Storage

ClearML automatically logs the storage of models and debug samples locally. You can also configure ClearML for the storage you use.

If your script loads other data, that data must be accessible from the machine where the script runs. If, for example, you develop a script on your local machine, and then reproduce it by executing it on a remote machine, the data must be accessible from the remote machine.

The supported storage includes:

• local and shared folders

• S3 buckets

• Google Cloud Storage

• Azure Storage

• http(s)

Configuring ClearML for artifact storage

Configure ClearML for model checkpoint (snapshot) storage in any of the following ways:

• In the configuration file, set default_output_uri.

• In code, when initializing a Task, use the output_uri parameter.

• In the ClearML Web UI, when modifying an experiment.

Configuring ClearML for debug samples storage

Configure ClearML for debug sample storage by calling the Logger.set_default_upload_destination before calling explicit reporting methods (see the explicit report examples).

Next Steps

• Learn about workers and queues.