pretrained_model_labeling_tutorial.ipynb failed CI

Link to the notebook:
https://github.com/aws/amazon-sagemaker-examples/blob/master/ground_truth_labeling_jobs/pretrained_model/pretrained_model_labeling_tutorial.ipynb

Error:

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Exception encountered at "In [2]":
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ParamValidationError Traceback (most recent call last)
in
3 region = boto3.session.Session().region_name
4 s3 = boto3.client('s3')
----> 5 bucket_region = s3.head_bucket(Bucket=BUCKET)['ResponseMetadata']['HTTPHeaders']['x-amz-bucket-region']
6 assert bucket_region == region, "Your S3 bucket {} and this notebook need to be in the same region.".format(BUCKET)
7

/opt/conda/lib/python3.7/site-packages/boto

[...]

Invalid bucket name "<< YOUR S3 BUCKET NAME >>": Bucket name must match the regex "^[a-zA-Z0-9.\-_]{1,255}$" or be an ARN matching the regex "^arn:(aws).*:s3:[a-z\-0-9]+:[0-9]{12}:accesspoint[/:][a-zA-Z0-9\-]{1,63}$|^arn:(aws).*:s3-outposts:[a-z\-0-9]+:[0-9]{12}:outpost[/:][a-zA-Z0-9\-]{1,63}[/:]accesspoint[/:][a-zA-Z0-9\-]{1,63}$"

Open ground_truth_labeling_jobs/pretrained_model/pretrained_model_labeling_tutorial.ipynb and inspect cell In [2], starting with the failing s3.head_bucket call and its bucket-region assertion. Reproduce the reported CI failure, then verify that the notebook reaches the next step without the invalid bucket-name error and that CI passes.

Written by the indexing model from the issue text.