diff options
| -rwxr-xr-x | configure | 8 | ||||
| -rw-r--r-- | tensorflow/g3doc/get_started/os_setup.md | 24 |
2 files changed, 16 insertions, 16 deletions
@@ -64,12 +64,12 @@ while true; do # Retry done -# Find out where the CUDNN library is installed +# Find out where the cuDNN library is installed while true; do fromuser="" if [ -z "$CUDNN_INSTALL_PATH" ]; then default_cudnn_path=${CUDA_TOOLKIT_PATH} - read -p "Please specify the location where CUDNN 6.5 V2 library is installed. Refer to README.md for more details. [Default is $default_cudnn_path]: " CUDNN_INSTALL_PATH + read -p "Please specify the location where cuDNN v2 library is installed. Refer to README.md for more details. [Default is $default_cudnn_path]: " CUDNN_INSTALL_PATH fromuser="1" if [ -z "$CUDNN_INSTALL_PATH" ]; then CUDNN_INSTALL_PATH=$default_cudnn_path @@ -81,7 +81,7 @@ while true; do if [ -e "$CUDNN_INSTALL_PATH/libcudnn.so.6.5" -o -e "$CUDNN_INSTALL_PATH/lib64/libcudnn.so.6.5" ]; then break fi - echo "Invalid path to CUDNN 6.5 V2 toolkit. Neither of the following two files can be found:" + echo "Invalid path to cuDNN v2 toolkit. Neither of the following two files can be found:" echo "$CUDNN_INSTALL_PATH/lib64/libcudnn.so.6.5" echo "$CUDNN_INSTALL_PATH/libcudnn.so.6.5" if [ -z "$fromuser" ]; then @@ -96,7 +96,7 @@ cat > third_party/gpus/cuda/cuda.config <<EOF # at the moment. CUDA_TOOLKIT_PATH="$CUDA_TOOLKIT_PATH" -# CUDNN_INSTALL_PATH refers to the CUDNN toolkit. The cudnn header and library +# CUDNN_INSTALL_PATH refers to the cuDNN toolkit. The cuDNN header and library # files can be either in this directory, or under include/ and lib64/ # directories separately. CUDNN_INSTALL_PATH="$CUDNN_INSTALL_PATH" diff --git a/tensorflow/g3doc/get_started/os_setup.md b/tensorflow/g3doc/get_started/os_setup.md index 9efb183bf8..4484486ff8 100644 --- a/tensorflow/g3doc/get_started/os_setup.md +++ b/tensorflow/g3doc/get_started/os_setup.md @@ -8,8 +8,8 @@ github source. The TensorFlow Python API currently supports Python 2.7 and Python 3.3+ from source. -The GPU version (Linux only) currently requires the Cuda Toolkit 7.0 and CUDNN -6.5 V2. Please see [Cuda installation](#optional-install-cuda-gpus-on-linux). +The GPU version (Linux only) currently requires the Cuda Toolkit 7.0 and cuDNN +v2. Please see [Cuda installation](#optional-install-cuda-gpus-on-linux). ## Overview @@ -30,7 +30,7 @@ images are listed in the corresponding installation sections. If you encounter installation errors, see [common problems](#common-problems) for some solutions. -## Pip Installation +## Pip Installation [Pip](https://en.wikipedia.org/wiki/Pip_(package_manager)) is a package management system used to install and manage software packages written in @@ -219,12 +219,12 @@ $ path/to/repo/tensorflow/tools/docker/docker_run_gpu.sh b.gcr.io/tensorflow/ten You can now [test your installation](#test-the-tensorflow-installation) within the Docker container. -## Test the TensorFlow installation +## Test the TensorFlow installation ### (Optional, Linux) Enable GPU Support If you installed the GPU version of TensorFlow, you must also install the Cuda -Toolkit 7.0 and CUDNN 6.5 V2. Please see [Cuda installation](#optional-install-cuda-gpus-on-linux). +Toolkit 7.0 and cuDNN v2. Please see [Cuda installation](#optional-install-cuda-gpus-on-linux). You also need to set the `LD_LIBRARY_PATH` and `CUDA_HOME` environment variables. Consider adding the commands below to your `~/.bash_profile`. These @@ -331,7 +331,7 @@ binary path. $ sudo apt-get install python-numpy swig python-dev ``` -#### Configure the installation +#### Configure the installation Run the `configure` script at the root of the tree. The configure script asks you for the path to your python interpreter and allows (optional) @@ -344,10 +344,10 @@ $ ./configure Please specify the location of python. [Default is /usr/bin/python]: ``` -#### Optional: Install CUDA (GPUs on Linux) +#### Optional: Install CUDA (GPUs on Linux) In order to build or run TensorFlow with GPU support, both Cuda Toolkit 7.0 and -CUDNN 6.5 V2 from NVIDIA need to be installed. +cuDNN v2 from NVIDIA need to be installed. TensorFlow GPU support requires having a GPU card with NVidia Compute Capability >= 3.5. Supported cards include but are not limited to: @@ -363,11 +363,11 @@ https://developer.nvidia.com/cuda-toolkit-70 Install the toolkit into e.g. `/usr/local/cuda` -##### Download and install CUDNN Toolkit 6.5 +##### Download and install cuDNN v2 https://developer.nvidia.com/rdp/cudnn-archive -Uncompress and copy the cudnn files into the toolkit directory. Assuming the +Uncompress and copy the cuDNN files into the toolkit directory. Assuming the toolkit is installed in `/usr/local/cuda`: ``` bash @@ -376,7 +376,7 @@ sudo cp cudnn-6.5-linux-x64-v2/cudnn.h /usr/local/cuda/include sudo cp cudnn-6.5-linux-x64-v2/libcudnn* /usr/local/cuda/lib64 ``` -##### Configure TensorFlow's canonical view of Cuda libraries +##### Configure TensorFlow's canonical view of Cuda libraries When running the `configure` script from the root of your source tree, select the option `Y` when asked to build TensorFlow with GPU support. @@ -389,7 +389,7 @@ GPU support will be enabled for TensorFlow Please specify the location where CUDA 7.0 toolkit is installed. Refer to README.md for more details. [default is: /usr/local/cuda]: /usr/local/cuda -Please specify the location where CUDNN 6.5 V2 library is installed. Refer to +Please specify the location where the cuDNN v2 library is installed. Refer to README.md for more details. [default is: /usr/local/cuda]: /usr/local/cuda Setting up Cuda include |