aws / aws/amazon-sagemaker-examples

improving_industrial_workplace_safety.ipynb failed CI

Open
#2,285 0 comments 0 reactions 0 assignees View on GitHub
Dominant language
Jupyter Notebook
Stars
11k
Forks
7k
Avg merge
8h 29m
Merged PRs (30d)
8

Description

Link to the notebook:
https://github.com/aws/amazon-sagemaker-examples/blob/master/aws_marketplace/using_model_packages/improving_industrial_workplace_safety/improving_industrial_workplace_safety.ipynb

Error:

---------------------------------------------------------------------------
Exception encountered at "In [10]":
---------------------------------------------------------------------------
ClientError Traceback (most recent call last)
in
8
9 #Deploy the model.
---> 10 predictor_construction_worker_detection = construction_worker_detection_model.deploy(1, 'ml.c5.xlarge', endpoint_name=construction_worker_detection_model_name)

/opt/conda/lib/python3.7/site-packages/sagemaker/model.py in deploy(self, initial_instance_count, instance_type, serializer, deserializer, accelerator_type, endpoint_name, tags, kms_key, wait, data_capture_config, **kwargs)
761 self._base_name = "-".join((self._base_name, compiled_model_suffix))
762
--> 763 self._create

[...]

ClientError: An error occurred (ValidationException) when calling the CreateModel operation: Caller is not subscribed to the marketplace offering.

Contributor guide

Open the contributing guide

Research direction

Start with aws_marketplace/using_model_packages/improving_industrial_workplace_safety/improving_industrial_workplace_safety.ipynb and inspect cell 10, where deployment fails during the SageMaker CreateModel operation. Re-run the notebook to confirm the ValidationException and determine what change is needed for the marketplace model deployment to complete successfully.

Written by the indexing model from the issue text.

Assessment

Tech stack
aws, jupyter-notebook
Domain
cloud, machine-learning
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.