Configure your training script

Your training script must be configured to writeTensorBoard logs. For existing TensorBoard users, this requires no change toyour model training code.

To configure your training script in TensorFlow 2.x, create aTensorBoard callback and set thelog_dir variable to any locationwhich can connect to Google Cloud.

The TensorBoard callback is then included in the TensorFlowmodel.fitcallbacks list.

importtensorflowastfdeftrain_tensorflow_model_with_tensorboard(log_dir):(x_train,y_train),(x_test,y_test)=tf.keras.datasets.mnist.load_data()x_train,x_test=x_train/255.0,x_test/255.0defcreate_model():returntf.keras.models.Sequential([tf.keras.layers.Flatten(input_shape=(28,28)),tf.keras.layers.Dense(512,activation="relu"),])model=create_model()model.compile(optimizer="adam",loss="sparse_categorical_crossentropy",metrics=["accuracy"])tensorboard_callback=tf.keras.callbacks.TensorBoard(log_dir=log_dir,histogram_freq=1)model.fit(x=x_train,y=y_train,epochs=5,validation_data=(x_test,y_test),callbacks=[tensorboard_callback],)

The TensorBoard logs are created in the specified directory and can beuploaded to a Vertex AI TensorBoard experiment by followingtheUpload TensorBoard Logsinstructions for uploading.

For more examples, see theTensorBoard open source docs

What's next

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Last updated 2025-12-15 UTC.