-What are your command line arguments? python train.py --model=BiSeNet --dataset=XXX --crop_height=480 --crop_width=480 --batch_size=4
-Have you written any custom code? No
-What have you done to try and solve this issue? Read "FAQ" and "Issues"
-TensorFlow version? gpu 1.9.0
Describe the problem
I run train.py but the gpu utilization showed in nvidia-smi is insignificant. I changed the line "with tf.device('/cpu:0'):" to "with tf.device('/gpu:0'):" in train.py but nothing changes. Is there a way to activate gpu utilization that I haven't found? Or there is no significant difference between gpu and cpu training?
-What are your command line arguments? python train.py --model=BiSeNet --dataset=XXX --crop_height=480 --crop_width=480 --batch_size=4 -Have you written any custom code? No -What have you done to try and solve this issue? Read "FAQ" and "Issues" -TensorFlow version? gpu 1.9.0
Describe the problem
I run train.py but the gpu utilization showed in nvidia-smi is insignificant. I changed the line "with tf.device('/cpu:0'):" to "with tf.device('/gpu:0'):" in train.py but nothing changes. Is there a way to activate gpu utilization that I haven't found? Or there is no significant difference between gpu and cpu training?
Thanks in advance.