The eclipse from clovaai

environment and package version

Hi! May you provide the precise packages & environment version? Such as python, torch, torchvision?

delta settings are different in training and evaluation

Hi! I found delta used in training and evaluation sometimes sat different.
Such as delta in ade_ps/100_5.sh, ade_ps/100_50.sh.

May I ask why? Different delta settings would result in very different accuracy between the last training step and the evaluation.

'MaskFormer' object has no attribute 'module'

Hi! I got a error below: 'MaskFormer' object has no attribute 'module' and tried the weights from self-training step0 and which download from your page.
Do you know what's wrong is it? Or this is a version problem?
(Sorry I asked your version problem in the previous issue, but the cost for changing cuda version is too heavy to me.)

in train_inc.py L140

if self.cfg.CONT.NUM_PROMPTS > 0:
    self.model.module.copy_prompt_embed_weights()# error occur
    self.model.module.copy_mask_embed_weights()
    self.model.module.copy_no_obj_weights()
    self.model.module.copy_prompt_trans_decoder_weights()

ERROR message

[05/03 17:47:44 d2.checkpoint.detection_checkpoint]: [DetectionCheckpointer] Loading from results/ade_ss_100_step0.pth ...
[05/03 17:47:44 fvcore.common.checkpoint]: [Checkpointer] Loading from results/ade_ss_100_step0.pth ...
WARNING [05/03 17:47:44 fvcore.common.checkpoint]: Some model parameters or buffers are not found in the checkpoint:
sem_seg_head.predictor.class_embed.cls.2.layers.0.{bias, weight}
sem_seg_head.predictor.class_embed.cls.2.layers.1.{bias, weight}
sem_seg_head.predictor.class_embed.cls.2.layers.2.{bias, weight}
sem_seg_head.predictor.prompt_embed.0.0.weight
sem_seg_head.predictor.prompt_embed.0.1.weight
sem_seg_head.predictor.prompt_embed.0.2.weight
sem_seg_head.predictor.prompt_embed.0.3.weight
sem_seg_head.predictor.prompt_embed.0.4.weight
sem_seg_head.predictor.prompt_embed.0.5.weight
sem_seg_head.predictor.prompt_embed.0.6.weight
sem_seg_head.predictor.prompt_embed.0.7.weight
sem_seg_head.predictor.prompt_embed.0.8.weight
sem_seg_head.predictor.prompt_feat.0.weight
sem_seg_head.predictor.prompt_mask_embed.0.layers.0.{bias, weight}
sem_seg_head.predictor.prompt_mask_embed.0.layers.1.{bias, weight}
sem_seg_head.predictor.prompt_mask_embed.0.layers.2.{bias, weight}
Traceback (most recent call last):
  File "train_inc.py", line 782, in <module>
    launch(
  File "/home/vllab/anaconda3/envs/mask2former/lib/python3.8/site-packages/detectron2/engine/launch.py", line 84, in launch
    main_func(*args)
  File "train_inc.py", line 772, in main
    trainer.resume_or_load(resume=args.resume)
  File "train_inc.py", line 140, in resume_or_load
    self.model.module.copy_prompt_embed_weights()
  File "/home/vllab/anaconda3/envs/mask2former/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1695, in __getattr__
    raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")

Looking for the code

Thank you for your great work!
Can't wait to follow your work!
May I ask when you plan to release your code?

About training cost

Hi, thanks for your work! I want to reproduce the result and wonder the number of GPUs used in these experiments and the training time, hope you can help me!

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environment and package version

delta settings are different in training and evaluation

'MaskFormer' object has no attribute 'module'

Looking for the code

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