https://github.com/storswiftlabs/zkml-noir

zkml based on noir language
https://github.com/storswiftlabs/zkml-noir

Last synced: 3 months ago
JSON representation

zkml based on noir language

• Host: GitHub
• URL: https://github.com/storswiftlabs/zkml-noir
• Owner: storswiftlabs
• License: apache-2.0
• Created: 2023-08-23T07:08:26.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-09-08T07:46:49.000Z (over 1 year ago)
• Last Synced: 2024-04-14T02:08:19.126Z (10 months ago)
• Language: Python
• Size: 95.7 KB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-noir - zkML-Noir - Python ML model Noir transcoding, including various algorithms such as Decision tree, K-Means, XGBoost, FNN, CNN (Libraries / Machine Learning)

README

        
# zkML-Noir

## Description

Python ML model transcoding Noir, including various algorithms such as Decision tree, K-Means, XGBoost, FNN, CNN

## Directory structure

- data: ML model training and prediction data, including raw data and pre-processed data

- model: Three types of ML models

- noir: zkML generated Noir code

- tests: Testcase for zkML transpiler code

- zkml: The zkML code generation and floating point numbers quantize integer numbers

  - decision_tree: Python2Noir generate Noir prediction code for the decision tree based on sk-learn library

  - k_Means: Python2Noir generate Noir prediction code for the center points based on sk-learn library

  - quantization: ML floating point numbers quantize integer numbers

  - routine_code_generate: Routine generate Noir prediction code for the CNN and RNN based on Pytorch library

  - XGBoost: Python2Noir generate Noir prediction code for the XGBoost classification and regression based on XGBoost library

  

## Build guide

- Python 3.7+

- Anaconda

## Import package

- python2noir

- joblib

- scikit-learn

- xgboost

- numpy

- unittest

- pandas

- pytorch

- torchvision

## Usage

```shell

git clone https://github.com/storswiftlabs/zkml-noir.git

cd zkml-noir

# execute decision tree generate code

python  -m unittest tests/zkml/decision_tree/test_decision_tree_to_noir.py

# execute K-Means generate code

python  -m unittest tests/zkml/k_Means/test_k_Means_to_noir.py

# execute XGBoost generate code

python  -m unittest tests/zkml/XGBoost/test_xgboost_to_noir.py

# Train the CNN model

python tests/zkml/cnn/mnist_cnn.py

# execute FNN generate code

python zkml/routine_code_generate/fnn_to_noir.py

# execute CNN generate code

python zkml/routine_code_generate/cnn_to_noir.py

# Load the model and extract inputs

python zkml/routine_code_generate/extract_inputs.py

```