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PyTorch: reproducible training loops v1.0.0

Use this resource to write reproducible PyTorch training that does not depend on a GPU

New

  • 429 downloads
  • 233 likes
  • 102 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install reproducible-pytorch-training

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent reviews or writes a PyTorch training loop, from data loading to GPU handling and random seeds. You get code that runs on CPU or GPU and reproduces from one run to the next.

Mostly picked by

Updated November 2, 2026

Card for the “PyTorch: reproducible training loops” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: device-agnostic code (CPU or GPU)
  • SKILL.md: reproducibility setup and seed control
  • SKILL.md: explicit shape management and data loading

Good fit for

  • Your training gives different scores from one run to the next
  • Your script only runs on a machine with a GPU

Not for

    Tags

    • pytorch
    • training
    • reproducibility
    • deep learning

    About

    You say

    “Make this training loop reproducible and independent of the GPU.”

    Card for the “PyTorch: reproducible training loops” skill

    Skill published by affaan-m under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to write reproducible PyTorch training that does not depend on a GPU
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md11.5 KB

    Origin and licence

    Listed unmodified

    Author
    affaan-m
    Source
    github.com/affaan-m/ecc/tree/25278e7d7b6cf6e6a4e7a6c8e10f14ff22f0eb5b/skills/pytorch-patterns
    Licence
    MIT

    Notice

    « pytorch-patterns » (affaan-m, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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