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 |