Tensorflow with gpu
From ElphelWiki
Pre
- check device
~$ lspci | grep NVIDIA 81:00.0 VGA compatible controller: NVIDIA Corporation GF119 [GeForce GT 610] (rev a1) 81:00.1 Audio device: NVIDIA Corporation GF119 HDMI Audio Controller (rev a1)
- check driver version
~$ cat /proc/driver/nvidia/version NVRM version: NVIDIA UNIX x86_64 Kernel Module 387.26 Thu Nov 2 21:20:16 PDT 2017 GCC version: gcc version 5.4.0 20160609 (Ubuntu 5.4.0-6ubuntu1~16.04.9)
- install cuda 9.2 with patches
https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1604&target_type=deblocal
- then
sudo apt-get install cuda-9-2 # included on that NVidia page
https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions
~$ export PATH=/usr/local/cuda-9.2/bin${PATH:+:${PATH}}
~$ export LD_LIBRARY_PATH=/usr/local/cuda-9.2/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
~$ nvidia-smi
Thu Apr 26 12:39:25 2018
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 387.26 Driver Version: 387.26 |
|-------------------------------+----------------------+----------------------+
| 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 GT 610 Off | 00000000:81:00.0 N/A | N/A |
| N/A 31C P8 N/A / N/A | 148MiB / 956MiB | N/A Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 Not Supported |
+-----------------------------------------------------------------------------+
- install tensorflow
~$ sudo apt-get install python3-pip # if it is not already installed
~$ sudo pip3 install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.7.0-cp35-cp35m-linux_x86_64.whl
- testing: unsupported card GeForce GT 610
~$ python3
Python 3.5.2 (default, Nov 23 2017, 16:37:01)
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, World!')
>>> sess = tf.Session()
2018-04-26 13:00:19.050625: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-04-26 13:00:19.181581: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1344] Found device 0 with properties:
name: GeForce GT 610 major: 2 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:81:00.0
totalMemory: 956.50MiB freeMemory: 631.69MiB
2018-04-26 13:00:19.181648: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1394] Ignoring visible gpu device (device: 0, name: GeForce GT 610, pci bus id: 0000:81:00.0, compute capability: 2.1) with Cuda compute capability 2.1. The minimum required Cuda capability is 3.5.
2018-04-26 13:00:19.181669: I tensorflow/core/common_runtime/gpu/gpu_device.cc:911] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-04-26 13:00:19.181683: I tensorflow/core/common_runtime/gpu/gpu_device.cc:917] 0
2018-04-26 13:00:19.181695: I tensorflow/core/common_runtime/gpu/gpu_device.cc:930] 0: N
>>> print(sess.run(hello))
b'Hello, World!'
- testing: supported card GeForce GTX 750 Ti
~$ python3
Python 3.5.2 (default, Nov 23 2017, 16:37:01)
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, World!')
>>> sess = tf.Session()
2018-04-26 18:14:05.427668: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:898] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning
NUMA node zero
2018-04-26 18:14:05.428033: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1344] Found device 0 with properties:
name: GeForce GTX 750 Ti major: 5 minor: 0 memoryClockRate(GHz): 1.1105
pciBusID: 0000:01:00.0
totalMemory: 1.95GiB freeMemory: 1.53GiB
2018-04-26 18:14:05.428061: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1423] Adding visible gpu devices: 0
2018-04-26 18:14:05.927106: I tensorflow/core/common_runtime/gpu/gpu_device.cc:911] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-04-26 18:14:05.927149: I tensorflow/core/common_runtime/gpu/gpu_device.cc:917] 0
2018-04-26 18:14:05.927163: I tensorflow/core/common_runtime/gpu/gpu_device.cc:930] 0: N
2018-04-26 18:14:05.927313: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1289 MB memory) -> physical GPU (device: 0,
name: GeForce GTX 750 Ti, pci bus id: 0000:01:00.0, compute capability: 5.0)
>>> print(sess.run(hello))
b'Hello, World!'
- Supported cards:
https://developer.nvidia.com/cuda-gpus
- As a quickfix had to install CuDNN 7.0.5 instead of latest:
https://stackoverflow.com/questions/49960132/cudnn-library-compatibility-error-after-loading-model-weights
