aws / aws/amazon-sagemaker-examples
rl_portfolio_management_coach_customEnv.ipynb failed CI
- Dominant language
- Jupyter Notebook
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- 11k
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- 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_portfolio_management_coach_customEnv/rl_portfolio_management_coach_customEnv.ipynb
Error:
---------------------------------------------------------------------------
Exception encountered at "In [1]":
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
in
10 from time import gmtime, strftime
11 sys.path.append("common")
---> 12 from misc import get_execution_role, wait_for_s3_object
13 from sagemaker.rl import RLEstimator, RLToolkit, RLFramework
ModuleNotFoundError: No module named 'misc'
Contributor guide
Research direction
Open reinforcement_learning/rl_portfolio_management_coach_customEnv/rl_portfolio_management_coach_customEnv.ipynb and run its first cell in the CI environment. Check how the notebook adds the common path and resolves misc.get_execution_role and wait_for_s3_object; done means the notebook passes CI without the ModuleNotFoundError.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, jupyter-notebook, python
- Domain
- cloud, machine-learning, testing
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100