rasptorch-cli（rasptorch CLI 命令行）

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 device selection:

- --device auto (default): use GPU when Vulkan is working, else CPU - --device gpu: force GPU (will error / fall back depending on Vulkan availability) - --device cpu: force 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 tensor random --shape 2,3,4 --device cpu --dtype float32
rasptorch --json tensor zeros  --shape 3,4   --device auto
rasptorch --json tensor ones   --shape 5,10  --device gpu

Notes:

• Keep shapes small unless the user explicitly requests large workloads.
• Prefer --device auto unless the user asks to force CPU/GPU.

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.