Kernel restarting while testing demo_CoarseNet.ipynb
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I was trying to test your code for demoCoarseNet.ipnb, it takes some time for the pre-trained model to load. Once we are at line #82,
enh_img, enh_img_imag, enhance_img, ori_out_1, ori_out_2, seg_out, mnt_o_out, mnt_w_out, mnt_h_out, mnt_s_out \
= main_net_model.predict(image)
This seems to crash. I suspect out of memory issues on card but I am confident the card does have enough memory. I copied the code to simple text file and ran it in Spyder3, it seems that the above line is causing the kernel to restart in jupyter notebook. Same happens in Spyder3
Spyder 3.2.8
Python 3.6.5
Tensorflow 1.6.0
Keras 2.1.5
Nvidia GTX 960M (4GB )
Did you run into such an issue?
It is quite strange. I rechecked but everything is ok. Were you successful running CoarseNet_run.py? If not, the problem might be from your hardware??
I will try it and let you know. Have not looked into it yet
OK So i did some more code conversions for Python3 compatibility. Seems that the problem is persisting even in CoarseNet_run.py. My laptop has 16 GB of memory and code peaks at 14.9 before the kernel restarts. I suspect a problem with Tensorflow?
Yep - It was a tensorflow issue. I updated tensorflow 1.8.0 and keras to 2.2.0. The error is gone now.
Cool. Glad you fixed it!