TensorFlow安裝筆記
紀錄在 windows 10 安裝 TensorFlow GPU 版本的過程
目錄
安裝
安裝TensorFlow
此筆記紀錄支援GPU的安裝版本,安裝環境GPU為GeForce GTX 750 Ti 繪圖卡。
安裝CUDA 8.0
下載、安裝
CUDA 8 下載網址: https://developer.nvidia.com/cuda-80-ga2-download-archive
此筆記選擇local版本安裝。
選擇所要的版本下載完成後,打開安裝程式,照著指示安裝。此筆記安裝選項選擇: 快速(建議)。
並安裝Patch 2 (Released Jun 26, 2017)做補丁更新。
檢查配置是否正確
檢查CUDA Toolkit的版本: 在命令提示字元中輸入 nvcc -V
。
驗證硬體與軟體的正確配置,官方文件強烈建議在預設路徑 C:\ProgramData\NVIDIA Corporation\CUDA Samples\v8.0\bin\win64\Release
中執行 DEVICEQUERY
筆者結果如下:
C:\ProgramData\NVIDIA Corporation\CUDA Samples\v8.0\bin\win64\Release>DEVICEQUERY
DEVICEQUERY Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 750 Ti"
CUDA Driver Version / Runtime Version 8.0 / 8.0
CUDA Capability Major/Minor version number: 5.0
Total amount of global memory: 2048 MBytes (2147483648 bytes)
( 5) Multiprocessors, (128) CUDA Cores/MP: 640 CUDA Cores
GPU Max Clock rate: 1137 MHz (1.14 GHz)
Memory Clock rate: 2700 Mhz
Memory Bus Width: 128-bit
L2 Cache Size: 2097152 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
CUDA Device Driver Mode (TCC or WDDM): WDDM (Windows Display Driver Model)
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 1 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = GeForce GTX 750 Ti
Result = PASS
主要確保有偵測到與系統所安裝符合的設備,筆者即為GeForce GTX 750 Ti 。
若cmd找不到 DEVICEQUERY
,則到預設路徑 C:\ProgramData\NVIDIA Corporation\CUDA Samples\v8.0\1_Utilities\deviceQuery
找到與系統對應的VS版本.sln檔進行編譯,如筆者為VS2013版,包括Debug與Release皆進行編譯 [[1]]。編譯後即可回去執行 DEVICEQUERY
。
(另有 bandwidthTest
部分,cmd找不到,筆者未能理解,暫為保留)
(設定 $path
尚待理解,現確認有未新專案增加路徑與現存專案增加路徑2種)
安裝cuDNN 6.0
cuDNN下載網址: https://developer.nvidia.com/rdp/cudnn-download
需註冊nVIDIA developer帳號才能下載。
選擇符合的作業系統版本安裝,下載後為一個壓縮檔,將CUDA 資料夾裡面的3個資料夾: bin、include、lib,解壓縮至 C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0
中 [[2]]。此筆記使用cuDNN v6.0 (April 27, 2017), for CUDA 8.0。
原生pip安裝TensorFlow
安裝
此筆記選擇GPU版本TensorFlow,使用以下指令:
C:\> pip3 install --upgrade tensorflow-gpu
此指令會下載最新的版本,筆者此時的版本為1.4
驗證安裝成功
在shell裡啟動python(筆者使用cmd):
$ python
並在裡面輸入以下python程式碼:
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> print(sess.run(hello))
若輸出為Hello, TensorFlow!
表示成功可執行。
參考資料
Installing TensorFlow on Windows | TensorFlow
https://www.tensorflow.org/install/install_windows
Installation Guide Windows :: CUDA Toolkit Documentation
https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/
问一下大神deviceQuery.exe怎没有呢【cuda吧】_百度贴吧 [1]
[1]: http://tieba.baidu.com/p/4565248851
http://tieba.baidu.com/p/4565248851
閱讀記事: 於Win10環境下配置CUDA與cuDNN [2]
[2]: https://rreadmorebooks.blogspot.tw/2017/04/win10cudacudnn.html
https://rreadmorebooks.blogspot.tw/2017/04/win10cudacudnn.html
最後編輯日期: 2017/12/29
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