Tracking

It helps developers use submarine's internal data caching, data exchange, and task tracking capabilities to more efficiently improve the development and execution of machine learning productivity

• Allow data scientist to track distributed ML experiment
• Support store ML parameters and metrics in Submarine-server
• Support hdfs, S3 and mysql (Currently we only support mysql)

Functions

submarine.get_tracking_uri() -> str

Get the tracking URI. If none has been specified, check the environmental variables. If uri is still none, return the default submarine jdbc url.

Returns

• The tracking URI.

submarine.set_tracking_uri(uri: str) -> None

set the tracking URI. You can also set the SUBMARINE_TRACKING_URI environment variable to have Submarine find a URI from there. The URI should be database connection string.

Parameters

• uri - Submarine record data to Mysql server. The database URL is expected in the format <dialect>+<driver>://<username>:<password>@<host>:<port>/<database>. By default it's mysql+pymysql://submarine:password@submarine-database:3306/submarine. More detail : SQLAlchemy docs

submarine.log_param(key: str, value: str) -> None

log a single key-value parameter. The key and value are both strings.

Parameters

• key - Parameter name.
• value - Parameter value.

submarine.log_metric(key: str, value: float, step=0) -> None

log a single key-value metric. The value must always be a number.

Parameters

• key - Metric name.
• value - Metric value.
• step - A single integer step at which to log the specified Metrics, by default it's 0.