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Input type (torch.FloatTensor) and weight type (torch.cuda.FloatTensor) should be the same
See original GitHub issueHi there! Thanks for your great repo, but i faced with some difficulties while trying to inference on device (‘cuda:0’). My code:
device = torch.device('cuda:0')
tfms = transforms.Compose([transforms.Resize(224), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),])
img = tfms(Image.open('img.png')).unsqueeze(0)
img.to(device)
model.to(device)
model.eval()
with torch.no_grad(): outputs = model(img)
And thrown error:
RuntimeError: Input type (torch.FloatTensor) and weight type (torch.cuda.FloatTensor) should be the same
Issue Analytics
- State:
- Created 4 years ago
- Comments:7
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Sorry, i didn’t understand your answer. Thank you very much,
So it’s impossibile to run on GPU or i missed something?