code: def get_functional_model():
      inputs = tf.keras.layers.Input(shape=(28, 28, 1))
      x = tf.keras.layers.Conv2D(3, 3, activation="relu")(inputs)
      x = tf.keras.layers.Flatten()(x)
      outputs = tf.keras.layers.Dense(10, activation="softmax")(x)
  
      model = tf.keras.models.Model(inputs, outputs)
      model.compile(
          optimizer="sgd",
          loss="sparse_categorical_crossentropy",
          metrics=["accuracy"],
      )
  
      return model
  
imports: import numpy
  import tensorflow
  import wandb
  from wandb.keras import WandbCallback
label_desc: Use image node_id 1 for calling a global function with example usage: get_functional_model() and returns: model