microsoft / microsoft/onnxruntime
[Feature Request] expose `unidirectional` (causal) attribute of GQA
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- Dominant language
- C++
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Description
Describe the feature request
We have a unidirectional attribute in MHA, but it is missing in GQA because most LLMs are causal. Transformer-based Text-to-Image models, on the other hand, are not causal. We should expose this attribute in GQA to help facilitate the deployment of Text-to-Image models.
Describe scenario use case
Text-to-Image generation models (like Stable Diffusion 3) require attention implemented with causal=False.
PR
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Research direction
Start by reviewing how the existing MHA unidirectional attribute is represented and how GQA attention is implemented, then inspect PR #23412. Done means GQA exposes the attribute and supports causal=False for Transformer-based text-to-image models such as Stable Diffusion 3.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100