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Frameworks & web · #pytorch
When should I use .eval() ? I understand it is supposed to allow me to "evaluate my model". How do I turn it back off for training? Example training code using .eval() .
I am trying to initialize a tensor on Google Colab with GPU enabled. device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') t = torch.tensor([1,2], device=device) But I am getting this strange error. RuntimeError: CUDA error: device-side assert triggered CUDA kernel errors might be asynchronously reported at some other API call,so the stacktra
I'm trying to run Pytorch on a laptop that I have. It's an older model but it does have an Nvidia graphics card. I realize it is probably not going to be sufficient for real machine learning but I am trying to do it so I can learn the process of getting CUDA installed. I have followed the steps on the installation guide for Ubuntu 18.04 (my specific distribu
On a Windows 10 PC with an NVidia GeForce 820M I installed CUDA 9.2 and cudnn 7.1 successfully, and then installed PyTorch using the instructions at pytorch.org: pip install torch==1.4.0+cu92 torchvision==0.5.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html But I get: >>> import torch >>> torch.cuda.is_available() False
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