Comments (1)
I do not know you set the norm pix loss is true or false , when you make pretraining. If you want to generate the image like original image , you should set norm pix loss to false ( remove the --norm_pix_loss) when you make pretraining or fine-tuning.
it will close the norm for patch of target tensor.
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Related Issues (20)
- param_groups_lrd for layer decay HOT 1
- Loss is considerably worse on custom data set with different mean and standard deviation HOT 3
- Error in loading pretrained weight for 'mae_vit_base_patch16' HOT 2
- About the gan-loss HOT 2
- patchify and unpatchify HOT 1
- I found both LLAMA and MAE used smaller beta2 in ADAMW optimizer during pre-training. Is that any intuition behind such setting? HOT 1
- How to obtain the reconstructed image for inference and masked
- model.fc_norm is not trained in linear probing
- visualization attention map.
- Could you provide the pretrained checkpoints of both encoder and decoder in MAE? HOT 2
- Is the training procedure result normal? Masked regions do not improve and appear to be random noise. HOT 2
- Two different checkpoints for each ViT type HOT 5
- Code: Compatible to any channels for function patchify and unpatchify HOT 2
- collab notebook error HOT 2
- How to obtain the complete reconstructed image?
- Can run interactive visualization demo with GPU?
- 训练的代码用最新的timm跑不通
- Reconstruction using normalized pixel values to get unnormalized pixel values?
- 不匹配 HOT 1
- Bug in `random_masking`?
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