Driverless AI Logs

This section describes how to access Driverless AI logs and includes information on which logs to send in the event of a failure.

Accessing Driverless AI Logs

Driverless AI provides a number of logs that can be retrieved while visualizing datasets, while an experiment is running, and after an experiment is completed.

While Visualizing Datasets

When running Autovisualization, you can access the Autoviz logs by clicking the Display Logs button on the Visualize Datasets page.

Display Logs button
Autoviz logging

This page presents logs created while the dataset visualization was being performed. You can download the vis-data-server.log file by clicking the Download Logs button on this page. This file can be used to troubleshoot any issues encountered during dataset visualization.

While an Experiment is Running

While the experiment is running, you can access the logs by clicking on the Log button on the experiment screen. The Log button can be found in the CPU/Memory section.

Log button

Clicking on the Log button will present the experiment logs in real time. You can download these logs by clicking on the Download Logs button in the upper right corner.

Log when experiment is running

Only the h2oai_experiment.log can be downloaded while the experiment is running (for example: h2oai_experiment_tobosoru.log). It will have the same information as the logs being presented in real time on the screen.

For troubleshooting purposes, it is best to view the complete h2oai_experiment.log (or h2oai_experiment_anonymized.log). This will be available after the experiment finishes, as described in the next section.

After an Experiment has Finished

If the experiment has finished, you can download the logs by clicking on the Download Logs button at the center of the experiment screen.

Download Logs button

This will download a zip file which includes the following logs:

  • h2oai_experiment.log: This is the log corresponding to the experiment.
  • h2oai_experiment_anonymized.log: This is the log corresponding to the experiment where all data in the log is anonymized.
  • h2oai_server.log: Contains the logs for all experiments and all users.
  • h2oai_server_anonymized.log: Contains the logs for all experiments and all users where all data in the log is anonymized.
  • h2o.log: This is the log corresponding to H2O-3. (H2O-3 is used internally for parts of Driverless AI.)

For troubleshooting, it is best to view the h2oai_experiment.log or h2oai_experiment_anonymized.log.

The following additional information about your particular experiment will also be included in the zip file:

  • tuning_leaderboard.txt: The results of the parameter tuning stage. This contains the model parameters investigated and their performance.
  • gene_summary.txt: A summary of the feature transformations available for each gene over the feature engineering iterations
  • features.txt: The features used in the final Driverless AI model along with feature importance and feature description
  • details folder: Contains standard streams for each of the subprocesses performed by Driverless AI. This information is for debugging purposes.
  • contrib folder: Contains information about custom recipes used during the experiment.

During Model Interpretation

Driverless AI allows you to view and download Python and/or Java logs while MLI is running. Note that these logs are not available for time-series experiments.

MLI runtime logs
  • The Display MLI Python Logs button allows you to view or download the Python log for the model interpretation. The downloaded file is named h2oai_experiment_{mli_key}.log.
  • The Display MLI Java Logs button allows you to view or download the Java log for the model interpretation. The downloaded file is named mli_experiment_{mli_key}.log.

After Model Interpretation

You can view an MLI log for completed model interpretations by selecting the Download MLI Logs link on the MLI page.

Download MLI Logs button

This will download a zip file which includes the following logs:

  • h2oai_experiment_{mli_key}.log: This is the log corresponding to the model interpretation.
  • h2oai_experiment_{mli_key}_anonymized.log: This is the log corresponding to the model interpretation where all data in the log is anonymized.
  • mli_experiment_{mli_key}.log: This is the Java log corresponding to the model interpretation.

This file can be used to view logging information for successful interpretations. If MLI fails, then those logs are in ./tmp/h2oai_experiment_{mli_key}.log, ./tmp/h2oai_experiment_{mli_key}_anonymized.log, and ./tmp/mli_experiment_{mli_key}.log.

Sending Logs to H2O

This section describes the logs to send in the event of failures when running Driverless AI.

Dataset Failures

  • Adding Datasets: If a dataset fails to import, a message on the screen should provide the reason for the failure. The logs to send are available in the Driverless AI ./tmp folder.
  • Dataset Details: If a failure occurs when attempting to view Dataset Details, the logs to send are available in the Driverless AI ./tmp folder.
  • Autovisualization: If a failure occurs when attempting to Visualize Datasets, a message on the screen should provide a reason for the failure. The logs to send are available in the Driverless AI ./tmp folder.

Experiments

  • While Running an Experiment: As indicated previously, a Log button is available on the Experiment page. Clicking on the Log button will present the experiment logs in real time. You can download these logs by clicking on the Download Logs button in the upper right corner. You can also retrieve the h2oai_experiment.log for the corresponding experiment in the Driverless AI ./tmp folder.

MLI

  • During Model Interpretation: If a failure occurs during model interpretation, then the logs to send are ./tmp/h2oai_experiment_{mli_key}.log and ./tmp/h2oai_experiment_{mli_key}_anonymized.log.

Custom Recipes

  • After Running an Experiment: If a Custom Recipe is producing errors, the entire zip file obtained by clicking on the Download Logs button can be sent for troubleshooting. Please note that these files may contain information that is not anonymized.