# Evidence: Batch a function with vmap

Copy this template into your own portfolio and fill it after running your modified exercise.

## Evidence required

Keep the shape contract, loop/vmap/matrix equivalence, row/column layout checks, per-example gradient array, and mean-gradient identity under two target sets. Explain what each gradient shape means.

- Command: `python3 phases/02-transforms/03-batch-a-function-with-vmap/code/main.py`
- Working directory: repository root
- Python / JAX / NumPy versions: 
- Hardware and device: 
- My prediction before running: 
- My change to the exercise: 
- Exit code and meaningful output: 
- Why the result supports or contradicts my prediction: 
- Checkpoint result: 
- Artifact link or saved filename: 
- Portfolio status: saved in local workspace