code: def test_no_convert_layout():
      def before():
          x = relay.var("x", shape=(1, 64, 56, 56))
          weight = relay.var("weight", shape=(64, 64, 3, 3))
          y = relay.nn.conv2d(
              x, weight, channels=64, kernel_size=(3, 3), padding=(1, 1)
          )
          y = relay.nn.relu(y)
          y = relay.Function([x, weight], y)
          return y
  
      def expected():
          return before()
  
      a = before()
      a = run_opt_pass(
          a, transform.ConvertLayout({"nn.conv2d": ["NCHW", "default"]})
      )
      b = run_opt_pass(expected(), transform.InferType())
  
      assert tvm.ir.structural_equal(a, b), "Actual = \n" + str(a)
  
imports: import pytest
  import tvm
  from tvm import relay, te
  from tvm.relay import analysis, transform
  from tvm.relay.op import op
  from tvm.relay.op import register_alter_op_layout
  from tvm.relay.quantize._annotate import attach_simulated_quantize, QAnnotateKind
  from tvm.relay.transform.infer_layout_utils import InferCorrectLayoutOutput
label_desc: Use image node_id 2 for calling a global function with example usage: test_no_convert_layout() and returns: y, before