Comments (4)
Hi @upupming
I see. We trained the model using 4 nodes with 8 GPUs (total 32). We noticed scaling up the pre-training to multi-node is important for convergence.
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Hi @ahatamiz, i meet the same problem ,as i pre-training the model on a single GPU with batch size 2.My input and ground-turth are shown in the image, but the output does not seem to have any resemblance to the original image, do you mean to train on multiple GPUs to have good results
x1_aug
x1_gt
x1_recon
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hI @GaoHuaZhang ,
Thanks, batch size should be a key point. We don't have the record for this training any more, but we have this
https://github.com/Project-MONAI/tutorials/tree/main/self_supervised_pretraining
which is a similar strategy pre-trianing, you could see loss curves with this tutorial.
Thanks
from research-contributions.
Hi @ahatamiz, i meet the same problem ,as i pre-training the model on a single GPU with batch size 2.My input and ground-turth are shown in the image, but the output does not seem to have any resemblance to the original image, do you mean to train on multiple GPUs to have good results
x1_aug
x1_gt
x1_recon
Have you solved the problem? I have the same problem as you
from research-contributions.
Related Issues (20)
- Training model cannot load properly HOT 2
- Add version control for the auto3dseg
- AttributeError: module 'torch._C' has no attribute '_cuda_setDevice' HOT 1
- Converting SwinUNETR to ONNX or Tensorflow
- RuntimeError: applying the transform < monai. Transforms. Spatial. Dictionary. Orientationd object at 0 x7f791cb8bfd0 >
- Problem with the number of output channels in brats data sets HOT 2
- Unable to run prostate-mri-lesion-seg on Colab HOT 6
- Unable to run the prostate-mri-lesion-seg tutorial notebook using jupyter HOT 6
- Why is there a significant difference in the maximum number of epochs required for different segmentation tasks? HOT 4
- Swin-UNETR pretraining model weights do not load into the model
- Validation
- One problem came when I was using SwinUNETR to train my own data HOT 5
- Invalid organ segmentation nii file produced from prostate_mri_lesion_seg_app
- SwinUNETR-V2
- About Test HOT 4
- about evaluation HOT 1
- About SwimUNETR Model Structure
- Unnecessary conv3 Layer Weights in DAE with MONAI v0.8.0 Leading to Compatibility Issues with v0.9.0+
- FileNotFoundError in swinunetr
- Swin-UNETR pretraining validation criterion
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