Can You Solve It?
This text is about the implementation of a graph-level representation learning method called GraphLoG at ICML 2021. The author of a previous paper, Strategies for Pre-training Graph Neural Networks, proposed two methods for pre-training at the node level - Context and Attribute. The article also discusses loading the zinc dataset into the PyG dataset and learning about the DATA class in PyG. Additionally, the article mentions a library called Datamol that is optimized for molecular machine-learning workflows.
I'm currently unable to access in-depth search results for your query. However, based on my knowledge, it appears that the torch_geometric.datasets.zinc
module may not directly possess the num_atom_features
attribute.
To address this, you might need to inspect the documentation for torch_geometric.datasets.zinc
or the source code for the module to determine the correct way to access the number of atom features. Additionally, you may want to explore alternative methods for obtaining the required information from the zinc
dataset.
If you could provide more details about the specific nature of the dataset and the information you are trying to access, I would be better positioned to offer more targeted guidance.
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