Building environment

# Building environment ###### tags: `ML` ## Displaying Basic System Information on Linux Shell using **`uanme`** command with `-a` return all system information. ``` $ uname -a ``` Get Machine Hardware Architecture ```shell $ uname --m ppc64le ``` Get Operation System Information ```shell $ uname -o GNU/Linux ``` Get Linux kernal version ```shell $ uname -r 4.4.0-142-generic ppc64le ``` Type any one of the following command to find os name and version in Linux: ```shell $ cat /etc/os-release $ lsb_release -a $ hostnamectl ``` ## CUDA 安裝時須注意的幾個問題 - CUDA版本是否支援cuDNN版本 - cuDNN版本是否支援tensorflow版本 - nvidia driver環境變數路徑是否有設定正確 - CUDA路徑是否有設定正確 Check CUDA version ``` $ nvcc --version ``` **To check installation of CUDA, run below command**, if it’s installed properly then below command will not throw any error and will print correct version of library. ``` function lib_installed() { /sbin/ldconfig -N -v $(sed 's/:/ /' <<< $LD_LIBRARY_PATH) 2>/dev/null | grep $1; } function check() { lib_installed $1 && echo "$1 is installed" || echo "ERROR: $1 is NOT installed"; } check libcuda check libcudart ``` ## cuDNN Installation NVDIA cuDNN is a GPU-accelerated library of primitives for deep neural networks. Download the coresponding cuDNN on [cuDNN archive](https://developer.nvidia.com/rdp/cudnn-archive). After download, follow the **installation guide** from [NVDIA SDK Document](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html) **To check installation of CuDNN, run below command**, if CuDNN is installed properly then you will not get any error. ``` function lib_installed() { /sbin/ldconfig -N -v $(sed 's/:/ /' <<< $LD_LIBRARY_PATH) 2>/dev/null | grep $1; } function check() { lib_installed $1 && echo "$1 is installed" || echo "ERROR: $1 is NOT installed"; } check libcudnn ``` ### Test Build Configuration **GPU** |Version|Python version | Compiler | Build tools | cuDNN | CUDA | | ----- | ------------- | -------- | ----------- | ----- | ---- | |tensorflow-2.0.0 | 2.7, 3.3-3.7 | GCC 7.3.1 | Bazel 0.26.1 | 7.4 | 10.0 | tensorflow_gpu-1.14.0 | 2.7, 3.3-3.7 | GCC 4.8 | Bazel 0.24.1 | 7.4 | 10.0 | tensorflow_gpu-1.13.1 | 2.7, 3.3-3.7 | GCC 4.8 | Bazel 0.19.2 | 7.4 | 10.0 | tensorflow_gpu-1.12.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.15.0 | 7 | 9 | tensorflow_gpu-1.11.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.15.0 | 7 | 9 | tensorflow_gpu-1.10.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.15.0 | 7 | 9 | tensorflow_gpu-1.9.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.11.0 | 7 | 9 | tensorflow_gpu-1.8.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.10.0 | 7 | 9 | tensorflow_gpu-1.7.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.9.0 | 7 | 9 | tensorflow_gpu-1.6.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.9.0 | 7 | 9 | tensorflow_gpu-1.5.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.8.0 | 7 | 9 | tensorflow_gpu-1.4.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.5.4 | 6 | 8 | tensorflow_gpu-1.3.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.4.5 | 6 | 8 | tensorflow_gpu-1.2.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.4.5 | 5.1 | 8 | tensorflow_gpu-1.1.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.4.2 | 5.1 | 8 | tensorflow_gpu-1.0.0 | 2.7, 3.3-3.6 | GCC 4.8 | Bazel 0.4.2 | 5.1 | 8 | > [Table refernece: Tensorflow build ](https://www.tensorflow.org/install/source#common_installation_problems) ## install docker ## Install Package ## Install tensorflow ```shell $ conda install -c anaconda tensorflow-gpu ``` ##

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