# Pytorch Training

> Best practices for building robust PyTorch training loops. Use when generating or reviewing ML training code.

- **Type:** Skill
- **Install:** `agentstack add skill-thada2402-autoresearchclaw-pytorch-training`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [thada2402](https://agentstack.voostack.com/s/thada2402)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [thada2402](https://github.com/thada2402)
- **Source:** https://github.com/thada2402/AutoResearchClaw/tree/main/researchclaw/skills/builtin/tooling/pytorch-training

## Install

```sh
agentstack add skill-thada2402-autoresearchclaw-pytorch-training
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

## PyTorch Training Best Practice
1. Use torch.manual_seed() for reproducibility (set for torch, numpy, random)
2. Use DataLoader with num_workers>0 and pin_memory=True for GPU
3. Enable cudnn.benchmark=True for fixed input sizes
4. Use learning rate schedulers (CosineAnnealingLR or OneCycleLR)
5. Implement early stopping based on validation metric
6. Log metrics every epoch, save best model checkpoint
7. Use torch.no_grad() for evaluation
8. Clear gradients with optimizer.zero_grad(set_to_none=True) for efficiency

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [thada2402](https://github.com/thada2402)
- **Source:** [thada2402/AutoResearchClaw](https://github.com/thada2402/AutoResearchClaw)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-thada2402-autoresearchclaw-pytorch-training
- Seller: https://agentstack.voostack.com/s/thada2402
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.