code: def train_lenet_gluon_save_params_api():
      model_name = "lenet_gluon_save_params_api"
      create_model_folder(model_name)
      logging.info(f"Saving files for model {model_name}")
      net = Net()
      weights = mx.initializer.Xavier(magnitude=2.57)
      net.initialize(weights, ctx=[mx.cpu(0)])
      # Prepare data
  
      test_data = mx.np.random.uniform(-1, 1, size=(20, 1, 30, 30))
      output = net(test_data)
      # print (y)
  
      mx.npx.savez(
          os.path.join(
              get_model_path(model_name), "".join([model_name, "-data"])
          ),
          **{"data": test_data},
      )
      save_inference_results(output, model_name)
      net.save(
          os.path.join(
              get_model_path(model_name),
              "".join([model_name, "-params"]),
          )
      )
  
imports: from .common import *
label_desc: Use image node_id 1 for calling a global function with example usage: train_lenet_gluon_save_params_api() without return types