code: def test_tvmc_cl_workflow_json_config(keras_simple, tmpdir_factory):
      pytest.importorskip("tensorflow")
      tune_config_file = "tune_config_test"
      tmpdir = tmpdir_factory.mktemp("data")
  
      # Test model tuning
      log_path = os.path.join(tmpdir, "keras-autotuner_records.json")
      tuning_str = (
          f"tvmc tune --config {tune_config_file} --output {log_path} "
          f"--enable-autoscheduler {keras_simple}"
      )
      tuning_args = tuning_str.split(" ")[1:]
      _main(tuning_args)
      assert os.path.exists(log_path)
  
      # Test model compilation
      package_path = os.path.join(tmpdir, "keras-tvm.tar")
      compile_str = (
          f"tvmc compile --tuning-records {log_path} "
          f"--output {package_path} {keras_simple}"
      )
      compile_args = compile_str.split(" ")[1:]
      _main(compile_args)
      assert os.path.exists(package_path)
  
      # Test running the model
      output_path = os.path.join(tmpdir, "predictions.npz")
      run_str = f"tvmc run --outputs {output_path} {package_path}"
      run_args = run_str.split(" ")[1:]
      _main(run_args)
      assert os.path.exists(output_path)
  
imports: import os
  import platform
  import pytest
  import shutil
  import logging
  import sys
  from pytest_lazyfixture import lazy_fixture
  from unittest import mock
  import tvm
  from tvm.driver.tvmc.main import _main
  from tvm.driver.tvmc.model import TVMCException
  from tvm.driver.tvmc import compiler
  from unittest.mock import MagicMock
label_desc: Use image node_id 2 for calling a global function with example usage: test_tvmc_cl_workflow_json_config(keras_simple, tmpdir_factory) without return types