diff --git a/README.md b/README.md index 38e6dc02..5da60782 100755 --- a/README.md +++ b/README.md @@ -33,8 +33,8 @@ GraphGallery is a gallery of state-of-the-arts graph neural networks for [TensorFlow 2.x](https://github.com/tensorflow/tensorflow) and [PyTorch](https://github.com/pytorch/pytorch). GraphGallery 0.4.x is a total re-write from previous versions, and some things have changed. # 👀 What's important -Difference between GraphGallery and [pytorch geometric (PyG)](https://github.com/rusty1s/pytorch_geometric), [deep graph library (DGL)](https://github.com/dmlc/dgl), etc... -+ PyG and DGL are just like **TensorFlow**, but GraphGallery is more like **Keras** +Difference between GraphGallery and [Pytorch Geometric (PyG)](https://github.com/rusty1s/pytorch_geometric), [Deep Graph Library (DGL)](https://github.com/dmlc/dgl), etc... ++ PyG and DGL are just like **TensorFlow** while GraphGallery is more like **Keras** + GraphGallery is more friendly to use + GraphGallery is more efficiient @@ -50,7 +50,7 @@ python setup.py install ```bash pip install -U graphgallery ``` -# :octocat: Implementations +# 🤖 Implementations In detail, the following methods are currently implemented: ## Semi-supervised models @@ -216,7 +216,7 @@ model.build() # verbose takes 0, 1, 2, 3, 4 his = model.train(idx_train, idx_val, verbose=1, epochs=100) # test your model -# verbose takes 0, 1 +# verbose takes 0, 1, 2 loss, accuracy = model.test(idx_test, verbose=1) print(f'Test loss {loss:.5}, Test accuracy {accuracy:.2%}') ``` @@ -313,7 +313,7 @@ Test loss 1.0131, Test accuracy 82.20% ``` -# ❓ How to add your custom datasets +# ❓ How to add your datasets This is motivated by [gnn-benchmark](https://github.com/shchur/gnn-benchmark/) ```python from graphgallery.data import Graph @@ -330,13 +330,13 @@ mydataset.to_npz('path/to/mydataset.npz') mydataset = Graph.from_npz('path/to/mydataset.npz') ``` -# ❓ How to define your custom models +# ❓ How to define your models TODO # 😎 More Examples Please refer to the [examples](https://github.com/EdisonLeeeee/GraphGallery/blob/master/examples) directory. -# ⭐ TODO Lists +# ⭐ TODO List - [x] Add PyTorch models support - [ ] Add more GNN models (TF and Torch backend) - [ ] Support for more tasks, e.g., `graph Classification` and `link prediction`