The autokeras_imdb_example.py example script demonstrates the integration of Trains into code which uses autokeras. It trains text classification networks on the Keras built-in IMDB dataset, using the autokeras TextClassifier class, and searches for the best model. It uses two TensorBoard callbacks, one for training and one for testing. Trains automatically logs everything the code sends to TensorBoard. When the script runs, it creates an experiment named
autokeras imdb example with scalars, which is associated with the
Loss and the accuracy metric per iteration which appear in RESULTS > SCALARS, along with the resource utilization plots as :monitor: machine.
Trains automatically logs TensorFlow DEFINES. They appear in CONFIGURATIONS > HYPER PARAMETERS > TF_DEFINE.
Text printed to the console for training progress, as well as all other console output, appear in RESULTS > LOG.
Model artifacts associated with the experiment appear in the experiment info panel (in the EXPERIMENTS tab), and in the model info panel (in the MODELS tab).
The experiment info panel shows model tracking, including the model name and design (in this case, no design was stored).
The model info panel contains the model details, including the model URL, framework, and snapshot locations.