How to use Keras TensorBoard callback for grid search

Question

I\'m using the Keras TensorBoard callback. I would like to run a grid search and visualize the results of each single model in the tensor board. The problem is that all resu

Answer 1

It's easy, just save logs to separate dirs with concatenated parameters string as dir name:

Here is example using date as name of run:

from datetime import datetime

datetime_str = ('{date:%Y-%m-%d-%H:%M:%S}'.format(date=datetime.now()))
callbacks = [
    ModelCheckpoint(model_filepath, monitor='val_loss', save_best_only=True, verbose=0),
    TensorBoard(log_dir='./logs/'+datetime_str, histogram_freq=0, write_graph=True, write_images=True),
]

history = model.fit_generator(
    generator=generator.batch_generator(is_train=True),
    epochs=config.N_EPOCHS,
    steps_per_epoch=100,
    validation_data=generator.batch_generator(is_train=False),
    validation_steps=10,
    verbose=1,
    shuffle=False,
    callbacks=callbacks)