Keras: use Tensorboard with train_on_batch()

Question

For the keras functions fit() and fit_generator() there is the possibility of tensorboard visualization by passing a keras.callbacks.TensorBoard object to the functions. For the train_on_batch() function there obviously are no callback available. Are there other options in keras to create a Tensorboard in this case?

Answer 1

A possible way to create the TensorBoard callback, and drive it manually:

# This example shows how to use keras TensorBoard callback # with model.train_on_batch  import tensorflow.keras as keras  # Setup the model model = keras.models.Sequential() model.add(...) # Add your layers model.compile(...) # Compile as usual  batch_size=256  # Create the TensorBoard callback, # which we will drive manually tensorboard = keras.callbacks.TensorBoard(   log_dir='/tmp/my_tf_logs',   histogram_freq=0,   batch_size=batch_size,   write_graph=True,   write_grads=True ) tensorboard.set_model(model)  # Transform train_on_batch return value # to dict expected by on_batch_end callback def named_logs(model, logs):   result = {}   for l in zip(model.metrics_names, logs):     result[l[0]] = l[1]   return result  # Run training batches, notify tensorboard at the end of each epoch for batch_id in range(1000):   x_train,y_train = create_training_data(batch_size)   logs = model.train_on_batch(x_train, y_train)   tensorboard.on_epoch_end(batch_id, named_logs(model, logs))  tensorboard.on_train_end(None) 

Answer 2

I think that currently, the only option is to use TensorFlow code. In this stackoverflow answer I found a way to create a TensorBoard log manually.
Thus a code sample with the Keras train_on_batch() could look like this:

# before training init writer (for tensorboard log) / model writer = tf.summary.FileWriter(...) model = ...  # train model loss = model.train_on_batch(...) summary = tf.Summary(value=[tf.Summary.Value(tag="loss",                                               simple_value=value), ]) writer.add_summary(summary) 

Note: For this example in TensorBoard you have to choose Horizontal Axis "RELATIVE" as no step is passed to the summary.