Be sure you have torch and torchvision installed: pip install torchvision The minimalist example below assumes the definition of a Net class and train and test functions, included in pytorch_example: import torch from petastorm.pytorch import DataLoader torch.manual_seed(1) device = torch.device('...
import torch torch.cuda.is_available() Both driver 470, everything works, does not matter what order you do this. Both driver 535, the first machine to run the python code has access to the GPU, the second machine fails. Machine 1 has driver 470, Machine 2 has driver 535, if you ...
3. machine learning by pytorch workflow --> torch.load torch.save4. prediction task deep dive--> dynamics, map encode , ego predection infromation5. remote GPU cluster workflow6. dataset to ros bag for visualization7. method for handle very big dataset, test mini dataset at first, make ...
Approach 3: Call API Directly # copy the ./models folder iin your project folderfrom.model.camn_audioimportCaMNAudioModelmodel=CaMNAudioModel.from_pretrained("H-Liu1997/huggingface-model/camn_audio")model.cuda().eval()importlibrosaimportnumpyasnpimporttorch# copy the ./emage_utils folder in ...