deepspeedai / deepspeedai/DeepSpeed
DeepSpeed initialization with GNN-like model
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 43.1k
- Forks
- 5k
- Avg merge
- 4d 15h
- Merged PRs (30d)
- 112
Description
My code is quite similar to some GNN structure : NN_output = graph.forward(NN_input, types="f")
So, outputs = model_engine(inputs) seems does not really fit in my case ? args also does not follow such code styling.
Any idea ?
Contributor guide
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
Start by comparing the linked gdas.py graph.forward(...) call with DeepSpeedExamples/cifar/cifar10_deepspeed.py at the model_engine(inputs) entry point, including how args are passed. The issue needs a defined initialization approach for this GNN-like model and a clear validation case before implementation can be considered done.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- distributed-systems, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100