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rasptorch

该 Skill 指导以 JSON 方式调用 rasptorch 命令行工具,用于创建张量、查看 Vulkan GPU 可用状态、构建线性/MLP/CNN/GRU/Transformer 模型,并保存、加载与训练模型;模型命令维护会话式注册表,训练和文件写入需用户批准。

joshua-ludolf
joshua-ludolf
热度 39.70
最近更新 2026-05-11 17:43:29
分类:开发依赖:代码执行 / 读写文件应用场景:自动化脚本 / 数据处理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add rasptorch-cli
Metadata
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 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.