import numpy
label_desc: Use image node_id 7 for calling a global function with example usage: test_add_broadcast_op() without return types