I have a really small neural network -
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
scores_input (InputL (None, 2) 0
_________________________________________________________________
dense1 (Dense) (None, 1) 2
_________________________________________________________________
bn (BatchNormalizati (None, 1) 4
_________________________________________________________________
sigmoid (Activation) (None, 1) 0
=================================================================
Total params: 6
Trainable params: 4
Non-trainable params: 2
However, it takes about 1.3 GB in the gpu memory as shown by nvidia-smi
Wed Aug 28 08:41:38 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 384.130 Driver Version: 384.130 |
|-------------------------------+----------------------+----------------------+
| 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 GTX 960 Off | 00000000:01:00.0 On | N/A |
| 30% 42C P2 29W / 120W | 1763MiB / 1988MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1258 G /usr/lib/xorg/Xorg 251MiB |
| 0 2336 G compiz 231MiB |
| 0 25537 G .../innereye/qtcreator-4.9.2/bin/qtcreator 2MiB |
| 0 30098 G ...-token=DA8EE4CD7070EDEBCD3537BAAD982629 37MiB |
| 0 30436 C python 1227MiB |
+-----------------------------------------------------------------------------+
I need to load another (larger) network, but they don't fit together in the GPU memory. Any help?
