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@@ -1,10 +1,9 @@ | ||
from dataset import Planetoid | ||
from models.homo import SGC | ||
from tasks import NodeClassification | ||
from sgl.dataset import Planetoid | ||
from sgl.models.homo import SGC | ||
from sgl.tasks import NodeClassification | ||
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dataset = Planetoid("pubmed", "./", "official") | ||
model = SGC(prop_steps=3, feat_dim=dataset.num_features, num_classes=dataset.num_classes) | ||
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device = "cuda:0" | ||
test_acc = NodeClassification(dataset, model, lr=0.1, weight_decay=5e-5, epochs=200, device=device).test_acc | ||
print(test_acc) |
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[build-system] | ||
requires = [ | ||
"setuptools>=42", | ||
"wheel" | ||
] | ||
build-backend = "setuptools.build_meta" |
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@@ -1,5 +1,9 @@ | ||
torch==1.11.0 | ||
scipy==1.5.2 | ||
ogb==1.3.3 | ||
numpy==1.22.3 | ||
torch-geometric | ||
torch>=1.8 | ||
networkx | ||
tqdm | ||
numpy>=1.21 | ||
scipy | ||
gensim | ||
scikit_learn | ||
ogb | ||
openbox |
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import setuptools | ||
|
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with open("README.md", "r", encoding="utf-8") as readme: | ||
long_description = readme.read() | ||
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with open("requirements.txt", "r", encoding="utf-8") as require: | ||
requirements = [r for r in require.read().splitlines() if r != ''] | ||
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setuptools.setup( | ||
name="sgl-dair", | ||
version="0.1.0", | ||
author="DAIR Lab @PKU", | ||
description="Graph Neural Network (GNN) toolkit targeting scalable graph learning", | ||
long_description=long_description, | ||
long_description_content_type="text/markdown", | ||
url="https://github.com/PKU-DAIR/SGL", | ||
classifiers=[ | ||
"Programming Language :: Python :: 3", | ||
"License :: OSI Approved :: MIT License", | ||
"Operating System :: OS Independent", | ||
], | ||
packages=setuptools.find_packages(), | ||
python_requires='>=3.6', | ||
install_requires=requirements, | ||
data_files=["requirements.txt"], | ||
) |
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name = "sgl" |
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