code: def test_dynamic_to_static_broadcast_to():
      def verify_broadcast_to(shape, broadcast_shape):
          x = relay.var("x", relay.TensorType(shape, "float32"))
          y = relay.var(
              "y", relay.TensorType(broadcast_shape, "float32")
          )
          z = relay.broadcast_to(x, shape=relay.shape_of(y))
  
          func = run_infer_type(relay.Function([x, y], z))
          func2 = run_opt_pass(
              run_opt_pass(func, transform.DynamicToStatic()),
              transform.InferType(),
          )
  
          zz = func2.body
          assert isinstance(zz, relay.Call)
          assert zz.op == relay.op.get("broadcast_to")
          assert zz.checked_type == relay.ty.TensorType(
              broadcast_shape, "float32"
          )
  
          x_data = np.random.uniform(low=-1, high=1, size=shape).astype(
              "float32"
          )
          y_data = np.random.uniform(
              low=-1, high=1, size=broadcast_shape
          ).astype("float32")
  
          ref_res = np.broadcast_to(x_data, y_data.shape)
          verify_func(func2, [x_data, y_data], ref_res)
  
      verify_broadcast_to((3, 1), (3, 3))
  
imports: import numpy
  import pytest
  import tvm
  from tvm import te
  from tvm import relay
  from tvm.relay import transform
  from tvm.relay.build_module import bind_params_by_name
  from tvm.relay.testing import run_infer_type, create_workload
  import tvm.topi.testing
  import tvm.testing
label_desc: Use image node_id 9 for calling a global function with example usage: test_dynamic_to_static_broadcast_to() without return types