Pseudo Code

# Pseudo Code for Activation Function Evolution Utility (DEAP-based)

# License: CC BY-NC 4.0 (Non-Commercial)



"""

## 🔍 Purpose

Discover optimal activation functions via genetic programming using DEAP, for use in TensorFlow/Keras models.


## 🚀 How It Works

- Uses DEAP to evolve symbolic activation functions

- Benchmarks top candidates against ReLU, Swish, GELU

- Can be configured to plug into any TensorFlow/Keras model


## 📁 Structure

```

project_root/

|- evolution_engine.py       # Core DEAP GP engine

|- activations.py            # Safe primitives and evolved functions

|- benchmark.py              # Benchmarks evolved functions against standard ones

|- keras_model.py            # Example CNN/GPT-like model

|- requirements.txt

```


## 🔐 Licensing

This repository and pseudo code are licensed under:

**Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)**


You may:

- Use, remix, and adapt the code for non-commercial research or personal use


You must:

- Attribute the original author


You may not:

- Use it for commercial purposes without a separate license




## 🛠 Dependencies & Licenses

The utility uses the following open-source packages:


| Package      | License          | Notes                                      |

|--------------|------------------|--------------------------------------------|

| DEAP         | LGPL 3.0         | Must retain attribution                    |

| TensorFlow   | Apache 2.0       | Permissive, commercial use allowed         |

| NumPy        | BSD              | Permissive                                 |

| matplotlib   | PSF (Python Software Foundation) | For optional plotting           |

| psutil       | BSD              | Used for hardware usage measurement        |


None of these licenses conflict with non-commercial open release, but redistribution must retain original licenses.





## 📫 Contact

Questions or license inquiries? machinesmartsor@gmail.com



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