TensorFlow: Use GPU 使用GPU运行Tenso

作者: 正在学习的Yuki | 来源:发表于2019-07-08 00:07 被阅读3次

    使用GPU运行TensorFlow

    System Information

    • OS: Windows 10
    • GPU: NVIDIA GeForce 930M (Compute Capability = 5.0)
    • CUDA/cuDNN version: 10
    • Python version: 3.7 (Use Anaconda3 env)
    • TensorFlow version: tensorflow-gpu 1.13.1

    Step1: 检查硬件

    硬件要求:NVIDIA® GPU card with CUDA® Compute Capability 3.5 or higher.

    1. 确认电脑配备GPU
    • 打开 设备管理器 (Device Manager)
    • 展开 显示适配器 (Display adapters)
    • 确认及查看 GPU型号 (我的是NVIDIA GeForce 930M)


      GPU.png
    2. 查看GPU的计算能力(需>=3.5)

    See the list of CUDA-enabled GPU cards.
    e.g. NVIDIA GeForce 930M是

    GPU_ComputeCapability.png

    Step2: 安装软件

    软件要求:

    一些建议:

    1. NVIDIA® GPU drivers:更新driver

    设备管理器 -> GPU 右键 属性 -> Driver 栏 -> Update Driver


    UpdateDriver.png
    2. CUDA Toolkit:10.0 (9.0或以上)

    安装:https://developer.nvidia.com/cuda-toolkit-archive

    3. cuDNN

    Download cuDNN v7.6.1 (June 24, 2019), for CUDA 10.0
    All versions here

    Step3: 添加环境变量

    将CUDA, CUPTI, cuDNN 路径 加到 系统环境变量PATH 中。
    Terminal command:

    SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0\bin;%PATH%
    SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0\extras\CUPTI\libx64;%PATH%
    SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0\include;%PATH%
    SET PATH=C:\tools\cuda\bin;%PATH%
    

    Step4: 安装 tensorflow-gpu (in Anaconda Prompt)

    1. 创建一个python3.7的环境

    教程:https://www.jianshu.com/p/64b94a6a7e98

    2. 激活环境

    conda activate [env_name]

    3. 安装tensorflow-gpu1.13.1

    建议先 uninstall tensorflow cpu: pip uninstall tensorflow
    再安装 tensorflow-gpu1.13.1: pip install tensorflow-gpu==1.13.1

    Step5: 测试

    '''test.py'''
    
    import tensorflow as tf
    
    import os
    os.environ['CUDA_VISIBLE_DEVICES'] = "0" # 设置GPU DEVICE为0 (单显卡)
    
    print("GPU Available: ", tf.test.is_gpu_available()) 
    # 若成功,会返回:
    # GPU Available:  True
    

    在Terminal中运行成功:


    RunningSuccess_Terminal.png

    用Pycharm出现的问题

    1. Configuration

    PyCharm: Configure a Conda virtual environment
    PyCharm: Setting an existing project interpreter

    2. Import Error
    PYCHARM from . import _mklinit 
    ImportError: DLL load failed: The specified module could not be found.
    
    解决方法: Update Driver (见Step2.1)
    3. CUDA Error
    E tensorflow/stream_executor/cuda/cuda_driver.cc:318] failed call to cuInit:
    CUDA_ERROR_UNKNOWN: unknown error
    
    解决方法 (Refer to Guilherme Melo's advice):
    • 打开 Anaconda Prompt:
    source activate [env_name]
    conda install -c conda-forge conda-wrappers
    
    • 改变Pycharm中 Interpreter path:
      将原本的 <env>/python.exe 改为 <env>/Scripts/wrappers/conda/python.bat
    Edit_InterpreterPath.png

    最后终于在PyCharm中运行成功啦:


    RunningSuccess_Terminal.png

    参考来源:https://www.tensorflow.org/install/gpu
    有问题欢迎留言讨论

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