gammagl.datasets.Coauthor

class Coauthor(root: str | None = None, name: str = 'cs', transform: Callable | None = None, pre_transform: Callable | None = None, force_reload: bool = False)

The Coauthor CS and Coauthor Physics networks from the “Pitfalls of Graph Neural Network Evaluation” paper. Nodes represent authors that are connected by an edge if they co-authored a paper. Given paper keywords for each author’s papers, the task is to map authors to their respective field of study.

Parameters:

• root (str, optional) – Root directory where the dataset should be saved.

• name (str, optional) – The name of the dataset ("CS", "Physics").

• transform (callable, optional) – A function/transform that takes in an gammagl.data.Graph object and returns a transformed version. The data object will be transformed before every access. (default: None)

• pre_transform (callable, optional) – A function/transform that takes in an gammagl.data.Graph object and returns a transformed version. The data object will be transformed before being saved to disk. (default: None)

• (bool (force_reload) – (default: False)

• optional) (Whether to re-process the dataset.) – (default: False)

• Stats –

  Name	#nodes	#edges	#features	#classes
  CS	18,333	163,788	6,805	15
  Physics	34,493	495,924	8,415	5

url = 'https://github.com/shchur/gnn-benchmark/raw/master/data/npz/'

property raw_dir: str

property processed_dir: str

property raw_file_names: str

The name of the files in the self.raw_dir folder that must be present in order to skip downloading.

property processed_file_names: str

The name of the files in the self.processed_dir folder that must be present in order to skip processing.

download()

Downloads the dataset to the self.raw_dir folder.

process()

Processes the dataset to the self.processed_dir folder.