Add describe_transform_job() to the SageMaker Session class

[alex23lemm]

Is your feature request related to a problem? Please describe.
A SageMaker Session object comes with the following two methods which allow me to retrieve the status of training and AutoML jobs: describe_training_job(), describe_auto_ml_job(). Example:

import sagemaker

session = sagemaker.Session()
session.describe_training_job("[YOUR_JOB_NAME]")["TrainingJobStatus"]

However, if I like to get the status of a batch transform job (like, e.g., a batch interence job) in the same workflow, I need to create an extra low-level SageMaker client using boto3:

import boto3

sm = boto3.client("sagemaker")
sm.describe_transform_job(TransformJobName = "[YOUR_JOB_NAME]")["TransformJobStatus"]

Describe the solution you'd like
Even though the above workflow works it could become much more concise and smoother by adding a describe_transform_job() method to the SageMaker Session class. This would eliminate the need to use the extra low-level SageMaker client in the same workflow.

[laurenyu]

thanks for the feature request! this was just addressed in #1507, and should be released tomorrow

[alex23lemm]

Thanks @laurenyu for the feedback and for adding the request so quickly to the next release!

[laurenyu]

this has now been released in v1.58.4. thanks to @ChuyangDeng for jumping on the implementation so quickly :)