Last active
March 5, 2019 10:10
-
-
Save oneleo/8a62bf483d46ee47c1a34b8c8fbea397 to your computer and use it in GitHub Desktop.
Install Tensorflow/Keras in Ubuntu 18.04
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# 在 Ubuntu 18 安裝 Tensorflow/Keras 開發環境 | |
## 安裝 nVidia 顯示卡驅動程式 | |
``` | |
$ sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub | |
$ sudo bash -c 'echo "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/cuda.list' | |
$ sudo add-apt-repository ppa:graphics-drivers/ppa | |
$ sudo apt-get update | |
$ sudo apt-get -y install nvidia-driver-415 htop git | |
``` | |
## 測試 nVidia 驅動程式安裝完成 | |
``` | |
$ sudo reboot # 重新開機 | |
$ nvidia-smi | |
$ htop | |
``` | |
## 安裝 CUDA Toolkit | |
``` | |
$ cd /tmp && wget ftp://10.131.28.168/Public/cuda_10.0.130_410.48_linux | |
$ sudo chmod +x cuda_10.0.130_410.48_linux | |
$ sudo ./cuda_10.0.130_410.48_linux | |
``` | |
### cuda_10.0.130_410.48_linux 的安裝流程(注意:安裝的過程中不要再安裝 nVidia Driver): | |
``` | |
Do you accept the previously read EULA? | |
accept/decline/quit: accept →【ENTER】 | |
Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 410.48? | |
(y)es/(n)o/(q)uit: n →【ENTER】 | |
Install the CUDA 10.0 Toolkit? | |
(y)es/(n)o/(q)uit: y →【ENTER】 | |
Enter Toolkit Location | |
[ default is /usr/local/cuda-10.0 ]:【ENTER】 | |
Do you want to install a symbolic link at /usr/local/cuda? | |
(y)es/(n)o/(q)uit: y →【ENTER】 | |
Install the CUDA 10.0 Samples? | |
(y)es/(n)o/(q)uit: y →【ENTER】 | |
Enter CUDA Samples Location | |
[ default is /home/chtti ]:【ENTER】 | |
``` | |
## 刪除用不到的 cuda_10.0.130_410.48_linux 安裝檔 | |
``` | |
$ sudo rm -rf cuda_10.0.130_410.48_linux | |
``` | |
## 安裝 CUDNN | |
``` | |
$ cd /tmp && wget ftp://10.131.28.168/Public/cudnn-10.0-linux-x64-v7.5.0.56.tgz | |
$ tar -zxvf cudnn-10.0-linux-x64-v7.5.0.56.tgz | |
$ sudo cp cuda/include/cudnn.h /usr/local/cuda/include/ | |
$ sudo cp cuda/lib64//libcudnn* /usr/local/cuda/lib64/ | |
$ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn* | |
$ sudo rm -rf cuda cudnn-10.0-linux-x64-v7.5.0.56.tgz | |
``` | |
## 設定環境變數 | |
``` | |
$ vim ~/.bashrc | |
``` | |
### 在 ~/.bashrc 檔最下方加入以下內容 | |
``` | |
(上略) | |
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64" | |
export CUDA_HOME=/usr/local/cuda | |
export PATH=$PATH:/usr/local/cuda/bin | |
``` | |
## 測試環境變數是否有設定完成 | |
``` | |
$ source ~/.bashrc | |
$ nvcc -V | |
``` | |
## 安裝 Anaconda | |
``` | |
$ cd /tmp && wget ftp://10.131.28.168/Public/Anaconda3-2018.12-Linux-x86_64.sh | |
$ chmod +x Anaconda3-2018.12-Linux-x86_64.sh | |
$ ./Anaconda3-2018.12-Linux-x86_64.sh | |
``` | |
### Anaconda3-2018.12-Linux-x86_64.sh 的安裝流程: | |
``` | |
Please, press ENTER to continue | |
>>>【ENTER】 | |
Do you accept the license terms? [yes|no] | |
[no] >>> yes →【ENTER】 | |
Anaconda3 will now be installed into this location: /home/chtti/anaconda3 | |
- Press ENTER to confirm the location | |
- Press CTRL-C to abort the installation | |
- Or specify a different location below | |
[/home/chtti/anaconda3] >>> | |
Do you wish the installer to initialize Anaconda3 in your /home/chtti/.bashrc ? [yes|no] | |
[no] >>> yes →【ENTER】 | |
Do you wish to proceed with the installation of Microsoft VSCode? [yes|no] | |
>>> yes →【ENTER】 | |
``` | |
## 刪除用不到的 Anaconda3-2018.12-Linux-x86_64.sh 安裝檔 | |
``` | |
$ sudo rm -rf cuda Anaconda3-2018.12-Linux-x86_64.sh | |
``` | |
## 測試 Anaconda 是否有安裝完成 | |
``` | |
$ source ~/.bashrc | |
$ conda | |
``` | |
## 使用 conda 指令建立 Tensorflow 開發環境(名為 tensorflow217) | |
``` | |
$ conda create -n tensorflow217 anaconda nb_conda # Proceed ([y]/n)? y →【ENTER】 | |
$ source activate tensorflow217 | |
``` | |
## 在 tensorflow217 開發環境安裝 tensorflow、opencv、keras | |
``` | |
$ pip install tensorflow-gpu | |
$ pip install opencv-python | |
$ pip install keras | |
``` | |
## 測試 tensorflow217 開發環境可正確執行 tensorflow | |
``` | |
$ cd /tmp && git clone https://github.com/tensorflow/benchmarks.git | |
$ cd benchmarks/ | |
$ git checkout cnn_tf_v1.12_compatible | |
$ python scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --num_gpus=1 --model resnet50 --batch_size=16 | |
``` | |
## 在 tensorflow217 開發環境中開啟 jupyter 網頁開發界面(工作目錄在 ~/workspace) | |
``` | |
$ mkdir -p ~/workspace && cd ~/workspace | |
$ jupyter notebook | |
``` | |
## 刪除名為 tensorflow217 開發環境 | |
``` | |
source deactivate | |
conda-env remove -n tensorflow217 # Proceed ([y]/n)? y →【ENTER】 | |
``` |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment