# Evidence: The chain rule, Jacobians, and directions

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

## Evidence required

Keep the handwritten Jacobian, JVP and VJP checks, adjoint identity, finite-direction check and stop-gradient diagnosis.

- Command: `python3 phases/04-optimization/07-chain-rule-jacobians-and-directional-derivatives/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