Epoch: 0
Traceback (most recent call last):
File "train.py", line 114, in
train(epoch)
File "train.py", line 75, in train
loss = criterion(loc_preds, loc_targets, cls_preds, cls_targets)
File "/home/hs/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, *kwargs)
File "/home/hs/hs/pytorch/pytorch-retinanet-580/loss.py", line 99, in forward
print('loc_loss: %.3f | cls_loss: %.3f' % (loc_loss.item()/num_pos, cls_loss.item()/num_pos), end=' | ')
File "/home/hs/anaconda3/lib/python3.6/site-packages/torch/tensor.py", line 320, in rdiv
return self.reciprocal() other
RuntimeError: reciprocal is not implemented for type torch.cuda.LongTensor
1.Run script get_state_dict.py first to get a base model.
2.Put the generated model in model/net.pth.
3.Then start the training with python train.py --lr 0.001.
python train.py ==> Preparing data..
Epoch: 0 Traceback (most recent call last): File "train.py", line 114, in
train(epoch)
File "train.py", line 75, in train
loss = criterion(loc_preds, loc_targets, cls_preds, cls_targets)
File "/home/hs/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, *kwargs)
File "/home/hs/hs/pytorch/pytorch-retinanet-580/loss.py", line 99, in forward
print('loc_loss: %.3f | cls_loss: %.3f' % (loc_loss.item()/num_pos, cls_loss.item()/num_pos), end=' | ')
File "/home/hs/anaconda3/lib/python3.6/site-packages/torch/tensor.py", line 320, in rdiv
return self.reciprocal() other
RuntimeError: reciprocal is not implemented for type torch.cuda.LongTensor