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Error while applying your model #24
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Thank you for your question. Could you please let me know the shape of the input feature you feed into the model? I am not sure if you |
In this repo, we provided the MATLAB code for preprocessing. If you prefer to use Python, please refer to |
torch.Size([60, 750]) Please find my notebook file what i am doing. How can i connect with you? email id? |
@yzyouzhang Also i am not able to train the model from scratch , it give me error: RuntimeError: CUDA out of memory. Tried to allocate 60.00 MiB (GPU 0; 6.00 GiB total capacity; 4.49 GiB already allocated; 0 bytes free; 4.52 GiB reserved in total by PyTorch) |
The feature size should be [B, 1, 60, 750]. |
In my case, I use RTX 1080 Ti 11GB. I can load with batch size 64. So I think batch size 2 should be totally OK for your device. Have you made sure there are no other processes occupying the GPU memory? |
@yzyouzhang how can i convert my feature size (60,750) to [B, 1, 60, 750]. what is B and 1 means? |
@yzyouzhang i checked it again , no other process occupying my gpu memory. could you please share your id or zoom id for further contact to solve this issue? |
@yzyouzhang what threshold score you have set for real and fake samples? |
B is the batch size, 1 is the number of channels for CNN. |
We do not need a threshold to calculate EER. If you want to classify samples into two classes, you can choose a value between the r1 and r2 of the OCSoftmax. |
Please contact yzyouzhang@gmail.com for further zoom discussions. Thanks. |
ok thanks :) |
I have applied your pretrained model on some audio files but it give me error :
RuntimeError: Calculated padded input size per channel: (3 x 752). Kernel size: (9 x 3). Kernel size can't be greater than actual input size
Do you know what is the reason?
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