code: def get_model():
      m = tf.keras.Sequential()
      m.add(
          tf.keras.layers.Conv2D(
              3, 3, activation="relu", input_shape=(28, 28, 1)
          )
      )
      m.add(tf.keras.layers.Flatten())
      m.add(tf.keras.layers.Dense(10, activation="softmax"))
      return m
  
imports: import numpy
  import tensorflow
  import wandb
  from wandb.keras import WandbModelCheckpoint
label_desc: Use image node_id 1 for calling a global function with example usage: get_model() and returns: m