duoan / TorchCode

---
title: TorchCode
emoji: 🔥
colorFrom: red
colorTo: yellow
sdk: docker
app_port: 7860
pinned: false
---
# 🔥 TorchCode
**Crack the PyTorch interview.**
Practice implementing operators and architectures from scratch — the exact skills top ML teams test for.
*An interactive coding platform, but for tensors. Self-hosted. Jupyter-based. Instant feedback.*
---
## 🎯 Why TorchCode?
Top companies (Meta, Google DeepMind, OpenAI, etc.) expect ML engineers to implement core operations **from memory on a whiteboard**. Reading papers isn't enough — you need to write `softmax`, `LayerNorm`, `MultiHeadAttention`, and full Transformer blocks code.
TorchCode gives you a **structured practice environment** with:
| | Feature | |
|---|---|---|
| 🧩 | **41 curated problems** | The most frequently asked PyTorch interview topics |
| ⚖️ | **Automated judge** | Correctness checks, gradient verification, and timing |
| 🎨 | **Instant feedback** | Colored pass/fail per test case, just like competitive programming |
| 💡 | **Hints when stuck** | Nudges without full spoilers |
| 📖 | **Reference solutions** | Study optimal implementations after your attempt |
| 📊 | **Progress tracking** | What you've solved, best times, and attempt counts |
| 🔄 | **One-click reset** | Toolbar button to reset any notebook back to its blank template — practice the same problem as many times as you want |
| | **Open in Colab** | Every notebook has an "Open in Colab" badge + toolbar button — run problems in Google Colab with zero setup |
No cloud. No signup. No GPU needed. Just `make run` — or try it instantly on Hugging Face.
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## 🚀 Quick Start
### Option 0 — Try it online (zero install)
**Launch on Hugging Face Spaces** — opens a full JupyterLab environment in your browser. Nothing to install.
Or open any problem directly in Google Colab — every notebook has an badge.
### Option 0b — Use the judge in Colab (pip)
In Google Colab, install the judge from PyPI so you can run `check(...)` without cloning the repo:
 [code] 
Then in a notebook cell:
 [code] 
### Option 1 — Pull the pre-built image (fastest)
 [code] 
If the registry image is unavailable for your platform, use Option 2 instead. This is the common path on Apple Silicon / `arm64`.
### Option 2 — Build locally
 [code] 
`make run` will try the prebuilt image first and automatically fall back to a local build when needed.
Open ** ** — that's it. Works with both Docker and Podman (auto-detected).
### Option 3 — Standalone Web UI (Next.js + FastAPI)
For a modern, standalone coding experience with an integrated IDE and dual-pane layout:
1. **Start Backend (FastAPI):**
 [code] 
2. **Start Frontend (Next.js):**
 [code] 
3. Open ** ** in your browser.
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## 📋 Problem Set
> **Frequency**: 🔥 = very likely in interviews, ⭐ = commonly asked, 💡 = emerging / differentiator
### 🧱 Fundamentals — "Implement X from scratch"
The bread and butter of ML coding interviews. You'll be asked to write these without `torch.nn`.
| # | Problem | What You'll Implement