finetuner.run module#

class finetuner.run.Run(client, name, experiment_name, config, created_at, description='')[source]#

Bases: object

Class for a run.

Parameters

client (FinetunerV1Client) – Client object for sending api requests.
name (str) – Name of the run.
experiment_name (str) – Name of the experiment.
config (dict) – Configuration for the run.
created_at (str) – Creation time of the run.
description (str) – Optional description of the run.

property name: str#

Return type: str

property config: dict#

Return type: dict

status()[source]#

Run status.

Return type: dict
Returns: A string representing the run status.

logs()[source]#

Check the run logs.

Return type: str
Returns: A string dump of the run logs.

stream_logs(interval=5)[source]#

Stream the run logs.

Parameters: interval (int) – The time interval to sync the status of finetuner Run.
Yield: An iterators keep stream the logs from server.
Return type: Iterator[str]

save_artifact(directory='artifacts/')[source]#

Save artifact if the run is finished.

Parameters: directory (str) – Directory where the artifact will be stored.
Return type: str
Returns: A string object that indicates the download path.

property artifact_id#

Get artifact id from the run.

An artifact in finetuner contains fine-tuned model and its metadata. Such as preprocessing function, collate function. This id could be useful if you want to directly pull the artifact from the cloud storage, such as using FinetunerExecutor.

Returns: Artifact id as string object.