code: def test_concatenate(target, expected_implementation):
      target = tvm.target.Target(target)
  
      shape = (1, 1, 1, 3)
      dtype = "float32"
      axis = 1
      inputs = []
      inputs.append(relay.var("var0", shape=shape, dtype=dtype))
      inputs.append(relay.var("var1", shape=shape, dtype=dtype))
      input_tuple = relay.Tuple(inputs)
      out = relay.op.concatenate(input_tuple, axis)
      out = run_infer_type(out)
  
      impl, xx = relay.backend.te_compiler.select_implementation(
          relay.op.get("concatenate"),
          out.attrs,
          [te.placeholder(shape)],
          out.checked_type,
          target,
          use_autotvm=False,
      )
      assert impl.name == expected_implementation
  
file_path: tvm/tests/python/relay/strategy/test_select_implementation.py
imports: import pytest
  import numpy
  from unittest.mock import MagicMock
  import tvm
  from tvm import relay
  from tvm import te
  from tvm.relay.testing import run_infer_type, run_opt_pass
  import tvm.testing
  from tvm import topi
label_desc: Use image node_id 1 for calling a global function with example usage: test_concatenate(target, expected_implementation) without return types