install.sh

#!/usr/bin/env bash

unset PYTORCH_VERSION
# For unittest, nightly PyTorch is used as the following section,
# so no need to set PYTORCH_VERSION.
# In fact, keeping PYTORCH_VERSION forces us to hardcode PyTorch version in config.

set -ex

this_dir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"

eval "$(./conda/Scripts/conda.exe 'shell.bash' 'hook')"
conda activate ./env

# TODO, refactor the below logic to make it easy to understand how to get correct cuda_version.
if [ "${CU_VERSION:-}" == cpu ] ; then
    cudatoolkit="cpuonly"
    version="cpu"
else
    if [[ ${#CU_VERSION} -eq 4 ]]; then
        CUDA_VERSION="${CU_VERSION:2:1}.${CU_VERSION:3:1}"
    elif [[ ${#CU_VERSION} -eq 5 ]]; then
        CUDA_VERSION="${CU_VERSION:2:2}.${CU_VERSION:4:1}"
    fi

    cuda_toolkit_pckg="cudatoolkit"
    if [[ $CUDA_VERSION == 11.6 || $CUDA_VERSION == 11.7 || $CUDA_VERSION == 11.8 || $CUDA_VERSION == 12.1 ]]; then
        cuda_toolkit_pckg="pytorch-cuda"
    fi

    echo "Using CUDA $CUDA_VERSION as determined by CU_VERSION"
    version="$(python -c "print('.'.join(\"${CUDA_VERSION}\".split('.')[:2]))")"
    cudatoolkit="${cuda_toolkit_pckg}=${version}"
fi

printf "Installing PyTorch with %s\n" "${cudatoolkit}"
conda install -y -c "pytorch-${UPLOAD_CHANNEL}" -c nvidia "pytorch-${UPLOAD_CHANNEL}"::pytorch[build="*${version}*"] "${cudatoolkit}"

torch_cuda=$(python -c "import torch; print(torch.cuda.is_available())")
echo torch.cuda.is_available is $torch_cuda

if [ ! -z "${CUDA_VERSION:-}" ] ; then
    if [ "$torch_cuda" == "False" ]; then
        echo "torch with cuda installed but torch.cuda.is_available() is False"
        exit 1
    fi
fi

source "$this_dir/set_cuda_envs.sh"

printf "* Installing torchvision\n"
"$this_dir/vc_env_helper.bat" python setup.py develop