Tensorflow-GPU getting stuck saving checkpoint during training - also not using entire GPU, not sure why
Had the same issues till I upgradet the Nvidia driver from Version 441.28 to the newest Version.
After this, the training runs without stops or freezes.
GPU: Nvidia GTX 2070
Python Version: 3.5 
Tensorflow: 1.13.1
CUDA: 10
cuDNN: 7.4
Model: Faster-RCNN-Inception-V2
I am using the legacy method of training my model (trian.py) and when I run it as such
python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config
The training runs for some random amount of time (it usually gets stuck around the 150th step, but it will often make it up to 300-700 sometimes when I try it) and then will get stuck attempting to save a checkpoint. I reach the point where it just says 
INFO:tensorflow:global step 864: loss = 0.4430 (0.996 sec/step)
INFO:tensorflow:Saving checkpoint to path training/model.ckpt
INFO:tensorflow:Saving checkpoint to path training/model.ckpt
And does not move past that point. Once it reaches this point, I also become incapable of killing the program no matter which methods I try and am forced to simply close the terminal window if I want the process to stop. 
Additionally, based on what I have read, the program should theoretically be using up close to 100% of my GPU while it trains but it only ends up using about 10%. I'm not sure if those two things are related but I feel it is probably worth mentioning, especially considering I would like to have it train as fast as possible if I do manage to get it working. 
I've seen others post about similar issues in the past but none seem to have any answers. If anyone has any idea please let me know! Thanks.