Comments (2)
I'm sure that the reason is the model is wrapped by Accelerate. You can use self.model.module.has_multiscale_discrs or self.unwrapped_model.has_multiscale_discrs to solve this issue. And I also find many bugs on multi-GPUs training and validation, and I'm fix these issues. If I successfully run the code for multiple GPUs, and the author does not mind, I will share these codes with the author. @lucidrains
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@Ted-developer thanks for raising this issue
it is a quirk with accelerate library and it being wrapped with DDP, as Du Yao noted. i put in a fix for all the places where i think there should be unwrapping @Du-Yao def welcome a PR from you if you spot any others missing!
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Related Issues (20)
- Large scale training HOT 17
- Running multi-gpu hangs after first step HOT 9
- Is there any requirement on the training images? HOT 3
- weights HOT 1
- Unsuccessful image reconstruction HOT 3
- expired discord invitation HOT 3
- pretrained weights
- Pixelated image reconstruction HOT 7
- ‘video_contains_first_frame’ in encoder HOT 1
- recon images is black HOT 9
- Question about casual 3d cnn HOT 1
- The configuration of training
- Is there anyone success to train this model? HOT 27
- Running multi-gpu training HOT 5
- About training steps and correctness. HOT 3
- Error while loading the states of optimizer in Trainer - def load(self, path)
- Is there any pretrained weights for debug? HOT 1
- About training speed.
- Why is magvitv2 different from the description in the paper? Am I understanding it wrong? HOT 7
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