What do if the DeepChem install isn't working for me?
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- Dominant language
- Python
- Stars
- 322
- Forks
- 155
- PR merge metrics
- No merged PRs in 30d
Description
The TensorFlow for Deep Learning book uses DeepChem (https://deepchem.io/) for examples in Chapters 4, 5, and 8. While DeepChem installations work fine for most users, there are some users for whom DeepChem causes issues. If you're running into these issues, here are some steps we suggest:
- Try asking a question on the DeepChem [gitter chatroom](https://gitter.im/deepchem/Lobby). Please make sure to provide your OS, Python details, and if relevant a stack trace so we can help debug.
- The Gitter can get crowded. If your question has not been answered, please raise an issue on the [DeepChem GitHub ](https://github.com/deepchem/deepchem). Please include all relevant information and we will try to help debug.
- Only Chapters 4, 5, 8 in the TensorFlow book use DeepChem. You should be able to proceed while we help you work through any potential DeepChem issues.
We are working on putting together example code which doesn't rely on DeepChem for these chapters. We sincerely apologize if you've been facing difficulties and hope to help you find a quick resolution.
We will use this issue to track progress.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No repository file or test is named. Start by reviewing the DeepChem-dependent examples in Chapters 4, 5, and 8, then clarify whether the work is support triage or creating alternatives that do not rely on DeepChem. Done means the affected examples have a documented resolution or a working non-DeepChem path.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100