Hello all , As per available pretrained nets which were trained on msra dataset or coco dataset and we have various versions of resnet50 ,101 and 152 . I was planning go ahead with resnet101 as we train it or fine tune it using existing .pkl , i want to create my own .pkl for further training to simplify like create my massive aerial imagery dataset and train it on top of coco dataset so it would have learned features of earlier and now new aerial features than use it for further training of which we create .pth file .
I tried convert .pth file to .pkl using script convert-torchvision-to-d2.py available in d2 tools folder however it could not be converted so i changed line newmodel[k] = obj.pop(old_k).detach().numpy() to newmodel[k] = obj.pop(old_k) it got converted however gave error when used for training . Please help me out thank you !
Hello all , As per available pretrained nets which were trained on msra dataset or coco dataset and we have various versions of resnet50 ,101 and 152 . I was planning go ahead with resnet101 as we train it or fine tune it using existing .pkl , i want to create my own .pkl for further training to simplify like create my massive aerial imagery dataset and train it on top of coco dataset so it would have learned features of earlier and now new aerial features than use it for further training of which we create .pth file . I tried convert .pth file to .pkl using script convert-torchvision-to-d2.py available in d2 tools folder however it could not be converted so i changed line
newmodel[k] = obj.pop(old_k).detach().numpy()tonewmodel[k] = obj.pop(old_k)it got converted however gave error when used for training . Please help me out thank you !