[Question] How do I retrieve the outputs of each trials of a sweep job?

• Package Name: azure.ai.ml.sweep
• Package Version: 1.0.0
• Operating System: Ubuntu
• Python Version: py38

I am running a Sweep job successfully on AzML and now I want to retrieve the outputs of each trials for further exploration. Thing is reading the both the doc and the code I can’t see how I am supposed to retrieve them. The SweepJob class does not seem to expose the run like hyperdrive used to.

I would love if any one could give me directions ❤️

[pievalentin]

Ok I guess I won’t be able to have the same behavior as the sdk v1. Here is the closest thing I have for retrieving the ouput of a single trial of a sweep job.

trial = next(ml_client.jobs.list(parent_job_name=returned_sweep_job.name))
client = mlflow.MlflowClient()
finished_mlflow_run = client.get_run(trial.name)
client.list_artifacts(finished_mlflow_run.info.run_id)

This should output:

$ [<FileInfo: file_size=-1, is_dir=True, path='outputs'>, <FileInfo: file_size=-1, is_dir=True, path='system_logs'>, <FileInfo: file_size=-1, is_dir=True, path='user_logs'>]

Now you can download the output directory.

mlflow.artifacts.download_artifacts(run_id=finished_mlflow_run.info.run_id, artifact_path ="outputs",dst_path='sweep_trial_outputs')

I am not sure if the mlflow API enable file renaming.

Hope this help someone in the future

[luigiw]

@pievalentin thx for sharing your solution. Another thing you can try is ml_client.jobs.download(name=trial.name)