Manually create a SigOpt Run

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If the CLI or Jupyter Notebook integration isn't right for your use case then you might want to create Runs and Experiments directly with the SigOpt Python Client. To create a Run, just add the following to your code:
run = sigopt.create_run()
With this Run object you can get and set parameter values and log attributes in a similar way as you would when using the CLI:
run.params.learning_rate = 0.1
accuracy = train_my_model(learning_rate=run.params.learning_rate)
run.log_metric("accuracy", accuracy)
Finally, end the Run:
run.end()
For convenience, you can use a Python context manager to end the Run automatically, including when your code raises an exception:
with sigopt.create_run() as run:
    run.params.learning_rate = 0.1
    accuracy = train_my_model(learning_rate=sigopt.params.learning_rate)
    run.log_metric("accuracy", accuracy)
When using an instance of a Run, all client calls can be applied to the instance as seen above.

API Reference

Tracking a Run

Last modified 3mo ago

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