code: def test_keras_image_output(
      dummy_model, dummy_data, relay_server, wandb_init
  ):
      with relay_server() as relay:
          run = wandb_init()
          dummy_model.fit(
              *dummy_data,
              epochs=2,
              batch_size=36,
              validation_data=dummy_data,
              callbacks=[
                  WandbCallback(
                      input_type="image",
                      predictions=10,
                      validation_data=dummy_data,
                  ),
              ],
          )
          run.finish()
  
      history = relay.context.get_run_history(run.id)
      assert history["examples"][0]["count"] == 30
      assert history["examples"][0]["height"] == 10
  
imports: import glob
  import json
  import os
  import pytest
  import tensorflow
  from tensorflow.keras import backend
  from tensorflow.keras.layers import Dense, Flatten, Reshape
  from tensorflow.keras.models import Sequential
  from wandb.keras import WandbCallback
label_desc: Use image node_id 11 for calling a global function with example usage: test_keras_image_output(dummy_model, dummy_data, relay_server, wandb_init) without return types