Comments (3)
endernewton
commented on June 22, 2024
Single GPU training is possible and doable for debugging. You can just comment that line (https://github.com/facebookresearch/simsiam/blob/main/main_simsiam.py#L183) so it does not raise an error.
Single GPU affects performance mainly due to batch size -- cannot fit many images into one single GPU. Otherwise if you manage to train on single GPU, let me know!
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nixczhou
commented on June 22, 2024
Just curious, small Batch Size like 64 ~ 256 does not matter for the SimSiam model , isn't it?
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dikapiliao1
commented on June 22, 2024
Can you train with a single GPU？
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Related Issues (20)
- loss question HOT 4
- Loss descent slowly HOT 1
- Checkpoints with 50 epochs HOT 1
- [Problem] problem occured when trained on custom dataset HOT 4
- difference between byol in table19 and simsiam? HOT 1
- larger batch size with linear scale does not work
- checkpoint for epoch 800
- Slow convergence with SGD linear evaluation HOT 1
- SyncBatchnorm usage in main_lincls.py HOT 2
- About the projection and prediction head dimension configs
- Loss collapse during training HOT 1
- About the shape of image[0] and image[1] HOT 1
- Pre-trained weights for SimCLR, MoCov2, BYOL, SwaV HOT 1
- The value of loss function nn.CosineSimilarity is negative HOT 1
- self.encoder.fc in builder.py
- which vector is used in experiment (the vector atfer predictor or after projection)?
- Why are training and testing so slow HOT 2
- Could not find any class folder
- Loss increasing
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