scripts/aphrody/cuda-torch.ts creates a virtual environment with the embedded UV (uv, aliased to Bun), installs torch from the PyTorch index that matches the CUDA version reported by nvidia-smi, then runs torch.cuda.is_available() through bun python.
bun scripts/aphrody/cuda-torch.ts # detects the driver, installs into ~/.aphrody/venvs/torch-cuda
bun scripts/aphrody/cuda-torch.ts --cuda cu128 # force an index
bun scripts/aphrody/cuda-torch.ts --dry-run # print the commands only
| Driver CUDA | Index |
|---|---|
| 13.0 and up | cu130 |
| 12.8, 12.9 | cu128 |
| older | cu126 |
| Option | Default |
|---|---|
--dir <path> | $APHRODY_HOME/venvs/torch-cuda |
--python <ver> | 3.12 |
--cuda <cuXXX> | detected from the driver |
--cpu | CPU wheels, for servers without GPU |
The script exits with status 3 when a CUDA index was requested and CUDA is not available after the install. Servers use --cpu only.