modelscope / modelscope/DiffSynth-Studio
oom on minimax h3
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- Python
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Description
I train h3 on 768p 10s videos with 9 reference images using parameter here:
--height 1344
--width 768
--num_frames 243 \
using 4*8h100 (84G memory), I get oom error. So I am curious about that one sample is very large, and should be splitted into different gpus with sequence parallel? I am not sure whether it supports sequence or context paralle.
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Research direction
No source file, test, or entry point is named. Start by reproducing the Minimax H3 training command with 768×1344 resolution, 243 frames, nine reference images, and four 84G H100 GPUs; then trace the H3 training entry point and its parallelism configuration. Done means the OOM cause and whether sequence or context parallelism is supported are established, with a documented fix or limitation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100