aws / aws/amazon-sagemaker-examples
chainer_sentiment_analysis.ipynb failed CI
- Dominant language
- Jupyter Notebook
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- Merged PRs (30d)
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Description
Link to the notebook:
https://github.com/aws/amazon-sagemaker-examples/blob/master/sagemaker-python-sdk/chainer_sentiment_analysis/chainer_sentiment_analysis.ipynb
Error:
---------------------------------------------------------------------------
Exception encountered at "In [2]":
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
in
----> 1 import dataset
2
3 file_paths = dataset.download_dataset("stsa.binary")
4
5 new_file_paths = dataset.get_stsa_dataset(file_paths)
/opt/ml/processing/input/dataset.py in
21
22 import numpy
---> 23 import chainer
24
25 from src.nlp_utils import transform_to_array, split_text, normalize_text, make_vocab
ModuleNotFoundError: No module named 'chainer'
Contributor guide
Research direction
Open sagemaker-python-sdk/chainer_sentiment_analysis/chainer_sentiment_analysis.ipynb and inspect the environment used by CI for cell In [2]. Reproduce the import failure and verify that the notebook's required Chainer dependency is available in that environment; done means the notebook runs past the failing cell in CI.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- 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
- 35/100