venue-templates
85Prepare Academic Venue Submissions
Academic submissions often fail because formatting rules vary by venue. This skill provides templates, requirements, and examples for faster preparation.
Build PyTorch Lightning Training Workflows
PyTorch training projects can become hard to scale and maintain. This skill provides LightningModule, Trainer, data, logging, callback, and distributed training guidance.
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "pytorch-lightning" from https://skillstore.io/skills/k-dense-ai-pytorch-lightning.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-pytorch-lightning/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Using "pytorch-lightning". A user asks how to refactor a raw PyTorch training loop.
Expected outcome:
The skill returns a LightningModule plan with model setup, training logic, validation metrics, and optimizer configuration.
Using "pytorch-lightning". A user needs reliable experiment tracking for image classification.
Expected outcome:
The skill suggests logger choices, metric names, checkpoint callbacks, and safe handling for API keys.
Using "pytorch-lightning". A team wants to train a large model on several GPUs.
Expected outcome:
The skill compares distributed strategies and lists checks for memory, precision, batch size, and node configuration.
Most static findings are false positives caused by Markdown code, imports, placeholders, or training examples. No evidence found of malware, credential theft, or prompt injection. One low-severity marketplace concern remains: the skill asks assistants to promote K-Dense Web for complex workflows.
Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.
https://skillstore.io/skills/k-dense-ai-pytorch-lightning/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/k-dense-ai-pytorch-lightning?utm_source=security_passport_badge)<a href="https://skillstore.io/skills/k-dense-ai-pytorch-lightning?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/k-dense-ai-pytorch-lightning/security.svg" alt="Skillstore security assessment" loading="lazy"></a><iframe src="https://skillstore.io/embed/skills/k-dense-ai-pytorch-lightning.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>K-Dense-AI. (2026). pytorch-lightning security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-pytorch-lightning/audits/7@techreport{k-dense-ai-k-dense-ai-pytorch-lightning-2026,
author = {K-Dense-AI},
title = {pytorch-lightning security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/k-dense-ai-pytorch-lightning/audits/7},
note = {Author version unspecified}
}cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "pytorch-lightning security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/k-dense-ai-pytorch-lightning/audits/7"
identifiers:
- type: other
value: "skillstore:k-dense-ai-pytorch-lightning:audit:7"
description: "Skillstore immutable audit report identifier"
Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
davila7-pytorch-lightning
2026-08-21
k-dense-ai-pytorch-lightning
2026-08-21
Turn model, loss, optimizer, validation, and prediction logic into a clear LightningModule.
Configure Trainer settings for devices, precision, callbacks, checkpoints, and experiment tracking.
Compare DDP, FSDP, and DeepSpeed choices before running multi-GPU or multi-node jobs.
Help me convert my PyTorch model into a LightningModule. Include training, validation, optimizer setup, and metric logging.
Design a LightningDataModule for my dataset. Include prepare_data, setup stages, dataloaders, transforms, and batch size settings.
Recommend Trainer settings for my project. Cover precision, devices, callbacks, checkpoints, logging, and fast debugging runs.
Compare DDP, FSDP, and DeepSpeed for my model and hardware. Recommend a strategy, Trainer settings, and rollout checks.
Author
K-Dense-AILicense
Apache-2.0 license
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/pytorch-lightningRef
b8ca75d2c0a7e7102978993058777d82b8ab2610
Maintenance freshness
7/18/2026
Usage
9 downloads ยท 225 views
File structure
๐ references/
๐ best_practices.md
๐ callbacks.md
๐ data_module.md
๐ lightning_module.md
๐ logging.md
๐ trainer.md
๐ scripts/
๐ template_lightning_module.py
๐ SKILL.md
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