VESSL provides integrations for Keras, an interface for the TensorFlow library. You can find a complete example using Keras in our GitHub repository.


ExperimentCallback extends Keras’ callback class. Add ExperimentCallback as a callback parameter in the fit function to automatically track Keras metrics at the end of each epoch. You can also log image objects using ExperimentCallback.

data_typeUse image to log image objects
validation_dataTuple of (validation_data, validation_labels)

List of labels to get the caption from the inferred logits.

The argmax value will be used if labels are not provided.

num_imagesNumber of images to log in the validation data

Logging metrics

# Logging loss and accuracy for each epoch in Keras
from vessl.integration.keras import ExperimentCallback

..., callbacks=[ExperimentCallback()])

Logging image objects

# Logging images along with the loss and accuracy for each epoch in Keras
from vessl.keras import ExperimentCallback

        validation_data=(x_val, y_val),