Python GAT.train示例

示例#1

文件： GAT.py 项目： Jagadambass/Graph-Neural-Networks

import torch
import dgl
import graphgallery

print("GraphGallery version: ", graphgallery.__version__)
print("Torch version: ", torch.__version__)
print("DGL version: ", dgl.__version__)
'''
Load Datasets
- cora/citeseer/pubmed
'''
from graphgallery.datasets import Planetoid
data = Planetoid('cora', root="~/GraphData/datasets/", verbose=False)
graph = data.graph
splits = data.split_nodes()

graphgallery.set_backend("dgl")

from graphgallery.gallery import GAT
trainer = GAT(graph, device="gpu",
              seed=123).process(attr_transform="normalize_attr").build()
his = trainer.train(splits.train_nodes,
                    splits.val_nodes,
                    verbose=1,
                    epochs=200)
results = trainer.test(splits.test_nodes)
print(f'Test loss {results.loss:.5}, Test accuracy {results.accuracy:.2%}')

示例#2

文件： GAT.py 项目： kisekizzz/GraphGallery

#!/usr/bin/env python
# coding: utf-8

import graphgallery 
import tensorflow as tf

graphgallery.set_memory_growth()

print("GraphGallery version: ", graphgallery.__version__)
print("TensorFlow version: ", tf.__version__)

'''
Load Datasets
- cora/citeseer/pubmed
'''
from graphgallery.datasets import Planetoid
data = Planetoid('cora', root="~/GraphData/datasets/", verbose=False)
graph = data.graph
splits = data.split_nodes()

from graphgallery.gallery import GAT
model = GAT(graph, attr_transform="normalize_attr", device="gpu", seed=123)
model.build()
his = model.train(splits.train_nodes, splits.val_nodes, verbose=1, epochs=100)
results = model.test(splits.test_nodes) 
print(f'Test loss {results.loss:.5}, Test accuracy {results.accuracy:.2%}')