Metadata-Version: 2.1
Name: pytulpa
Version: 0.0.1
Summary: A powerful and flexible neural network library
Author: FOLKY ROBOTICS
Author-email: folkyrobotics@gmail.com
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.18.0

# PyTulpa

PyTulpa is a powerful and flexible neural network library that provides tools for building and training various types of neural networks, including Liquid Neural Networks (LNNs).

## Features

- Easy-to-use API for creating and training neural networks
- Support for Liquid Neural Networks (LNNs)
- Various optimization algorithms (SGD, Adam)
- Multiple activation functions (tanh, ReLU, sigmoid)
- Loss functions (MSE, Cross-Entropy)

## Installation

You can install PyTulpa using pip: pip install pytulpa

## Usage

```python
import numpy as np
from pytulpa import PyTulpa, LNN, Adam, mse

# Create a random dataset
X = np.random.randn(100, 10)
y = np.random.randn(100, 1)

# Create a Liquid Neural Network
model = LNN(input_size=10, hidden_size=20, output_size=1)

# Create an optimizer
optimizer = Adam(learning_rate=0.01)

# Create a PyTulpa instance
pt = PyTulpa()

# Compile the model
pt.compile(model=model, optimizer=optimizer, loss_fn=mse)

# Train the model
history = pt.train(X, y, epochs=100, batch_size=32)

# Make predictions
predictions = pt.predict(X)
```
