Ubuntu version:
18.04 LTS
NVidia graphic card:
NVidia 1080
NVidia graphic driver:
410.93
CUDA:
9.0
Cudnn:
7.0.
Tensorflow-gpu:
18.04 LTS
NVidia graphic card:
NVidia 1080
NVidia graphic driver:
410.93
CUDA:
9.0
Cudnn:
7.0.
Tensorflow-gpu:
how to check nvidia driver version:
1. $ nvidia-smi
1. $ nvidia-smi
check cuda version:
cat /usr/local/cuda/version.txt
nvcc --version
cat /usr/local/cuda/version.txt
nvcc --version
Installing Tensorflow GPU on Ubuntu 18.04 LTS for deepfakehttps://medium.com/@taylordenouden/installing-tensorflow-gpu-on-ubuntu-18-04-89a142325138 *****
step1:nvidia driver
https://www.geforce.com.tw/drivers
sudo ./NVIDIA-Linux-x86_64-410.93.run
出現 Would you like to run the nvidia-xconfig utility to automatically update your X configuration file
so that the NVIDIA X driver will be used when you restart X?
Any pre-existing X configuration file will be backed up
回答:Yes (注意預設值是No)
OR:
(~) viper1 $ ubuntu-drivers devices
== /sys/devices/pci0000:00/0000:00:01.0/0000:01:00.0 ==
modalias : pci:v000010DEd00001BE0sv00001025sd00001146bc03sc00i00
vendor : NVIDIA Corporation
model : GP104M [GeForce GTX 1080 Mobile]
manual_install: True
driver : nvidia-driver-410 - third-party free
driver : nvidia-driver-390 - third-party free
driver : nvidia-driver-396 - third-party free
driver : nvidia-driver-415 - third-party free recommended
driver : xserver-xorg-video-nouveau - distro free builtin
step2:cuda V9.0
sudo chmod +x cuda_9.0.176_384.81_linux.run
./cuda_9.0.176_384.81_linux.run --override
choose no to “Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 384.81?”
step3:cudnn V7.1.4
cudnn
cuDNN v7.1.4 Library for Linux <=====pls download this one, not ubuntu XXXX
cudnn-9.0-linux-x64-v7.tgz
# Unpack the archive
tar -zxvf cudnn-9.0-linux-x64-v7.tgz
# Move the unpacked contents to your CUDA directory
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-9.0/lib64/
sudo cp cuda/include/cudnn.h /usr/local/cuda-9.0/include/
# Give read access to all users
sudo chmod a+r /usr/local/cuda-9.0/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
step4:Install libcupti
sudo apt-get install libcupti-dev
step5:Do the CUDA post-install actions
So Tensorflow can find your CUDA installation and use it properly, you need to add these lines to the end of you ~/.bashrc or ~/.zshrc.
export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
step6:Install Tensorflow GPU
pip install --upgrade tensorflow-gpu
check if tensorflow-gpu works:
python3
>>>import tensorflow as tf
>>>sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
step1:nvidia driver
https://www.geforce.com.tw/drivers
sudo ./NVIDIA-Linux-x86_64-410.93.run
出現 Would you like to run the nvidia-xconfig utility to automatically update your X configuration file
so that the NVIDIA X driver will be used when you restart X?
Any pre-existing X configuration file will be backed up
回答:Yes (注意預設值是No)
OR:
(~) viper1 $ ubuntu-drivers devices
== /sys/devices/pci0000:00/0000:00:01.0/0000:01:00.0 ==
modalias : pci:v000010DEd00001BE0sv00001025sd00001146bc03sc00i00
vendor : NVIDIA Corporation
model : GP104M [GeForce GTX 1080 Mobile]
manual_install: True
driver : nvidia-driver-410 - third-party free
driver : nvidia-driver-390 - third-party free
driver : nvidia-driver-396 - third-party free
driver : nvidia-driver-415 - third-party free recommended
driver : xserver-xorg-video-nouveau - distro free builtin
$ sudo ubuntu-drivers autoinstall
or
$ sudo apt install nvidia-415
step2:cuda V9.0
sudo chmod +x cuda_9.0.176_384.81_linux.run
./cuda_9.0.176_384.81_linux.run --override
choose no to “Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 384.81?”
step3:cudnn V7.1.4
cudnn
cuDNN v7.1.4 Library for Linux <=====pls download this one, not ubuntu XXXX
cudnn-9.0-linux-x64-v7.tgz
# Unpack the archive
tar -zxvf cudnn-9.0-linux-x64-v7.tgz
# Move the unpacked contents to your CUDA directory
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-9.0/lib64/
sudo cp cuda/include/cudnn.h /usr/local/cuda-9.0/include/
# Give read access to all users
sudo chmod a+r /usr/local/cuda-9.0/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
step4:Install libcupti
sudo apt-get install libcupti-dev
step5:Do the CUDA post-install actions
So Tensorflow can find your CUDA installation and use it properly, you need to add these lines to the end of you ~/.bashrc or ~/.zshrc.
export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
step6:Install Tensorflow GPU
pip install --upgrade tensorflow-gpu
check if tensorflow-gpu works:
python3
>>>import tensorflow as tf
>>>sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
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