aws / aws/amazon-sagemaker-examples
rl_cartpole_ray_gymEnv.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_cartpole_ray/rl_cartpole_ray_gymEnv.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
Inspect reinforcement_learning/rl_cartpole_ray/rl_cartpole_ray_gymEnv.ipynb, starting with the In [1] import that adds "common" and then imports misc. Reproduce the CI failure and verify the notebook's setup makes misc available; done means In [1] runs without ModuleNotFoundError and the notebook passes CI.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, jupyter-notebook, python
- Domain
- machine-learning, testing
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100