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This installation is for:
Ubuntu 22.04
Install the following before installing CERN ROOT TMVA
Miniconda installation
Check your: pip -v list | grep -v "/usr/lib/python3/dist-packages" * This will show you any package installed that is not part of Lambda Stack or Ubuntu (Ideally these other packages should only be in a virtual environment Python venv or Anaconda/Miniconda 1. Install Miniconda: From: https://docs.conda.io/en/latest/miniconda.html#linux-installers Current version for Python 3.10: $ wget https://repo.anaconda.com/miniconda/Miniconda3-py310_22.11.1-1-Linux-x86_64.sh $ bash Miniconda3-py310_22.11.1-1-Linux-x86_64.sh 2. Activate the environment for miniconda to be active: $ . $HOME/.bashrc If you want Miniconda installed but not always active, I would not mix Miniconda with python venv, since Miniconda blocks the default install. I do the following so conda is not always activated, and I can switch between Miniconda and Python venv: (base) $ conda deactivate $ conda config --set auto_activate_base false 3. Create a environment: a. Create from the command line: $ conda create --name tensorrt_quick tensorflow -c nvidia b. Activate the Miniconda environment: $ conda activate tensorrt_quick c. Install other dependencies: $tensorrt_quick) $ pip install pandas scikit-learn matplotlib numpy 4. Run the code: (tensorrt_quick) $ python quick.py * I did not need to set LD_LIBRARY_PATH or anything
Intial setup: Check your: $ pip -v list | grep -v "/usr/lib/python3/dist-packages" * This will show you any package installed that is not part of Lambda Stack or Ubuntu (Ideally these other packages should only be in a virtual environment Python venv or Anaconda/Miniconda Make sure you are not inside of Anaconda/Miniconda $ deactivate # Deactivates python venv environments $ conda deactivate # Deactivates a layer of Anaconda/Minicond keep doing that until there is no (base) or other. 1. Install python3-venv $ sudo apt update $ sudo apt install python3-venv 2. Create a new environment $ python -m venv --system-site-packages myvenv (--system-site-packages allows it to used the default installed packages, and new packages override in the environment and keep them versioned - not affecting the default or versioned environment) 3. Activate the environment: $ ./myvenv/bin/activate 4. Run a simple test with the base install: TF_CPP_MIN_LOG_LEVEL=3 python -c 'import tensorflow as tf; print("\nTensorflow version: ",tf.__version__, "\nTensorflow file: ",tf.__file__) ; print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices("GPU")))' 5. Install packages (like tensorrt). $ pip install nvidia-tensorrt On a older python3.8 release (still the latest 525.60.* driver, CUDA 11.8, tensorflow 11.2), I needed to install $ pip install nvidia-pyindex $ pip install nvidia-tensorrt Other dependencies, just to make sure they are installed (default current version works fine): $ pip install pandas scikit-learn matplotlib numpy 6. The good news is nvidia-tensorrt does install the libraries in the correct place so they are picked up. (By default Anaconda/Miniconda does not for cuDNN, and I need to setup up the LD_LIBRARY_PATH) 7. Run the code: Quietly (without the verbose tensorflow messages): $ TF_CPP_MIN_LOG_LEVEL=3 python quick.py Or by default if you want to see the specifics: $ python quick.py
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Example: joe@box:~/lambda/documentation/lambdastack-python-venv-tensorflow$ python -m venv --system-site-packages myvenv joe@box:~/lambda/documentation/lambdastack-python-venv-tensorflow$ . myvenv/bin/activate (myvenv) joe@box:~/lambda/documentation/lambdastack-python-venv-tensorflow$ (myvenv) joe@box:~/lambda/documentation/lambdastack-python-venv-tensorflow$ TF_CPP_MIN_LOG_LEVEL=3 python -c 'import tensorflow as tf; print("\nTensorflow version: ",tf.__version__, "\nTensorflow file: ",tf.__file__) ; print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices("GPU")))' Tensorflow version: 2.10.1 Tensorflow file: /usr/lib/python3/dist-packages/tensorflow/__init__.py Num GPUs Available: 2 * Note if it is not seeing your GPUs, you have a basic issue 1. Check: nvidia-smi Then install other packages that you need customized. (myvenv) joe@tensorbook-server:~$ pip install nvidia-pyindex (myvenv) joe@tensorbook-server:~$ pip install nvidia-tensorrt (myvenv) joe@tensorbook-server:~$ TF_CPP_MIN_LOG_LEVEL=3 python quick.py * quiet run output (myvenv) joe@tensorbook-server:~$ python quick.py * verbose output
Installation of ROOT:
Build from source using - https://root.cern/install/build_from_source/
prerequisits
sudo apt-get install gfortran libpcre3-dev xlibmesa-glu-dev libglew1.5-dev libftgl-dev libmysqlclient-dev libfftw3-dev libcfitsio-dev graphviz-dev libavahi-compat-libdnssd-dev libldap2-dev python-dev libxml2-dev libkrb5-dev libgsl0-dev qtwebengine5-dev
sudo apt-get install libxft-dev
sudo apt-get install libxext-dev
$git clone --branch latest-stable --depth=1 https://github.com/root-project/root.git root_src
$mkdir <builddir> <installdir>
$cd <builddir>
cmake -DCMAKE_INSTALL_PREFIX=/home/dir/root_inst -Dcuda=ON -Dcudnn=ON -Dtmva-gpu=ON -Dtmva-cpu=ON /home/dustin/root_src/
cmake --build . --target install j5
source /home/dustin/root_inst/bin/thisroot.sh