即使在重新启动计算机后,仍有95%的已用GPU内存
python3
.
请注意,即使没有运行的训练脚本,内存消耗也会保持不变,而且我从未使用过
keras/tensorflow
在系统环境中,只有
venv
更新时间:
最后一个活动是使用以下配置执行NN测试脚本:
tensorflow==1.14.0
Keras==2.0.3
tf.autograph.set_verbosity(1)
session_conf = tf.ConfigProto(intra_op_parallelism_threads=8, inter_op_parallelism_threads=8)
tf.set_random_seed(1)
session_conf.gpu_options.allow_growth = True
sess = tf.Session(graph=tf.get_default_graph(), config=session_conf)
K.set_session(sess)
$ nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.26 Driver Version: 440.26 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 GTX 105... Off | 00000000:01:00.0 Off | N/A |
| N/A 53C P3 N/A / N/A | 3981MiB / 4042MiB | 1% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 4105 G /usr/lib/xorg/Xorg 145MiB |
| 0 4762 C /usr/bin/python3 3631MiB |
| 0 4764 G /usr/bin/gnome-shell 88MiB |
| 0 5344 G ...quest-channel-token=8947774662807822104 61MiB |
| 0 6470 G ...Charm-P/ch-0/191.6605.12/jre64/bin/java 5MiB |
| 0 7200 C python 45MiB |
+-----------------------------------------------------------------------------+
nvidia-smi -r
但这并不能解决问题。
