code: def test_inception_like():
      def conv(data):
          y = relay.nn.conv2d(
              data,
              relay.var("w"),
              kernel_size=(3, 3),
              padding=(1, 1),
              channels=16,
          )
          return relay.nn.relu(data=y)
  
      def inception_like(data):
          c0 = conv(data)
          c1 = conv(data)
          return relay.concatenate((c0, c1), axis=1)
  
      def before(dshape):
          x = relay.var("x", shape=dshape)
          in1 = inception_like(x)
          in2 = inception_like(in1)
          return relay.Function(relay.analysis.free_vars(in2), in2)
  
      dshape = (1, 16, 64, 64)
      x = before(dshape)
      x = run_opt_pass(x, transform.InferType())
      fused = run_opt_pass(x, transform.FuseOps())
      defused = run_opt_pass(fused, transform.DefuseOps())
  
      assert tvm.ir.structural_equal(x, defused)
  
file_path: tvm/tests/python/relay/test_pass_defuse_ops.py
imports: import numpy
  import pytest
  import tvm
  from tvm import relay
  from tvm.relay import transform
  from tvm.relay.testing import run_opt_pass
label_desc: Use image node_id 2 for calling a global function with example usage: test_inception_like() and returns: relay, relay, relay