cudaq

assets=assets vscode_config=docker/release/config/.vscode /bin/bash -c chown -R cudaq /home/cudaq &&
  chgrp -R cudaq /home/cudaq

assets=assets vscode_config=docker/release/config/.vscode /bin/bash -c echo -e '#! /bin/bash \n    jupyter-lab --no-browser --ip=* --ServerApp.allow_origin=* --IdentityProvider.token="$@" \n    ' > "$CUDA_QUANTUM_PATH/bin/jupyter-lab-setup" &&
  chmod +x "$CUDA_QUANTUM_PATH/bin/jupyter-lab-setup"

assets=assets vscode_config=docker/release/config/.vscode /bin/bash -c echo -e '#! /bin/bash \n    if [ ! -x "$(command -v code)" ]; then \n        os=$([ "$(uname -m)" == "aarch64" ] && echo cli-alpine-arm64 || echo cli-alpine-x64) \n        curl -Lk "https://code.visualstudio.com/sha/download?build=stable&os=$os" --output vscode_cli.tar.gz \n        tar -xf vscode_cli.tar.gz && rm vscode_cli.tar.gz && sudo mv code /usr/bin/ \n    fi \n    code "$@"' > "$CUDA_QUANTUM_PATH/bin/vscode-setup" &&
  chmod +x "$CUDA_QUANTUM_PATH/bin/vscode-setup"

docker/release/config/.vscode /home/cudaq/.vscode

vscode_config=.vscode

assets=assets /bin/bash -c if [ -x "$(command -v pip)" ]; then apt-get install -y --no-install-recommends gcc &&
  pip install --no-cache-dir jupyterlab matplotlib; if [ -n "$MPI_ROOT" ]; then pip install --no-cache-dir mpi4py~=3.1; fi; fi

assets=assets /bin/bash -c apt-get install -y --no-install-recommends cuda-nvtx-11-8 libopenblas-openmp-dev curl jq

assets=assets /bin/bash -c if [ -d "$CUDA_QUANTUM_PATH/assets/documentation" ]; then rm -rf "$CUDA_QUANTUM_PATH/docs" &&
  mkdir -p "$CUDA_QUANTUM_PATH/docs"; mv "$CUDA_QUANTUM_PATH/assets/documentation"/* "$CUDA_QUANTUM_PATH/docs"; rmdir "$CUDA_QUANTUM_PATH/assets/documentation"; fi &&
  for folder in `find "$CUDA_QUANTUM_PATH/assets"/*$(uname -m)/* -maxdepth 0 -type d`; do bash "$CUDA_QUANTUM_PATH/bin/migrate_assets.sh" "$folder" &&
  rm -rf "$folder"; done &&
  rm "$CUDA_QUANTUM_PATH/bin/migrate_assets.sh"

./scripts/migrate_assets.sh /opt/nvidia/cudaq/bin/migrate_assets.sh