AutoGL
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THUMNLab
An autoML framework & toolkit for machine learning on graphs.
This issue is created to check whether the library has the same performance features with the native implemented models. **WARNING**: This is not the evaluation results of this library. For...
As far as I realize, various representative graph sampling mechanisms (e.g., Neighbor Sampling, GraphSAINT, cluster sampling, etc.) provided by PyTorch-Geometric can be unified as a unified interface, all the provided...
@wondergo2017 I introduce a novel module `preprocessing` in the `autogl.module` package. For now the `preprocessing` module is composed of two submodules, i.e., `feature_engineering` and `structure_engineering`. **The module of `preprocessing` is...
Hello! Thanks for your project! I think that there is a need to add an **extended description of creating your own dataset**. Without references to other sources, since there, too,...
### Overview Add module autogl.module.train.ssl, which will contains many trainers to do self-supervised task. Now, it only have one trainer using GraphCL and do the semi-supervised downstream tasks. And a...
the procedure of import frozen when the backend is selected as PyG. When the backend is selected as DGL, the import of autogl is good. **Environment (please complete the following...
**Describe the bug** When running /autogl/test/nas/node_classification.py with AUTOGL_BACKEND=dgl, I got the following error. ``` Traceback (most recent call last): File "node_classification.py", line 116, in model = algo.search(space, dataset, esti) File...
please upgrade this UserWarnning
