Metadata-Version: 2.4
Name: GConvNet
Version: 0.0.3
Summary: GConvNet
Author-email: sobazino <sobazino@gmail.com>
License: Apache-2.0 license
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: license-file

# GConvNet

GConvNet is a PyTorch module for graph convolution using triplet-based edge structures and dynamic node filtering. It enables higher-order neighborhood modeling via (3×1) convolution over node triplets, and selectively retains important nodes based on degree centrality.

## Features

- Triplet generation from sequential edges
- (3×1) convolution on node feature triplets
- Node filtering by degree
- Simple integration with PyTorch models

## Installation

Install with pip:

```bash
pip install GConvNet
```

## Usage

```python
import torch
from GConvNet import GConvNet

x = torch.rand(8, 4)
edge_index = torch.tensor([[0, 1, 2, 3], [1, 2, 3, 4]])
model = GConvNet(4, 8)
x_out, edge_index_out = model(x, edge_index)
```
