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vinn-offline

Routes VINN feature caching and non-interactive k-selection workflows for ACT++ BYOL/ResNet episode features.

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来源信息

仓库
VectorSpaceLab/AREX-Skill
最近来源活动
2026年8月26日 16:31
检测到的 SKILL.md 语言
英语
星标
12
分支
2

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默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。

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SKILL.md
来源说明 · 只读预览
name
vinn-offline
description
Routes VINN feature caching and non-interactive k-selection workflows for ACT++ BYOL/ResNet episode features.
disable-model-invocation
true
metadata
{"disco-role":"operating"}
license
MIT
# vinn-offline Use this sub-skill when the task is about caching image features for VINN or choosing a k value from cached episode features. ## Typical triggers - "Cache BYOL features for the simulated cube dataset" - "Choose k for VINN" - "How are feature files named?" - "Why does the raw k-selection script stop in IPython?" ## What this sub-skill covers - Feature caching from per-camera ResNet18 checkpoints. - Feature-file naming and layout for simulated and cotrain variants. - Offline nearest-neighbor k selection over cached features. - CUDA requirements and dataset-index assumptions for VINN preprocessing. ## What it excludes - ACT/CNNMLP/Diffusion training and eval -> [policy-training](../policy-training/SKILL.md). - Simulation episode generation / replay / visualization -> [simulation-data](../simulation-data/SKILL.md). - Real-robot VINN deployment -> root troubleshooting only. ## Read these first - [Workflow recipes](references/workflows.md) - [Troubleshooting](references/troubleshooting.md) - [Data formats](../../references/data-formats.md) ## Run this helper first Before a long cache or k-selection job, use [check_vinn_stack.py](scripts/check_vinn_stack.py) to confirm the repo checkout imports and the CUDA backend is visible.
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