code: def test_lrn():
      """LRN unit test."""
  
      def verify_lrn(xshape, size, dtype="float32"):
          x = relay.var("x", relay.ty.TensorType(xshape, dtype))
          y = relay.nn.lrn(
              x, size=size, axis=1, alpha=1.0, beta=1.0, bias=1.0
          )
          func = relay.Function([x], y)
          x_data = np.random.uniform(size=xshape).astype(dtype)
          verify_results(
              func, [x_data], "test_lrn", rtol=1e-5, atol=1e-5
          )
  
      isize = [(1, 1, 480, 640), (1, 3, 224, 224)]
      sizes = [1, 3]
      for i in isize:
          for s in sizes:
              verify_lrn(i, s)
  
imports: import pytest
  import numpy
  import onnxruntime
  import tvm
  from tvm import relay
  from tvm.contrib.target.onnx import to_onnx
  from tvm.relay.testing import run_infer_type
label_desc: Use image node_id 29 for calling a global function with example usage: test_lrn() without return types