0x3327 / starknet-skproof

Scikit-learn compatible Python library for generating ZK proofs of execution on top of Starknet.

SKProof

About

Supported models

• MLPClassifier with ReLU activation function

How it works

Planned improvements

• Code optimization
• Support for more models

Prerequisites

Installation

Installing skproof package is done using pip with command pip install starknet_skproof

Example

Example using Iris dataset and MLPClassifier

from starknet_skproof.mlp.MLPClassifierProver import MLPClassifierProver
from sklearn.neural_network import MLPClassifier
from sklearn.datasets import load_iris

print('Loading dataset...')

# Load test data
iris = load_iris()
X = iris.data
y = iris.target

print('Training MLPClassifier...')

# Train classifier
mlp = MLPClassifier((2,3), activation='relu', max_iter=2000)
mlp.fit(X, y)

# Generate proof for the first row
mlpcp = MLPClassifierProver(
    mlp,
    'src/lib.cairo',
    './zkfloat/zkfloat.cairo',
    7
)

mlpcp.prove(X[:1,:])