| name | rasptorch |
| description | Use the rasptorch CLI to create tensors, inspect Vulkan (GPU) availability, build models, and run training. |
| metadata | {"clawdbot":{"os":["windows","linux"],"requires":{"anyBins":["rasptorch","python","py"]}}} |
rasptorch skill
Use this skill when you need to operate rasptorch from an OpenClaw agent by calling its agent-native CLI and consuming JSON output.
Command rule
- Prefer JSON output: always pass
--json when returning results to the user/agent.
- Prefer explicit backend selection:
--backend auto (default): choose best available backend
--backend vulkan: prefer Vulkan backend
--backend opencl: use OpenCL backend
--backend cuda: use CUDA backend (CuPy or PyTorch CUDA provider)
--backend numpy: CPU backend (internal key: cpu)
How to run the CLI
Prefer the installed console script:
rasptorch --json info
If the console script is unavailable, use module invocation from this repo:
python -m rasptorch.CLI.cli --json info
Quick checks (read-only)
Environment + Vulkan status
rasptorch --json info
Key fields:
vulkan_available
vulkan_using_real_gpu
vulkan_status
Tensor workflows
Create tensors
rasptorch --json --backend numpy tensor random --shape 2,3,4 --device cpu --dtype float32
rasptorch --json tensor zeros --shape 3,4 --device auto
rasptorch --json --backend vulkan tensor ones --shape 5,10 --device gpu
Notes:
- Keep shapes small unless the user explicitly requests large workloads.
- Prefer
--backend auto unless the user asks to pin a specific backend.
Model workflows (stateful)
Model commands keep a session-like registry of created models.
Create models
rasptorch --json model linear --input-size 10 --hidden-sizes 32,16 --output-size 2
rasptorch --json model mlp --layers 64,32,16,2
rasptorch --json model cnn --in-channels 3 --out-channels 16,32
rasptorch --json model gru --input-size 8 --hidden-size 32 --num-layers 1
rasptorch --json model transformer --vocab-size 32000 --d-model 256 --num-heads 8 --num-layers 4
List / remove
rasptorch --json model list
rasptorch --json model remove --model-id <model-id>
Save / load (writes files)
Only do this when the user requests it (or approves writing files):
rasptorch --json model save --model-id <model-id> --path ./model.pkl
rasptorch --json model load --path ./model.pkl
Train (writes compute + may take time)
Only run training after user approval.
rasptorch --json model train --model-id <model-id> --epochs 5 --lr 0.001 --batch-size 32 --device auto --optimizer Adam
UI / chat modes
rasptorch ui starts a Streamlit server (long-running). Only launch with user approval.
rasptorch chat starts an interactive REPL. Avoid in automated tool flows.