Create and manage experiment runs

Python

from typing import Optional, Union from google.cloud import aiplatform def create_experiment_run_sample( experiment_name: str, run_name: str, experiment_run_tensorboard: Optional[Union[str, aiplatform.Tensorboard]], project: str, location: str, ): aiplatform.init(experiment=experiment_name, project=project, location=location) aiplatform.start_run(run=run_name, tensorboard=experiment_run_tensorboard) 

• experiment_name: Provide the name of your experiment. You can find your list of experiments in the Google Cloud console by selecting "Experiments" in the section nav.
• run_name: Specify a run name to associate with your current session. See start_run in the Vertex AI SDK reference documentation.
• experiment_run_tensorboard: Optional. A backing TensorBoard resource to enable and store time series metrics logged to this experiment run using log_time_series_metrics.
• project: . You can find these IDs in the Google Cloud console welcome page.
• location: See List of available locations

Python

from google.cloud import aiplatform def end_experiment_run_sample( experiment_name: str, run_name: str, project: str, location: str, ): aiplatform.init(experiment=experiment_name, project=project, location=location) aiplatform.start_run(run=run_name, resume=True) aiplatform.end_run() 

• experiment_name: Provide the name of your experiment. You can find your list of experiments in the Google Cloud console by selecting "Experiments" in the section nav.
• run_name: Specify a run name.
• project: . You can find these in the Google Cloud console welcome page.
• location: See List of available locations

Python

from google.cloud import aiplatform def resume_experiment_run_sample( experiment_name: str, run_name: str, project: str, location: str, ): aiplatform.init(experiment=experiment_name, project=project, location=location) aiplatform.start_run(run=run_name, resume=True) 

• experiment_name: Provide the name of your experiment. You can find your list of experiments in the Google Cloud console by selecting "Experiments" in the section nav.
• run_name: Specify name of run that you want to resume.
• project: . You can find these in the Google Cloud console welcome page.
• location: See List of available locations

Python

from typing import Union from google.cloud import aiplatform def delete_experiment_run_sample( run_name: str, experiment: Union[str, aiplatform.Experiment], project: str, location: str, delete_backing_tensorboard_run: bool = False, ): experiment_run = aiplatform.ExperimentRun( run_name=run_name, experiment=experiment, project=project, location=location ) experiment_run.delete(delete_backing_tensorboard_run=delete_backing_tensorboard_run) 

• experiment: The name or instance of this experiment. You can find your list of experiments in the Google Cloud console by selecting "Experiments" in the section nav.
• run_name: Specify name of run that you want to delete.
• project: . You can find these in the Google Cloud console welcome page.
• location: See List of available locations
• delete_backing_tensorboard_run: Whether to delete the backing Vertex AI TensorBoard run that stores time series metrics for this run.

Python

from typing import Union from google.cloud import aiplatform def update_experiment_run_state_sample( run_name: str, experiment: Union[str, aiplatform.Experiment], project: str, location: str, state: aiplatform.gapic.Execution.State, ) -> None: experiment_run = aiplatform.ExperimentRun( run_name=run_name, experiment=experiment, project=project, location=location, ) experiment_run.update_state(state) 

• run_name: run name associated with your experiment
• experiment_name: name of your experiment. You can find your list of experiments in the Google Cloud console by selecting Experiments in the section nav.
• project: . You can find these Project IDs in the Google Cloud console welcome page.
• location: See List of available locations
• state: Possible values for state, which shows up as "status" in the Google Cloud console, are:
  • aiplatform.gapic.Execution.State.CACHED
  • aiplatform.gapic.Execution.State.CANCELLED
  • aiplatform.gapic.Execution.State.COMPLETE
  • aiplatform.gapic.Execution.State.FAILED
  • aiplatform.gapic.Execution.State.NEW
  • aiplatform.gapic.Execution.State.RUNNING