Understand the project
Practical overview
When it fits
Use it for focused, hands-on tensor practice when you want to reason through operations rather than call the corresponding library function.
Who it is for
- Learners practising PyTorch tensor programming
- Programmers who want to understand broadcasting, indexing and tensor manipulation from first principles
Documented uses
- Practise expressing familiar array operations as constrained tensor code.
- Work through examples involving sums, outer products, diagonals and identity matrices.
- Build intuition for broadcasting and tensor shapes.
Before you choose
Requirements & limits
The repository is public and identifies its license as MIT. Its README recommends running the notebook in Google Colab.
- Each puzzle must be solved in one line of code under 80 columns.
- The rules allow arithmetic, comparisons, matrix multiplication, shape access, indexing and earlier puzzle functions, while excluding operations such as sum, view and squeeze.
- The notebook imports PyTorch, NumPy and torchtyping, and uses repository helper code.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Source-based practical guide
Open the puzzle notebook in Colab
Start from the project’s notebook in Google Colab.
Before you start
- Access to Google Colab
- The Tensor Puzzlers notebook linked from the repository README
Steps
Open the README’s Open in Colab notebook link.
Copy the notebook to get started.
Expected outcome
A copied notebook containing the tensor puzzles.
Guide limitations
- The README’s start instructions cover opening and copying the notebook; they do not describe further notebook setup.
Evidence and transparency
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 14 October 2026
- Original website title
- srush/Tensor-Puzzles · Official homepage title · retained in its source language