Hello everyone!
I have written a U-Net with TensorFlow (see attachment). With this I want to predict CT images from MR images. It's nothing fancy and the code is very well commented.
I started training over 5 hours ago (112 concatenated 3D MR/CT images as training and 25 concatenated 3D MR/CT images as validation) and it’s not even through the first of 50 epochs.
One guess is that Spyder is not using the available 32 processor cores and/or not using the Quadro GV100 32 GB GPU. I also have 512 GB of RAM at my disposal.
The only thing I did in the Python code regarding multiprocessing is to set use_multiprocessing=True.
Thanks in advance for ANY support!
I have written a U-Net with TensorFlow (see attachment). With this I want to predict CT images from MR images. It's nothing fancy and the code is very well commented.
I started training over 5 hours ago (112 concatenated 3D MR/CT images as training and 25 concatenated 3D MR/CT images as validation) and it’s not even through the first of 50 epochs.
One guess is that Spyder is not using the available 32 processor cores and/or not using the Quadro GV100 32 GB GPU. I also have 512 GB of RAM at my disposal.
The only thing I did in the Python code regarding multiprocessing is to set use_multiprocessing=True.
Thanks in advance for ANY support!
Attached Files
U-Net.py (Size: 2.98 KB / Downloads: 3)