modelscope / modelscope/DiffSynth-Studio
QwenImage的训练是否支持多卡多机
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- Dominant language
- Python
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Description
if [ $WORLD_SIZE -gt 1 ];
then
GPUS_PER_NODE=8
NNODES=$WORLD_SIZE
NODE_RANK=$RANK
MASTER_ADDR=$MASTER_ADDR
MASTER_PORT=$MASTER_PORT
else
GPUS_PER_NODE=8
NNODES=1
NODE_RANK=0
MASTER_ADDR=localhost
MASTER_PORT=6003
fi
DISTRIBUTED_ARGS="
--num_processes $((GPUS_PER_NODE * NNODES)) \
--num_machines $NNODES \
--machine_rank $NODE_RANK \
--main_process_ip $MASTER_ADDR \
--main_process_port $MASTER_PORT
"
QwenImage的训练代码是否支持使用多卡多机训练，我这边运行发现两组卡之间没有通信
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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 file, test, or training entry point is named. Start by locating the QwenImage training entry point and tracing how the shown WORLD_SIZE, RANK, and distributed arguments are consumed. Done means establishing whether multi-node communication is supported and reproducing or clearly documenting the observed behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- distributed-systems, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100