code: def test_lstm_gluon_load_parameters_api():
      # If this code is being run on version >= 1.2.0 only then execute it,
      # since it uses save_parameters and load_parameters API
  
      if compare_versions(str(mxnet_version), "1.2.1") < 0:
          logging.warn(
              f"Found MXNet version {str(mxnet_version)} and exiting because this version does not contain save_parameters"
              " and load_parameters functions"
          )
          return
  
      model_name = "lstm_gluon_save_parameters_api"
      logging.info(
          f"Performing inference for model/API {model_name} and model"
      )
  
      for folder in get_top_level_folders_in_bucket(
          s3, model_bucket_name
      ):
          logging.info(f"Fetching files for MXNet version : {folder}")
          model_files = download_model_files_from_s3(model_name, folder)
          if len(model_files) == 0:
              logging.warn(
                  f"No training files found for {model_name} for MXNet version : {folder}"
              )
              continue
  
          data = mx.npx.load("".join([model_name, "-data"]))
          test_data = data["data"]
          # Load the model and perform inference
          loaded_model = SimpleLSTMModel()
          loaded_model.load_parameters(model_name + "-params")
          output = loaded_model(test_data)
          old_inference_results = mx.npx.load(
              model_name + "-inference"
          )["inference"]
          assert_almost_equal(
              old_inference_results.asnumpy(),
              output.asnumpy(),
              rtol=rtol_default,
              atol=atol_default,
          )
          clean_model_files(model_files, model_name)
          logging.info("=================================")
      logging.info(f"Assertion passed for model : {model_name}")
  
imports: from .common import *
label_desc: Use image node_id 3 for calling a global function with example usage: test_lstm_gluon_load_parameters_api() without return types