prepare_install_tensorflow.txt

# Instructions for creating a tensorflow environment with GPU support:

# Check if GPU driver and CUDA is installed (you have to install it if not):
nvidia-smi

# Expected output (Nvidia Driver and CUDA should be installed already):
  Fri Apr 28 14:44:14 2023       
  +-----------------------------------------------------------------------------+
  | NVIDIA-SMI 470.182.03   Driver Version: 470.182.03   CUDA Version: 11.4     |
  |-------------------------------+----------------------+----------------------+
  | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
  | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
  |                               |                      |               MIG M. |
  |===============================+======================+======================|
  |   0  Quadro RTX 6000     Off  | 00000000:B3:00.0 Off |                  Off |
  | 33%   28C    P8     5W / 260W |     73MiB / 24211MiB |      0%      Default |
  |                               |                      |                  N/A |
  +-------------------------------+----------------------+----------------------+
                                                                               
  +-----------------------------------------------------------------------------+
  | Processes:                                                                  |
  |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
  |        ID   ID                                                   Usage      |
  |=============================================================================|
  |    0   N/A  N/A      1404      G   /usr/lib/xorg/Xorg                 64MiB |
  |    0   N/A  N/A      1727      G   /usr/bin/gnome-shell                6MiB |
  +-----------------------------------------------------------------------------+

# Create environment with miniconda: 
conda create --name tf python=3.9

# Activate environment:
conda deactivate
conda activate tf

# Install CUDA Toolkit and cuDNN (versions for Tensorflow 2.9.1):
conda install -c conda-forge cudatoolkit==11.2
pip install nvidia-cudnn-cu11==8.8.1.3

# Add environment variables to environment initialization:
mkdir -p $CONDA_PREFIX/etc/conda/activate.d
echo 'CUDNN_PATH=$(dirname $(python -c "import nvidia.cudnn;print(nvidia.cudnn.__file__)"))' >> $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CONDA_PREFIX/lib/:$CUDNN_PATH/lib' >> $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh

# Load environment variables:
conda deactivate
conda activate tf

# Install all required packages:
pip install -r requirements.txt