# Lab notebook

One file, kept for the whole course. Every lab ends by adding to it. The capstone is written from it.

## Machine

- Track: (S, X, M or N)
- Machine: (model, CPU, GPU or chip, memory, storage)
- Operating system and version:
- Driver, CUDA, ROCm or macOS version:
- Date prepared:

## Environment

- Python version:
- torch version and build (cuda, rocm, mps):
- mlx version (Track M):
- jupyterlab and matplotlib versions:
- accelerator line printed by setup-env.sh, verbatim:
- Other tools and versions, as they are installed:

## Results

Each lab appends one line per run below, as JSON, or a short table with the same fields:
lab, device, tool versions, the settings that produced the number, the number, the date.