code: def main():
      # wandb.init(project="tf2", sync_tensorboard=True, resume=True)
      wandb.init(sync_tensorboard=True, resume=True)
  
      wandb.config["nice"] = "So cool fun"
  
      class Logger(tf.keras.callbacks.Callback):
          def on_epoch_end(self, epoch, logs):
              time.sleep(2)
              wandb.log({"wild_metrics": logs, "interval": epoch * 10})
  
      model = tf.keras.models.Sequential()
      model.add(
          tf.keras.layers.Conv2D(
              3, 3, activation="relu", input_shape=(28, 28, 1)
          )
      )
      model.add(tf.keras.layers.Flatten())
      model.add(tf.keras.layers.Dense(10, activation="softmax"))
      model.compile(
          loss="sparse_categorical_crossentropy",
          optimizer="sgd",
          metrics=["accuracy"],
      )
  
      model.fit(
          np.ones((10, 28, 28, 1)),
          np.ones((10,)),
          epochs=17,
          validation_split=0.2,
          callbacks=[Logger(), tf.keras.callbacks.TensorBoard()],
      )
  
imports: import time
  import numpy
  import tensorflow
  import wandb
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types