code: def test_multi_kernel():
      """Test scheduling with multiple computes."""
      # graph
      arr_length = 1024
      arr_length_tvm = tvm.runtime.convert(arr_length)
      placeholder_a = te.placeholder((arr_length_tvm,), name="A")
      placeholder_b = te.placeholder((arr_length_tvm,), name="B")
      result_c = te.compute(
          placeholder_a.shape,
          lambda *i: placeholder_a(*i) + placeholder_b(*i),
          name="C",
      )
      result_d = te.compute(
          placeholder_a.shape,
          lambda *i: placeholder_a(*i) + result_c(*i),
          name="D",
      )
      schedule = te.create_schedule(result_d.op)
      # create iter var and assign them tags.
      axis1, _ = schedule[result_c].split(result_c.op.axis[0], nparts=1)
      schedule[result_c].bind(axis1, te.thread_axis("pipeline"))
      axis1, _ = schedule[result_d].split(result_d.op.axis[0], nparts=1)
      schedule[result_d].bind(axis1, te.thread_axis("pipeline"))
  
      # one line to build the function.
      def check_device(device, host="llvm"):
          if not tvm.testing.device_enabled(device):
              return
          dev = tvm.device(device, 0)
          fadd = tvm.build(
              schedule,
              [placeholder_a, placeholder_b, result_c, result_d],
              device,
              host,
              name="myadd",
          )
          dev = tvm.device(device, 0)
          # launch the kernel.
          buff_a = tvm.nd.array(
              np.random.uniform(size=arr_length).astype(
                  placeholder_a.dtype
              ),
              dev,
          )
          buff_b = tvm.nd.array(
              np.random.uniform(size=arr_length).astype(
                  placeholder_b.dtype
              ),
              dev,
          )
          buff_c = tvm.nd.array(
              np.random.uniform(size=arr_length).astype(result_c.dtype),
              dev,
          )
          buff_d = tvm.nd.array(
              np.random.uniform(size=arr_length).astype(result_d.dtype),
              dev,
          )
          fadd(buff_a, buff_b, buff_c, buff_d)
          tvm.testing.assert_allclose(
              buff_d.numpy(),
              buff_a.numpy() * 2 + buff_b.numpy(),
              rtol=1e-5,
          )
  
      check_device("sdaccel")
      check_device("aocl_sw_emu")
  
file_path: tvm/tests/python/integration/test_ewise_fpga.py
imports: import os
  import numpy
  import tvm
  import tvm.testing
  from tvm import te
label_desc: Use image node_id 3 for calling a global function with example usage: test_multi_kernel() without return types