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pytorch SKILL.md skillA

pytorch from yuecao365/offercome is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add yuecao365/offercome/pytorch@git:20260920.a4843f5

Pins git:20260920.a4843f5 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
yuecao365/offercome
Path
src/lib/mock-interviews/skills/pytorch/SKILL.md
Versions recorded
1
Latest version
git:20260920.a4843f5, committed Sep 20, 2026
Size
11,798 bytes
Repository stars
24
License
MIT

PyTorch 怎么面：自动求导、训练循环、数据管道、分布式训练、混合精度。JD 点名 PyTorch 时读。.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

## 面试官在意什么

PyTorch 是深度学习与大模型训练的默认框架，凡是简历上写"深度学习""模型训练""大模型微调"的候选人几乎都要过这一关。真实面试里 PyTorch 题分两档：一档是"会不会用"——张量操作、autograd、写训练循环、DataLoader；另一档是"能不能把训练跑快跑稳"——GPU 利用率低怎么查、显存 OOM 怎么省、多卡训练怎么配、loss 出 NaN 怎么办。面试官最在意的是候选人是否真正踩过坑：eval 忘了 no_grad、DDP 各卡 loss 不同步、DataLoader 成为瓶颈、混合精度溢出——这些都是能把"跟着教程跑过"和"独立训练过模型"区分开的点。

校招侧重基础机制：计算图怎么建、backward 做了什么、in-place 操作为什么会报错、train/eval 模式区别、手写一个完整训练循环；社招侧重工程效率：性能剖析、分布式训练（DDP/FSDP）、显存优化（checkpointing、混合精度、优化器状态分片）、torch.compile 的收益与坑、模型导出与推理部署。大模型方向额外追 FSDP 分片策略、序列并行、长序列训练的显存账。

怎么问才像这个方向的面试官：
- 所有题都从一个异常现象切入（NaN、OOM、hang、慢、结果不一致），考排查顺序与原理，不考 API 拼写。
- 必须问显存账和吞吐数字：候选人说"优化了训练"，追优化前后的具体数值和测量方法。
- 规模要与候选人项目匹配：单卡跑 ResNet 的候选人不问 FSDP 分片策略，训过 7B 以上模型的必须追分布式细节。
- torch.compile、FSDP2 等新特性只考"用过的坑"，不考版本差异。

## 项目 / 实习怎么深挖

简历上出现下面这类经历时从哪里切、追什么。追到候选人能说出机制、数字的来源与一次真实的故障或取舍才算实；只有框架名与结论、说不出自己那一段的，记为危险信号。通用的追问方法见 project-deep-dive。

- 简历出现"训练 X 模型" → 追多少卡、多久、GPU 利用率多少、遇到的最大工程问题
- 简历出现 DDP / FSDP / DeepSpeed → 追分片策略、通信瓶颈、显存账、出过什么 hang 或不一致
- 简历出现"显存优化 / 大 batch" → 追用了什么手段、速度代价、怎么验证效果不变
- 简历出现混合精度 → 追 FP16 还是 BF16、有没有 NaN、哪些层保留 FP32
- 简历出现"训练加速 X 倍" → 追优化前后 profiler 数据、瓶颈在哪、改了什么
- 简历出现模型部署 / ONNX / TensorRT → 追导出遇到的算子问题、精度对比、延迟数据
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add yuecao365/offercome/pytorch@sha256:da3b0b7cba7c0cc1

The line at the top of this page pins the label git:20260920.a4843f5, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_njff62et4tcd6dov.svg)](https://markdownregistry.com/a/art_njff62et4tcd6dov)

5 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Sep 20, 2026.

versioncommittedcommitsizeaudit
git:20260920.a4843f5 latest2026-09-20 a4843f5 11,798 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (11798 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

yuecao365/offercome · 24 stars · license MIT · pushed 2026-10-01 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_njff62et4tcd6dov
GET https://markdownregistry.com/api/v1/resolve?ref=yuecao365/offercome/pytorch
GET https://markdownregistry.com/api/v1/blob/da3b0b7cba7c0cc1779fd638a950ed78e7d8ed799dfe1cffa267d59a78859cf8

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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