thu-ml / thu-ml/TurboDiffusion
你好,为什么在尝试SLA训练时,会卡在这里
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- Python
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Description
[01-16 18:19:17|INFO|turbodiffusion/imaginaire/trainer.py:167:train] Starting training...
[01-16 18:19:17|INFO|turbodiffusion/rcm/callbacks/device_monitor.py:114:on_train_start] DeviceMonitor callback: local_dir: /workspace/code/TurboDiffusion-main/train_outputs/sla/SLA_Wan/wan2pt1_1pt3B_res480p_t2v_SLA/DeviceMonitor
[01-16 18:19:17|INFO|turbodiffusion/rcm/callbacks/every_n_draw_sla.py:122:on_train_start] Callback: local_dir: /workspace/code/TurboDiffusion-main/train_outputs/sla/SLA_Wan/wan2pt1_1pt3B_res480p_t2v_SLA/EveryNDrawSample_SLA
[01-16 18:19:17|INFO|turbodiffusion/rcm/callbacks/every_n_draw_sla.py:122:on_train_start] Callback: local_dir: /workspace/code/TurboDiffusion-main/train_outputs/sla/SLA_Wan/wan2pt1_1pt3B_res480p_t2v_SLA/EveryNDrawSample_SLA
[01-16 18:20:12|INFO|turbodiffusion/rcm/callbacks/iter_speed.py:57:on_training_step_end] Iteration 1: Hit counter: 1/5 | Loss: 0.0191 | Time: 69.76s
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
Start by reading turbodiffusion/imaginaire/trainer.py around line 167 and the callback locations shown in the log, especially device_monitor.py, every_n_draw_sla.py, and iter_speed.py. Determine whether training is progressing after Iteration 1 or actually stalled, and document the cause or the expected behavior for this SLA training run.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100