AutoML.fit(wait=False) requires explicit logs=False

[athewsey]

Describe the bug

Calling AutoML.fit(..., wait=False) will throw an error, requiring users to explicitly add the logs=False parameter.

The documentation does technically point out that logs defaults to True and that the parameter is "only meaningful when wait is True" - which implies inconsistent combinations would be ignored, rather than triggering error.

The behaviour is inconsistent with other functions e.g. Estimator.fit() where wait=False doesn't require a separate explicit logs configuration. Seems like it's accidental rather than a deliberate choice.

To reproduce

Create a sagemaker.automl.automl.AutoML instance and call .fit() with parameter wait=False and not specifying logs parameter.

Expected behavior

The job starts and the function returns without blocking the kernel. No logs printed because we're not waiting on the job: Comparable to Estimator.fit().

Screenshots or logs

Error as below:

ValueError: Logs can only be shown if wait is set to True.
                Please either set wait to True or set logs to False.

System information
A description of your system. Please provide:

• SageMaker Python SDK version: 1.60.0
• Framework name (eg. PyTorch) or algorithm (eg. KMeans): AutoML
• Framework version: N/A
• Python version: 3.7.6
• CPU or GPU: CPU
• Custom Docker image (Y/N): N (SM Studio Py3 Data Science kernel)

Additional context

Relevant part of the documentation:

• wait (bool) – Whether the call should wait until the job completes (default: True).
• logs (bool) – Whether to show the logs produced by the job. Only meaningful when wait is True (default: True).

[laurenyu]

fixed in #1585. should be released tomorrow morning

[laurenyu]

released in https://github.com/aws/sagemaker-python-sdk/releases/tag/v1.65.0