'Tensorflow can't use GPU. tf.test.is_gpu_available() show GPU but cannot use
I have Ubuntu 18.04. Python 3.7.3, Tensorflow 2.0.0
here's my cuda version:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Nov__3_21:07:56_CDT_2017
Cuda compilation tools, release 9.1, V9.1.85
My computer is UX430UQ, graphic card is GeForce 940MX
Here's the output from nvidia-smi:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.87.01 Driver Version: 418.87.01 CUDA Version: 10.1 |
|-------------------------------+----------------------+----------------------+
| 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 940MX On | 00000000:01:00.0 Off | N/A |
| N/A 45C P0 N/A / N/A | 283MiB / 2004MiB | 9% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1014 G /usr/lib/xorg/Xorg 24MiB |
| 0 1164 G /usr/bin/gnome-shell 47MiB |
| 0 1440 G /usr/lib/xorg/Xorg 123MiB |
| 0 1615 G /usr/bin/gnome-shell 84MiB |
+-----------------------------------------------------------------------------+
Here's the output when I run sudo apt-get install cuda:
Reading package lists...
Building dependency tree...
Reading state information...
cuda is already the newest version (10.1.243-1).
0 upgraded, 0 newly installed, 0 to remove and 138 not upgraded.
Here's the output when I run tf.test.is_gpu_available()
2019-10-08 21:04:37.186069: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-10-08 21:04:37.188434: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce 940MX major: 5 minor: 0 memoryClockRate(GHz): 1.2415
pciBusID: 0000:01:00.0
2019-10-08 21:04:37.188863: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcudart.so.10.0'; dlerror: libcudart.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-8.0/lib64
2019-10-08 21:04:37.189156: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcublas.so.10.0'; dlerror: libcublas.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-8.0/lib64
2019-10-08 21:04:37.189426: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcufft.so.10.0'; dlerror: libcufft.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-8.0/lib64
2019-10-08 21:04:37.189687: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcurand.so.10.0'; dlerror: libcurand.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-8.0/lib64
2019-10-08 21:04:37.189946: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcusolver.so.10.0'; dlerror: libcusolver.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-8.0/lib64
2019-10-08 21:04:37.190202: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcusparse.so.10.0'; dlerror: libcusparse.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-8.0/lib64
2019-10-08 21:04:37.190236: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-10-08 21:04:37.190244: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1641] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2019-10-08 21:04:37.190261: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-10-08 21:04:37.190268: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0
2019-10-08 21:04:37.190276: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N
Solution 1:[1]
You should use cuda10 and cudnn7.4 referring to this web
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | DachuanZhao |