Comments (2)
Impossible to run this model on single 1080ti GPU under the default setting in the code
The training is not a problem, since the model is trained by patches. For testing, it may be a problem if test images are too large. In practice, we can use 1x1 Conv or add pooling function to resize the resolution of feature input of SOCA for more efficiency.
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However, the default patch size is set to 192. if the patch size is smaller than 192, the kernel size will be larger than the size of feature map in some SOCA module, which will bring some error when doing cuddn_conv. Besides, setting a smaller patch size, 48 for example (I am not sure if this patch size is small enough to run on single 1080ti), the performance would definitely be influenced.
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Related Issues (20)
- Why is psnr declining on my own data?
- SR result low PSNR HOT 1
- Any other way to download pre-trained model? HOT 2
- Pretrained Models on Google Drive HOT 1
- Validation set? HOT 2
- ImportError: cannot import name '_update_worker_pids' HOT 5
- Pytorch version HOT 1
- Cuda Out of memory error
- 缺少benchmark
- Why CUDA out of memory HOT 2
- How to test?
- RuntimeError: CUDNN_STATUS_MAPPING_ERROR
- ValueError: _set_worker_pids should be called only once for each _BaseDataLoaderIter. HOT 1
- AssertionError: Invalid device id
- ZeroDivisionError: division by zero HOT 1
- Why scale 8 of 48x48 is 392x392 not 384x384? HOT 1
- Paper error!! (RCAN's parameter is 15.44M, which is less than SAN 15.7M)!!! HOT 2
- How test on DIV2K?!!! Out of memory!!!
- 关于BD退化模型 HOT 5
- undefined variable 'der_sacleTrace' HOT 3
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