Dear concern,
I need help with calling the trained model and getting prediction results from it. I really appreciate any help you can provide.
def get_prediction(model, dataloader):
with torch.no_grad():
model = model.to(device)
model.eval()
prediction = np.zeros(len(dataloader.dataset))
labels = np.zeros(len(dataloader.dataset))
k = 0
for images, target in dataloader:
if device:
images = images.type(torch.cuda.FloatTensor)
images = images.device
prediction[k:k+len(images)] = np.argmax(model(images).data.cpu().numpy(), axis=1)
labels[k:k+len(images)] = target.numpy()
k += len(images)
return prediction, labels
pred = get_prediction(model, valid_loader)