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如何使用virtualenv安装软件包,但仍然使用系统tensorflow安装

google-dl-platform virtualenv tensorflow

John Allard · 技术社区 · 6 年前

tensorflow
keras
h5py
requests
pillow
tensorflow-hub

我也试过了 --system-site-packages 标志,并表示tensorflow已经安装,但随后它停止使用GPU。

假设我做了以下几件事

$ virtualenv --sysem-site-packages venv/
$ source venv/bin/activate
$ pip install -r requirements.txt
Collecting tensorflow (from -r requirements.txt (line 1))
  Using cached https://files.pythonhosted.org/packages/1a/c4/8cb95df0bf06089014259b25997c3921a87aa08e2cd981417d91ca92f7e9/tensorflow-1.10.1-cp27-cp27mu-manylinux1_x86_64.whl
Requirement already satisfied: keras in /usr/local/lib/python2.7/dist-packages (from -r requirements.txt (line 2)) (2.2.2)
Requirement already satisfied: h5py in /usr/lib/python2.7/dist-packages (from -r requirements.txt (line 3)) (2.7.0)
Requirement already satisfied: requests in /usr/lib/python2.7/dist-packages (from -r requirements.txt (line 4)) (2.12.4)
Requirement already satisfied: pillow in /usr/lib/python2.7/dist-packages (from -r requirements.txt (line 5)) (4.0.0)
Requirement already satisfied: tensorflow-hub in /home/john/.local/lib/python2.7/site-packages (from -r requirements.txt (line 6)) (0.1.1)
Collecting numpy<=1.14.5,>=1.13.3 (from tensorflow->-r requirements.txt (line 1))
  Using cached https://files.pythonhosted.org/packages/6a/a9/c01a2d5f7b045f508c8cefef3b079fe8c413d05498ca0ae877cffa230564/numpy-1.14.5-cp27-cp27mu-manylinux1_x86_64.whl
Requirement already satisfied: grpcio>=1.8.6 in /usr/local/lib/python2.7/dist-packages (from tensorflow->-r requirements.txt (line 1)) (1.14.1)
Requirement already satisfied: protobuf>=3.6.0 in /home/john/.local/lib/python2.7/site-packages (from tensorflow->-r requirements.txt (line 1)) (3.6.1)
Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python2.7/dist-packages (from tensorflow->-r requirements.txt (line 1)) (1.1.0)
Requirement already satisfied: backports.weakref>=1.0rc1 in /usr/local/lib/python2.7/dist-packages (from tensorflow->-r requirements.txt (line 1)) (1.0.post1)
Requirement already satisfied: absl-py>=0.1.6 in /usr/local/lib/python2.7/dist-packages (from tensorflow->-r requirements.txt (line 1)) (0.3.0)
Requirement already satisfied: wheel in ./venv/lib/python2.7/site-packages (from tensorflow->-r requirements.txt (line 1)) (0.31.1)
Requirement already satisfied: tensorboard<1.11.0,>=1.10.0 in /usr/local/lib/python2.7/dist-packages (from tensorflow->-r requirements.txt (line 1)) (1.10.0)
Requirement already satisfied: six>=1.10.0 in /home/john/.local/lib/python2.7/site-packages (from tensorflow->-r requirements.txt (line 1)) (1.11.0)
Requirement already satisfied: gast>=0.2.0 in /usr/local/lib/python2.7/dist-packages (from tensorflow->-r requirements.txt (line 1)) (0.2.0)
Requirement already satisfied: mock>=2.0.0 in /usr/lib/python2.7/dist-packages (from tensorflow->-r requirements.txt (line 1)) (2.0.0)
Requirement already satisfied: enum34>=1.1.6 in /usr/lib/python2.7/dist-packages (from tensorflow->-r requirements.txt (line 1)) (1.1.6)
Requirement already satisfied: astor>=0.6.0 in /usr/local/lib/python2.7/dist-packages (from tensorflow->-r requirements.txt (line 1)) (0.7.1)
Collecting setuptools<=39.1.0 (from tensorflow->-r requirements.txt (line 1))
  Using cached https://files.pythonhosted.org/packages/8c/10/79282747f9169f21c053c562a0baa21815a8c7879be97abd930dbcf862e8/setuptools-39.1.0-py2.py3-none-any.whl
Requirement already satisfied: pyyaml in /usr/lib/python2.7/dist-packages (from keras->-r requirements.txt (line 2)) (3.12)
Requirement already satisfied: scipy>=0.14 in /usr/lib/python2.7/dist-packages (from keras->-r requirements.txt (line 2)) (0.18.1)
Requirement already satisfied: keras-applications==1.0.4 in /usr/local/lib/python2.7/dist-packages (from keras->-r requirements.txt (line 2)) (1.0.4)
Requirement already satisfied: keras-preprocessing==1.0.2 in /usr/local/lib/python2.7/dist-packages (from keras->-r requirements.txt (line 2)) (1.0.2)
Requirement already satisfied: futures>=2.2.0 in /usr/local/lib/python2.7/dist-packages (from grpcio>=1.8.6->tensorflow->-r requirements.txt (line 1)) (3.2.0)
Requirement already satisfied: markdown>=2.6.8 in /usr/lib/python2.7/dist-packages (from tensorboard<1.11.0,>=1.10.0->tensorflow->-r requirements.txt (line 1)) (2.6.8)
Requirement already satisfied: werkzeug>=0.11.10 in /usr/lib/python2.7/dist-packages (from tensorboard<1.11.0,>=1.10.0->tensorflow->-r requirements.txt (line 1)) (0.11.15)
tensorflow-serving-api 1.10.0 has requirement protobuf==3.6.0, but you'll have protobuf 3.6.1 which is incompatible.
Installing collected packages: numpy, setuptools, tensorflow
  Found existing installation: numpy 1.15.1
    Not uninstalling numpy at /home/john/.local/lib/python2.7/site-packages, outside environment /home/john/retrain/venv
    Can't uninstall 'numpy'. No files were found to uninstall.
  Found existing installation: setuptools 40.2.0
    Uninstalling setuptools-40.2.0:
      Successfully uninstalled setuptools-40.2.0
Successfully installed numpy-1.14.5 setuptools-39.1.0 tensorflow-1.10.1

2 回复 | 直到 6 年前

Viacheslav V Kovalevskyi 6 年前

不幸的是,没有为CPU和GPU优化的tensorflow的“胖”二进制文件。不过,在这两种情况下都可以使用tensorflow gpu。

在仅CPU实例上安装tensorflow gpu

事实上,在没有gpu的情况下,可以在实例上使用tensoflow gpu二进制文件。为了使用它,您需要在实例上安装CUDA和CuDNN(即使实例没有nvidiagpu)。CUDA,inside有一个模拟(存根)Nvidia驱动程序,允许CUDA和CuDNN在CPU上工作,为了在linux上使用它,您需要运行以下命令:

sudo ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/libcuda.so.1
sudo ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/libcuda.so

假设 /usr/local/cuda CUDA的安装路径(在不同平台上可能不同)。一旦这是一个真正可以安装和使用TensorFlowGPU上的CPU只有实例完成。

我知道这看起来像一个黑客,甚至可能在某些平台上不起作用,但至少在某种程度上,它使使用相同的工具成为可能要求.txt甚至GPU和非GPU实例上的相同二进制文件。

Corey Goldberg 6 年前

在您的需求文件中,您有 tensorflow 列出的包,这是仅限CPU的包。要获得GPU支持,请安装 tensorflow-gpu 相反。