[Tensorflow] windows 에 Tensorflow 설치하기 - CUDA GPU

 

[Tensorflow] windows 에 Tensorflow 설치하기 - CUDA GPU 

Windows 10 기준 텐서플로우 설치하기 

 

먼저 Python/Anaconda Windows 설치하기(http://dwfox.tistory.com/67)를 통해 3.5버전의 Python 설치 후 Tensorflow 설치 진행 할 것

 

 

  Tensorflow GPU 버전 - CUDA 설치하기

Tensorflow GUP 버전을 사용하기 위해서는 NVIDIA의 그래픽카드와 소프트웨어가 설치 되어 있어야 한다.

 

1. CUDA® Toolkit 8.0. 설치하기 

Cuda Toolkit 다운로드 [link] : https://developer.nvidia.com/cuda-downloads

컴퓨터 환경에 맞게 선택하고 다운로드 한다.

 

설치시 경로를 확인한다.

디폴트 경로는 아래와 같이 설정되어 있다.

 

설치 후 환경변수 편집을 통해

시스템 변수 Path에 경로 기준

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin 

 

2. cuDNN v5.1 설치하기 

 

cuDNN 5.1 다운로드 [link]: https://developer.nvidia.com/cudnn

CuDNN은 NVIDIA에서 회원가입을 해야 다운 받을 수 있다.

간단하게 회원가입을 하고 다운을 받는다.

 

 

 

다운받은 파일은 기본경로 기준에 압축을 풀도록 한다.

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin

 

 

 

  Tensorflow 설치

 

1. Tensorflow 설치 - Anaconda

 

C:\>python --version Python 3.5.2 :: Anaconda 4.2.0 (64-bit)

 

C:\>conda create -n tensorflow python=3.5

 

C:\>activate tensorflow

 

(tensorflow) C:\>

 

(tensorflow) C:\ pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.2.1-cp35-cp35m-win_amd64.whl

 

 

2. Tensorflow GPU - 테스트 결과

C:\>python Python 3.5.2 |Anaconda 4.2.0 (64-bit)| (default, Jul 5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>> import tensorflow as tf I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:128] successfully opened CUDA library cublas64_80.dll locally I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:119] Couldn't open CUDA library cudnn64_5.dll I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\cuda\cuda_dnn.cc:3459] Unable to load cuDNN DSO I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:128] successfully opened CUDA library cufft64_80.dll locally I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:128] successfully opened CUDA library nvcuda.dll locally I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:128] successfully opened CUDA library curand64_80.dll locally >>> hello = tf.constant('Hello, TensorFlow!') >>> sess = tf.Session() I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:885] Found device 0 with properties: name: GeForce GTX 960M major: 5 minor: 0 memoryClockRate (GHz) 1.176 pciBusID 0000:01:00.0 Total memory: 2.00GiB Free memory: 1.65GiB I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:906] DMA: 0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:916] 0: Y I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 960M, pci bus id: 0000:01:00.0) >>> print(sess.run(hello)) b'Hello, TensorFlow!'

 

참고 : https://www.tensorflow.org/install/install_windows