pytorch-graphsage/train.py/ Jump to Cannot retrieve contributors at this time executable file177 lines (140 sloc)5.45 KB RawBlame #!/usr/bin/env python """ train.py """ from__future__importdivision from__future__importprint_function ...
machine-learningresearchdeep-learningtensorflowsklearnpytorchdeepwalktransformerconvolutional-neural-networksgcniclrgraph-representationnode2vecgraph-convolutional-networkgraphsagegraph-neural-networksgraph-convolutiongwnngpt2gpt3 UpdatedMar 18, 2023 Python matenure/FastGCN ...
pytorchversion ofhttps://github.com/williamleif/GraphSAGE There are also a handful of new features, including: scripts for preprocessing data attention-based aggregator sparse edge sampler (eg, don't use the dense 2D edgelist) richer, pluggable preprocessing classes ...
pytorch版本中用的两个数据集都比较小,不是论文里用的数据集。这两个数据集在Kipf 16年经典的GCN论文用到了。节点数量分别约是2700,20000。 cora是一个机器学习论文引用数据集,提供了2708篇论文的引用关系,每篇论文的label是论文所属的领域。label一共七种,包括遗传算法,神经网络,强化学习等7个领域。特征是已经...
2. pytorch-geometric(pyg)介绍 官方仓库:https://github.com/pyg-team/pytorch_geometric 官方文档:PyG Documentation 参考官方文档 2.1 图数据建模 图用于建模对象(节点)之间的成对关系(边)。PyG中的单个图由torch_geometric.data.Data的一个实例描述。默认情况下包含以下属性: ...
[GraphSAGE](https://github.com/williamleif/GraphSAGE)的基本参考PyTorch实现。 这个参考实现对于大图来说没有TensorFlow版本那么快,但是代码更容易阅读,而且在小图的基准上表现得更好(就速度而言)。 该代码也是为了比TensorFlow版本更简单、更可扩展、更容易操作。目前,只有GraphSAGE-mean和GraphSAGE-GCN的监督版本被...
其实看懂了gcn之后,graphsage基本上也能看懂,graphsage一直强调自己是归纳式的,gcn是直推式的,其实gcn稍微改动一下就可以变成归纳式的,所以其实硬说gcn是直推式的其实对于应用来说帮助不大。 从代码实现上来看, https://github.com/dmlc/dgl/blob/master/python/dgl/nn/pytorch/conv/graphconv.pygithub.com/...
Graph Neural Networks (GNNs) for Node Classification using Graph Attention Networks (GAT) and GraphSAGE, implemented in PyTorch and TensorFlow - MohammadHeydari/GraphSAGE-GAT-Cora-Dataset
官方代码:https://github.com/williamleif/graphsage-simple/ 如果我们使用pytorch的PyG也能很方便调用: # -*- coding: utf-8 -*- """ Created on Fri Oct 8 23:16:13 2021 @author: 86493 """ import torch from torch_geometric.datasets import Planetoid from torch_geometric.transforms import Normalize...
Alternative reference PyTorch implementation Overview This directory contains code necessary to run the GraphSage algorithm. GraphSage can be viewed as a stochastic generalization of graph convolutions, and it is especially useful for massive, dynamic graphs that contain rich feature information. See ourpa...