Comments (5)
Akhiladdh
commented on August 16, 2024
I want to use multiple GPUs where can i configure those details?
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arnoweng
commented on August 16, 2024
@Akhiladdh The code can be directly used for training on multiple GPUs. You just need to specify available GPU IDs (e.g. CUDA_VISIBLE_DEVICES=0,1,2,3 python model.py).
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Akhiladdh
commented on August 16, 2024
@arnoweng Thank you so much. Can you add details about how to retrain this?
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arnoweng
commented on August 16, 2024
@Akhiladdh We followed the training strategy described in the official paper. Sorry the training code is not available yet.
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Akhiladdh
commented on August 16, 2024
Thank you!
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Related Issues (20)
- what torchvision version? HOT 1
- Tencrop on test images & preprocessing imbalanced data HOT 2
- Broken Pipeline error HOT 1
- model.load_state_dict(checkpoint['state_dict']) error with pytorch 0.4.0 HOT 10
- RuntimeError: CUDA Error: out of memory HOT 11
- where can i get the pretrained model?
- Unable to run the model on CPU
- cannot be unzipped HOT 1
- FPGA Development
- Low AUROC HOT 6
- can you share pre trained model
- I have an error with the first line of the code. the error is about 'tuple' object is not callable HOT 1
- How to Cite?
- Code to make Class Activation Maps?
- Replication having probelm.
- torch._C._cuda_init() RuntimeError: The NVIDIA driver on your system is too old (found version 10020)
- isn't the training labels should be 15 (14 disease labels+ No Findings) instead of 14?
- How long will it take for training?
- 协议声明
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