TensorFlow / Keras

You can use NeptuneHandler to capture model training metadata when using TensorFlow with Keras.

You can find detailed information on how to install and use the integration in the user guide.

NeptuneCallback

Captures model training metadata and logs them to Neptune.

Goes over the last_metrics and smooth_loss after each batch and epoch and logs them to Neptune.

You need to have Keras or TensorFlow 2 installed on your computer to use this module.

Parameters

run

(Run) - An existing run reference (as returned by neptune.init()).

base_namespace

(str, optional, default is None) - Namespace under which all metadata logged by the NeptuneCallback will be stored.

Examples

# Create run
import neptune.new as neptune
run = neptune.init(project="WORKSPACE/PROJECT")
# Instantiate the callback and pass
# it to callbacks argument of model.fit()
from neptune.new.integrations.tensorflow_keras import NeptuneCallback
neptune_callback = NeptuneCallback(run=run)
model.fit(x_train, y_train,
callbacks=[neptune_callback])