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)

Functional api

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) -> 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.

Param	Type	Description	Default Value
uri	String	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	x

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

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

Param	Type	Description	Default Value
key	String	Parameter name.	x
value	String	Parameter value.	x

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

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

Param	Type	Description	Default Value
key	String	Metric name.	x
value	Float	Metric value.	x
step	Integer	A single integer step at which to log the specified Metrics.	0

submarine.save_model(model_type, model, registered_model_name, input_dim, output_dim) -> None

Save a model into the minio pod.

Param	Type	Description	Default Value
model_type	String	The type of model. Only support pytorch and tensorflow.	x
model	Object	Model artifact.	x
registered_model_name	String	If it is not None, the model will be registered into the model registry with this name.	None
input_dim	List<Integer>	The input dimension of the model.	None
output_dim	List<Integer>	The output dimension of the model.	None