aws / aws/amazon-sagemaker-examples
rl_unity_ray.ipynb failed CI
- 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/reinforcement_learning/rl_unity_ray/rl_unity_ray.ipynb
Error:
---------------------------------------------------------------------------
Exception encountered at "In [1]":
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
in
11 from time import gmtime, strftime
12 sys.path.append("common")
---> 13 from misc import get_execution_role, wait_for_s3_object
14 from docker_utils import build_and_push_docker_image
15 from sagemaker.rl import RLEstimator, RLToolkit, RLFramework
ModuleNotFoundError: No module named 'misc'
Contributor guide
Research direction
Open reinforcement_learning/rl_unity_ray/rl_unity_ray.ipynb and inspect the sys.path setup around the misc import in the first cell. Run the notebook or its CI check to reproduce the ModuleNotFoundError. Done means the notebook gets past the first cell without the missing-module error and CI succeeds.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, jupyter-notebook, python
- Domain
- ci-cd, machine-learning
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100