code: def model_creator(config):
      import tensorflow as tf
  
      model = tf.keras.Sequential(
          [
              tf.keras.layers.Flatten(input_shape=(224, 224, 3)),
              tf.keras.layers.Dense(64, activation="relu"),
              tf.keras.layers.Dense(2),
          ]
      )
      model.compile(
          optimizer="adam",
          loss=tf.keras.losses.SparseCategoricalCrossentropy(
              from_logits=True
          ),
          metrics=["accuracy"],
      )
      return model
  
file_path: analytics-zoo/pyzoo/test/zoo/orca/data/test_read_parquet_images.py
imports: import tempfile
  import shutil
  import pytest
  from unittest import TestCase
  import os
  from zoo.orca.data.image.parquet_dataset import ParquetDataset, read_parquet
  from zoo.orca.data.image.utils import DType, FeatureType, SchemaField
  import tensorflow
  from zoo.ray import RayContext
label_desc: Use image node_id 3 for calling a global function with example usage: model_creator(config) and returns: model