Training on GPU is not working for me by setting -gpu 0,1,2 command line options.
./scripts/train.sh -gpu 0 -image_set train -log_dir ./log/
I'm running SqueezeSegV2 on a conda virtual environment with tensorflow-gpu version 1.4.1
$ pip list | grep tensorflow
tensorflow-estimator 1.14.0
tensorflow-gpu 1.4.1
tensorflow-tensorboard 0.4.0
By invoking the training script the GPU remains mainly unused
$ nvidia-smi
Thu Aug 1 15:50:58 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 430.26 Driver Version: 430.26 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce RTX 2070 Off | 00000000:15:00.0 Off | N/A |
| 29% 30C P8 14W / 175W | 107MiB / 7982MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 Quadro P1000 Off | 00000000:21:00.0 On | N/A |
| 34% 40C P8 N/A / N/A | 507MiB / 4030MiB | 4% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 26958 C python 93MiB |
| 1 1599 G /usr/bin/gnome-shell 92MiB |
| 1 2379 G /usr/bin/gnome-shell 392MiB |
+-----------------------------------------------------------------------------+
I expected GPU training to be working out of the box. What am I missing?