How to get current run_id inside of mlflow.start_run()?

mlflow.active_run() returns nothing so I can't just usecurrent_rui_id = mlflow.active_run().info.run_id

I have to get run_id inside of this construction for being able to continue logging parameters, metrics and artifacts inside of another block but for the same model:

with mlflow.start_run(run_name="test_ololo"): """ fitting a model here ... """ for name, val in metrics: mlflow.log_metric(name, np.float(val)) # Log our parameters into mlflow for k, v in params.items(): mlflow.log_param(key=k, value=v) pytorch.log_model(learn.model, f'model') mlflow.log_artifact('./outputs/fig.jpg')

I have to get current run_id to continue training inside the same run

with mlflow.start_run(run_id="215d3a71925a4709a9b694c45012988a"): """ fit again log_metrics """ pytorch.log_model(learn.model, f'model') mlflow.log_artifact('./outputs/fig2.jpg')

3 Answers

with mlflow.start_run(run_name="test_ololo") as run: run_id = run.info.run_id

You can try this code snippet:

import mlflow
mlflow.start_run()
run = mlflow.active_run()
print("Active run_id: {}".format(run.info.run_id))
mlflow.end_run()

The above should work and is in fact the best way to get a hold of active run inside of the with mlflow.start_run() block.

For completeness, mlflow.active_run().info.run_id will also work if executed inside of the with block. The with block will end mlflow run on exit, so there is no active run once the block exited.