code: def test_sync_tensorboard(relay_server, wandb_init):
      with relay_server() as relay:
          run = wandb_init(sync_tensorboard=True)
  
          mnist = tf.keras.datasets.mnist
  
          (x_train, y_train), (x_test, y_test) = mnist.load_data()
          x_train, x_test = x_train / 255.0, x_test / 255.0
  
          model = create_model()
          model.compile(
              optimizer="adam",
              loss="sparse_categorical_crossentropy",
              metrics=["accuracy"],
          )
  
          tensorboard_callback = tf.keras.callbacks.TensorBoard(
              histogram_freq=1
          )
  
          model.fit(
              x=x_train,
              y=y_train,
              # epochs=5,
              epochs=1,
              validation_data=(x_test, y_test),
              callbacks=[tensorboard_callback],
          )
  
          run.finish()
  
          uploaded_files = relay.context.get_run_uploaded_files(run.id)
          print(uploaded_files)
          assert any("events.out.tfevents" in f for f in uploaded_files)
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_sync_tensorboard(relay_server, wandb_init) without return types