Post date: 2017/05/04 5:51:10
# yum -y install python-pip python-devel # yum -y install gcc gcc-c++ python-pip python-devel atlas atlas-devel gcc-gfortran openssl-devel libffi-devel $ pip install --upgrade virtualenv $ virtualenv --system-site-packages ~/venvs/tensorflow $ source ~/venvs/tensorflow/bin/activate (tensorflow) $ pip install --upgrade numpy scipy wheel cryptography (tensorflow) $ pip install --upgrade tensorflow-gpu Collecting tensorflow-gpu Downloading tensorflow_gpu-1.1.0-cp27-cp27mu-manylinux1_x86_64.whl (84.1MB) ... (tensorflow) $ python >>> import tensorflow as tf ... ImportError: libcudnn.so.5: cannot open shared object file: No such file or directory Failed to load the native TensorFlow runtime. See https://www.tensorflow.org/install/install_sources#common_installation_problems for some common reasons and solutions. Include the entire stack trace above this error message when asking for help. >>> $ tar zxvf cudnn-8.0-linux-x64-v5.0.solitairetheme8 # cp -a lib64/* /usr/local/cuda/lib64/ # cp -a include/cudnn.h /usr/local/cuda/include/ $ source ~/venvs/tensorflow/bin/activate (tensorflow) $ python Python 2.7.5 (default, Nov 6 2016, 00:28:07) [GCC 4.8.5 20150623 (Red Hat 4.8.5-11)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import tensorflow as tf >>> hello = tf.constant('Hello, TensorFlow!') >>> sess = tf.Session() 2017-05-04 16:26:03.801993: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 2017-05-04 16:26:03.802038: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 2017-05-04 16:26:03.802049: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. ... >>> print(sess.run(hello)) Hello, TensorFlow! >>> ^D (tensorflow) $ deactivate $ Ref: