r""" Parameters ---------- x : torch.Tensor Tensor of input features. adj : list of torch.SparseTensor

r""" Parameters ---------- mean : torch.Tensor Tensor of mean of input features. var : torch.Tensor, optio

r""" Description ----------- Get index under the inductive training setting. Parameters ---------- index_a : tuple T

r""" Description ----------- Convert scipy sparse matrix to torch sparse tensor. Parameters ---------- model : torch.nn.modu

r""" Description ----------- Arithmetic weights for calculating weighted robust score. Parameters ---------- n : int

r""" Description ----------- Arithmetic weights for calculating weighted robust score. Parameters ---------- n : int

Split the graph into training graph, validation graph, and test graph by training and validation masks. Suitable for inductive models.

r""" Description ----------- Convert labels to torch tensor. Parameters ---------- labels : torch.Tensor Labels in f

Loads input data from gcn/data directory ind.dataset_str.x => the feature vectors of the training instances as scipy.sparse.csr.csr_matrix o

Loads features saved in a variety of formats. Supported formats: - .npz compressed (assumes features are saved with name "features")

Read prebuilt word embeddings from a file :param embedding_path: string, file path of the word embeddings :param embedding_dim: int, dime

Creates a directory given a path to either a directory or file. If a directory is provided, creates that directory. If a file is provided (i

Preprocessing of adjacency matrix for simple GCN model and conversion to tuple representation.

Row-normalize feature matrix and convert to tuple representation

r""" Description ----------- Save generated adversarial adjacency matrix. Parameters ---------- adj : scipy.sparse.csr.csr_m

r""" Description ----------- Save dataframe to .csv file. Parameters ---------- df : pandas.DataFrame Dataframe cont

r""" Description ----------- Save dataframe to .xlsx file. Parameters ---------- df : pandas.DataFrame Dataframe con

r""" Description ----------- Save dictinary to .json file. Parameters ---------- result_dict : dict Dictionary conta

r""" Description ----------- Save result dictionary to .xlsx file. Parameters ---------- result_dict : dict Dictiona

Saves features to a compressed .npz file with array name "features". :param path: Path to a .npz file where the features will be saved.

r""" Description ----------- Save generated adversarial features. Parameters ---------- features : torch.Tensor or numpy.arr

r""" Description ----------- Save trained model. Parameters ---------- model : torch.nn.module Model implemented bas

r"""Splits the edges of a :obj:`torch_geometric.data.Data` object into positive and negative train/val/test edges, and adds attributes of `tra