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fix gpu launching on AWS #109

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19 changes: 19 additions & 0 deletions README.md
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Expand Up @@ -35,3 +35,22 @@ Videos of hand by Katie Rupp
Here are some references for DeepLabCut and other things this project relies upon:
- Mathis et al, 2018, "DeepLabCut: markerless pose estimation of user-defined body parts with deep learning"
- Romero-Ramirez et al, 2018, "Speeded up detection of squared fiducial markers"

## How to launch Anipose on new versions of TensorFlow 2+ and on GPU and Linux (tested on AWS with Tesla)
I used all instructions from Anipose Installation
Moving from CPU to GPU on Tesla provided 15x speed boost

# Important
Installation tensorflow 2.12.* failed cause python 3.7 is too old, so I selected version from suggested 2.11.0
# Commands
conda install -c conda-forge cudatoolkit=11.8.0
python3 -m pip install nvidia-cudnn-cu11==8.6.0.163 tensorflow==2.12.*
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
source $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh
# Verify install:
python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"

# Instruction originated from here
https://www.tensorflow.org/install/pip