SYMBOL INDEX (339 symbols across 31 files)

FILE: recbole_gnn/config.py
  class Config (line 9) | class Config(RecBole_Config):
    method __init__ (line 10) | def __init__(self, model=None, dataset=None, config_file_list=None, co...
    method compatibility_settings (line 24) | def compatibility_settings(self):
    method _get_model_and_dataset (line 35) | def _get_model_and_dataset(self, model, dataset):
    method _load_internal_config_dict (line 65) | def _load_internal_config_dict(self, model, model_class, dataset):

FILE: recbole_gnn/data/dataloader.py
  class CustomizedTrainDataLoader (line 9) | class CustomizedTrainDataLoader(TrainDataLoader):
    method __init__ (line 10) | def __init__(self, config, dataset, sampler, shuffle=False):
  class CustomizedNegSampleEvalDataLoader (line 16) | class CustomizedNegSampleEvalDataLoader(NegSampleEvalDataLoader):
    method __init__ (line 17) | def __init__(self, config, dataset, sampler, shuffle=False):
    method collate_fn (line 22) | def collate_fn(self, index):
  class CustomizedFullSortEvalDataLoader (line 55) | class CustomizedFullSortEvalDataLoader(FullSortEvalDataLoader):
    method __init__ (line 56) | def __init__(self, config, dataset, sampler, shuffle=False):

FILE: recbole_gnn/data/dataset.py
  class GeneralGraphDataset (line 24) | class GeneralGraphDataset(RecBoleDataset):
    method __init__ (line 25) | def __init__(self, config):
    method save (line 30) | def save(self):
    method edge_index_to_adj_t (line 42) | def edge_index_to_adj_t(edge_index, edge_weight, m_num_nodes, n_num_no...
    method get_norm_adj_mat (line 49) | def get_norm_adj_mat(self, enable_sparse=False):
    method get_bipartite_inter_mat (line 81) | def get_bipartite_inter_mat(self, row='user', row_norm=True):
  class SessionGraphDataset (line 109) | class SessionGraphDataset(SequentialDataset):
    method __init__ (line 110) | def __init__(self, config):
    method session_graph_construction (line 113) | def session_graph_construction(self):
    method build (line 138) | def build(self):
  class MultiBehaviorDataset (line 145) | class MultiBehaviorDataset(SessionGraphDataset):
    method session_graph_construction (line 147) | def session_graph_construction(self):
  class LESSRDataset (line 197) | class LESSRDataset(SessionGraphDataset):
    method session_graph_construction (line 198) | def session_graph_construction(self):
  class GCEGNNDataset (line 235) | class GCEGNNDataset(SequentialDataset):
    method __init__ (line 236) | def __init__(self, config):
    method reverse_session (line 239) | def reverse_session(self):
    method bidirectional_edge (line 246) | def bidirectional_edge(self, edge_index):
    method session_graph_construction (line 253) | def session_graph_construction(self):
    method build (line 295) | def build(self):
  class SocialDataset (line 303) | class SocialDataset(GeneralGraphDataset):
    method __init__ (line 322) | def __init__(self, config):
    method _get_field_from_config (line 325) | def _get_field_from_config(self):
    method _data_filtering (line 337) | def _data_filtering(self):
    method _filter_net_by_inter (line 342) | def _filter_net_by_inter(self):
    method _load_data (line 349) | def _load_data(self, token, dataset_path):
    method net_num (line 354) | def net_num(self):
    method __str__ (line 362) | def __str__(self):
    method _build_feat_name_list (line 369) | def _build_feat_name_list(self):
    method _load_net (line 375) | def _load_net(self, token, dataset_path):
    method _check_net (line 392) | def _check_net(self, net):
    method _init_alias (line 397) | def _init_alias(self):
    method get_norm_net_adj_mat (line 423) | def get_norm_net_adj_mat(self, row_norm=False):
    method net_matrix (line 448) | def net_matrix(self, form='coo', value_field=None):

FILE: recbole_gnn/data/transform.py
  function gnn_construct_transform (line 7) | def gnn_construct_transform(config):
  class SessionGraph (line 16) | class SessionGraph:
    method __init__ (line 17) | def __init__(self, config):
    method __call__ (line 21) | def __call__(self, dataset, interaction):

FILE: recbole_gnn/model/abstract_recommender.py
  class GeneralGraphRecommender (line 7) | class GeneralGraphRecommender(GeneralRecommender):
    method __init__ (line 13) | def __init__(self, config, dataset):
  class SocialRecommender (line 23) | class SocialRecommender(GeneralRecommender):
    method __init__ (line 29) | def __init__(self, config, dataset):

FILE: recbole_gnn/model/general_recommender/directau.py
  class DirectAU (line 24) | class DirectAU(GeneralGraphRecommender):
    method __init__ (line 27) | def __init__(self, config, dataset):
    method forward (line 50) | def forward(self, user, item):
    method alignment (line 55) | def alignment(x, y, alpha=2):
    method uniformity (line 59) | def uniformity(x, t=2):
    method calculate_loss (line 62) | def calculate_loss(self, interaction):
    method predict (line 75) | def predict(self, interaction):
    method full_sort_predict (line 82) | def full_sort_predict(self, interaction):
  class MFEncoder (line 96) | class MFEncoder(BPR):
    method __init__ (line 97) | def __init__(self, config, dataset):
    method forward (line 100) | def forward(self, user_id, item_id):
    method get_all_embeddings (line 103) | def get_all_embeddings(self):
  class LGCNEncoder (line 109) | class LGCNEncoder(LightGCN):
    method __init__ (line 110) | def __init__(self, config, dataset):
    method forward (line 113) | def forward(self, user_id, item_id):
    method get_all_embeddings (line 119) | def get_all_embeddings(self):

FILE: recbole_gnn/model/general_recommender/hmlet.py
  class Gating_Net (line 27) | class Gating_Net(nn.Module):
    method __init__ (line 28) | def __init__(self, embedding_dim, mlp_dims, dropout_p):
    method gumbel_softmax (line 46) | def gumbel_softmax(self, logits, temperature, hard):
    method gumbel_softmax_sample (line 65) | def gumbel_softmax_sample(self, logits, temperature):
    method sample_gumbel (line 71) | def sample_gumbel(self, logits):
    method forward (line 79) | def forward(self, feature, temperature, hard):
  class HMLET (line 87) | class HMLET(GeneralGraphRecommender):
    method __init__ (line 92) | def __init__(self, config, dataset):
    method _gating_freeze (line 129) | def _gating_freeze(self, model, freeze_flag):
    method __choosing_one (line 134) | def __choosing_one(self, features, gumbel_out):
    method __where (line 138) | def __where(self, idx, lst):
    method get_ego_embeddings (line 144) | def get_ego_embeddings(self):
    method forward (line 154) | def forward(self):
    method calculate_loss (line 179) | def calculate_loss(self, interaction):
    method predict (line 208) | def predict(self, interaction):
    method full_sort_predict (line 219) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/general_recommender/lightgcl.py
  class LightGCL (line 27) | class LightGCL(GeneralRecommender):
    method __init__ (line 38) | def __init__(self, config, dataset):
    method create_adjust_matrix (line 86) | def create_adjust_matrix(self):
    method coo2tensor (line 103) | def coo2tensor(self, matrix: sp.coo_matrix):
    method sparse_dropout (line 119) | def sparse_dropout(self, matrix, dropout):
    method forward (line 127) | def forward(self):
    method calculate_loss (line 144) | def calculate_loss(self, interaction):
    method calc_bpr_loss (line 157) | def calc_bpr_loss(self, E_u_norm, E_i_norm, user_list, pos_item_list, ...
    method calc_ssl_loss (line 184) | def calc_ssl_loss(self, E_u_norm, E_i_norm, user_list, pos_item_list):
    method predict (line 215) | def predict(self, interaction):
    method full_sort_predict (line 222) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/general_recommender/lightgcn.py
  class LightGCN (line 26) | class LightGCN(GeneralGraphRecommender):
    method __init__ (line 36) | def __init__(self, config, dataset):
    method get_ego_embeddings (line 60) | def get_ego_embeddings(self):
    method forward (line 70) | def forward(self):
    method calculate_loss (line 83) | def calculate_loss(self, interaction):
    method predict (line 112) | def predict(self, interaction):
    method full_sort_predict (line 123) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/general_recommender/ncl.py
  class NCL (line 20) | class NCL(GeneralGraphRecommender):
    method __init__ (line 23) | def __init__(self, config, dataset):
    method e_step (line 60) | def e_step(self):
    method run_kmeans (line 66) | def run_kmeans(self, x):
    method get_ego_embeddings (line 83) | def get_ego_embeddings(self):
    method forward (line 93) | def forward(self):
    method ProtoNCE_loss (line 106) | def ProtoNCE_loss(self, node_embedding, user, item):
    method ssl_layer_loss (line 135) | def ssl_layer_loss(self, current_embedding, previous_embedding, user, ...
    method calculate_loss (line 166) | def calculate_loss(self, interaction):
    method predict (line 201) | def predict(self, interaction):
    method full_sort_predict (line 212) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/general_recommender/ngcf.py
  class NGCF (line 28) | class NGCF(GeneralGraphRecommender):
    method __init__ (line 34) | def __init__(self, config, dataset):
    method get_ego_embeddings (line 62) | def get_ego_embeddings(self):
    method forward (line 73) | def forward(self):
    method calculate_loss (line 106) | def calculate_loss(self, interaction):
    method predict (line 128) | def predict(self, interaction):
    method full_sort_predict (line 139) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/general_recommender/sgl.py
  class SGL (line 29) | class SGL(GeneralGraphRecommender):
    method __init__ (line 43) | def __init__(self, config, dataset):
    method train (line 73) | def train(self, mode: bool = True):
    method graph_construction (line 82) | def graph_construction(self):
    method random_graph_augment (line 93) | def random_graph_augment(self):
    method forward (line 128) | def forward(self, graph=None):
    method calc_bpr_loss (line 147) | def calc_bpr_loss(self, user_emd, item_emd, user_list, pos_item_list, ...
    method calc_ssl_loss (line 176) | def calc_ssl_loss(self, user_list, pos_item_list, user_sub1, user_sub2...
    method calculate_loss (line 211) | def calculate_loss(self, interaction):
    method predict (line 227) | def predict(self, interaction):
    method full_sort_predict (line 235) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/general_recommender/simgcl.py
  class SimGCL (line 16) | class SimGCL(LightGCN):
    method __init__ (line 17) | def __init__(self, config, dataset):
    method forward (line 24) | def forward(self, perturbed=False):
    method calculate_cl_loss (line 40) | def calculate_cl_loss(self, x1, x2):
    method calculate_loss (line 48) | def calculate_loss(self, interaction):

FILE: recbole_gnn/model/general_recommender/ssl4rec.py
  class SSL4REC (line 22) | class SSL4REC(GeneralGraphRecommender):
    method __init__ (line 25) | def __init__(self, config, dataset):
    method forward (line 46) | def forward(self, user, item):
    method calculate_batch_softmax_loss (line 50) | def calculate_batch_softmax_loss(self, user_emb, item_emb, temperature):
    method calculate_loss (line 59) | def calculate_loss(self, interaction):
    method predict (line 77) | def predict(self, interaction):
    method full_sort_predict (line 88) | def full_sort_predict(self, interaction):
  class DNN_Encoder (line 102) | class DNN_Encoder(nn.Module):
    method __init__ (line 103) | def __init__(self, config, dataset):
    method reset_parameters (line 133) | def reset_parameters(self):
    method forward (line 137) | def forward(self, q, x):
    method item_encoding (line 146) | def item_encoding(self, x):
    method calculate_cl_loss (line 156) | def calculate_cl_loss(self, idx):

FILE: recbole_gnn/model/general_recommender/xsimgcl.py
  class XSimGCL (line 19) | class XSimGCL(LightGCN):
    method __init__ (line 20) | def __init__(self, config, dataset):
    method forward (line 28) | def forward(self, perturbed=False):
    method calculate_cl_loss (line 50) | def calculate_cl_loss(self, x1, x2):
    method calculate_loss (line 58) | def calculate_loss(self, interaction):

FILE: recbole_gnn/model/layers.py
  class LightGCNConv (line 8) | class LightGCNConv(MessagePassing):
    method __init__ (line 9) | def __init__(self, dim):
    method forward (line 13) | def forward(self, x, edge_index, edge_weight):
    method message (line 16) | def message(self, x_j, edge_weight):
    method message_and_aggregate (line 19) | def message_and_aggregate(self, adj_t, x):
    method __repr__ (line 22) | def __repr__(self):
  class BipartiteGCNConv (line 26) | class BipartiteGCNConv(MessagePassing):
    method __init__ (line 27) | def __init__(self, dim):
    method forward (line 31) | def forward(self, x, edge_index, edge_weight, size):
    method message (line 34) | def message(self, x_j, edge_weight):
    method __repr__ (line 37) | def __repr__(self):
  class BiGNNConv (line 41) | class BiGNNConv(MessagePassing):
    method __init__ (line 48) | def __init__(self, in_channels, out_channels):
    method forward (line 54) | def forward(self, x, edge_index, edge_weight):
    method message (line 60) | def message(self, x_j, edge_weight):
    method message_and_aggregate (line 63) | def message_and_aggregate(self, adj_t, x):
    method __repr__ (line 66) | def __repr__(self):
  class SRGNNConv (line 70) | class SRGNNConv(MessagePassing):
    method __init__ (line 71) | def __init__(self, dim):
    method forward (line 77) | def forward(self, x, edge_index):
  class SRGNNCell (line 82) | class SRGNNCell(nn.Module):
    method __init__ (line 83) | def __init__(self, dim):
    method forward (line 95) | def forward(self, hidden, edge_index):
    method _reset_parameters (line 111) | def _reset_parameters(self):

FILE: recbole_gnn/model/sequential_recommender/gcegnn.py
  class LocalAggregator (line 28) | class LocalAggregator(MessagePassing):
    method __init__ (line 29) | def __init__(self, dim, alpha):
    method forward (line 34) | def forward(self, x, edge_index, edge_attr):
    method message (line 37) | def message(self, x_j, x_i, edge_attr, index, ptr, size_i):
  class GlobalAggregator (line 46) | class GlobalAggregator(nn.Module):
    method __init__ (line 47) | def __init__(self, dim, dropout, act=torch.relu):
    method forward (line 58) | def forward(self, self_vectors, neighbor_vector, batch_size, masks, ne...
  class GCEGNN (line 76) | class GCEGNN(SequentialRecommender):
    method __init__ (line 77) | def __init__(self, config, dataset):
    method reset_parameters (line 124) | def reset_parameters(self):
    method _add_edge (line 129) | def _add_edge(self, graph, sid, tid):
    method construct_global_graph (line 134) | def construct_global_graph(self, dataset):
    method fusion (line 158) | def fusion(self, hidden, mask):
    method forward (line 174) | def forward(self, x, edge_index, edge_attr, alias_inputs, item_seq_len):
    method calculate_loss (line 234) | def calculate_loss(self, interaction):
    method predict (line 256) | def predict(self, interaction):
    method full_sort_predict (line 268) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/sequential_recommender/gcsan.py
  class GCSAN (line 23) | class GCSAN(SequentialRecommender):
    method __init__ (line 34) | def __init__(self, config, dataset):
    method _init_weights (line 80) | def _init_weights(self, module):
    method get_attention_mask (line 92) | def get_attention_mask(self, item_seq):
    method forward (line 108) | def forward(self, x, edge_index, alias_inputs, item_seq_len):
    method calculate_loss (line 124) | def calculate_loss(self, interaction):
    method predict (line 146) | def predict(self, interaction):
    method full_sort_predict (line 157) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/sequential_recommender/lessr.py
  class EOPA (line 24) | class EOPA(nn.Module):
    method __init__ (line 25) | def __init__(
    method reducer (line 36) | def reducer(self, nodes):
    method forward (line 45) | def forward(self, mg, feat):
  class SGAT (line 63) | class SGAT(nn.Module):
    method __init__ (line 64) | def __init__(
    method forward (line 82) | def forward(self, sg, feat):
  class AttnReadout (line 100) | class AttnReadout(nn.Module):
    method __init__ (line 101) | def __init__(
    method forward (line 122) | def forward(self, g, feat, last_nodes, batch):
  class LESSR (line 140) | class LESSR(SequentialRecommender):
    method __init__ (line 152) | def __init__(self, config, dataset):
    method forward (line 202) | def forward(self, x, edge_index_EOP, edge_index_shortcut, batch, is_la...
    method calculate_loss (line 223) | def calculate_loss(self, interaction):
    method predict (line 236) | def predict(self, interaction):
    method full_sort_predict (line 248) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/sequential_recommender/niser.py
  class NISER (line 23) | class NISER(SequentialRecommender):
    method __init__ (line 27) | def __init__(self, config, dataset):
    method _reset_parameters (line 59) | def _reset_parameters(self):
    method forward (line 64) | def forward(self, x, edge_index, alias_inputs, item_seq_len):
    method calculate_loss (line 91) | def calculate_loss(self, interaction):
    method predict (line 112) | def predict(self, interaction):
    method full_sort_predict (line 123) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/sequential_recommender/sgnnhn.py
  function layer_norm (line 29) | def layer_norm(x):
  class SGNNHN (line 37) | class SGNNHN(SequentialRecommender):
    method __init__ (line 42) | def __init__(self, config, dataset):
    method _reset_parameters (line 74) | def _reset_parameters(self):
    method att_out (line 79) | def att_out(self, hidden, star_node, batch):
    method forward (line 88) | def forward(self, x, edge_index, batch, alias_inputs, item_seq_len):
    method calculate_loss (line 118) | def calculate_loss(self, interaction):
    method predict (line 140) | def predict(self, interaction):
    method full_sort_predict (line 152) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/sequential_recommender/srgnn.py
  class SRGNN (line 25) | class SRGNN(SequentialRecommender):
    method __init__ (line 53) | def __init__(self, config, dataset):
    method _reset_parameters (line 81) | def _reset_parameters(self):
    method forward (line 86) | def forward(self, x, edge_index, alias_inputs, item_seq_len):
    method calculate_loss (line 103) | def calculate_loss(self, interaction):
    method predict (line 124) | def predict(self, interaction):
    method full_sort_predict (line 135) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/sequential_recommender/tagnn.py
  class TAGNN (line 26) | class TAGNN(SequentialRecommender):
    method __init__ (line 30) | def __init__(self, config, dataset):
    method _reset_parameters (line 57) | def _reset_parameters(self):
    method forward (line 62) | def forward(self, x, edge_index, alias_inputs, item_seq_len):
    method calculate_loss (line 89) | def calculate_loss(self, interaction):
    method predict (line 99) | def predict(self, interaction):
    method full_sort_predict (line 102) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/social_recommender/diffnet.py
  class DiffNet (line 27) | class DiffNet(SocialRecommender):
    method __init__ (line 33) | def __init__(self, config, dataset):
    method convertDistribution (line 78) | def convertDistribution(self, x):
    method forward (line 83) | def forward(self):
    method calculate_loss (line 108) | def calculate_loss(self, interaction):
    method predict (line 137) | def predict(self, interaction):
    method full_sort_predict (line 148) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/social_recommender/mhcn.py
  class GatingLayer (line 30) | class GatingLayer(nn.Module):
    method __init__ (line 31) | def __init__(self, dim):
    method forward (line 37) | def forward(self, emb):
  class AttLayer (line 44) | class AttLayer(nn.Module):
    method __init__ (line 45) | def __init__(self, dim):
    method forward (line 51) | def forward(self, *embs):
  class MHCN (line 63) | class MHCN(SocialRecommender):
    method __init__ (line 71) | def __init__(self, config, dataset):
    method get_bipartite_inter_mat (line 118) | def get_bipartite_inter_mat(self, dataset):
    method get_edge_index_weight (line 123) | def get_edge_index_weight(self, matrix):
    method get_motif_adj_matrix (line 129) | def get_motif_adj_matrix(self, dataset):
    method forward (line 160) | def forward(self):
    method hierarchical_self_supervision (line 217) | def hierarchical_self_supervision(self, user_embeddings, edge_index, e...
    method calculate_loss (line 243) | def calculate_loss(self, interaction):
    method predict (line 277) | def predict(self, interaction):
    method full_sort_predict (line 288) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/model/social_recommender/sept.py
  class SEPT (line 30) | class SEPT(SocialRecommender):
    method __init__ (line 41) | def __init__(self, config, dataset):
    method get_norm_edge_weight (line 83) | def get_norm_edge_weight(self, edge_index, node_num):
    method get_user_view_matrix (line 91) | def get_user_view_matrix(self, dataset):
    method subgraph_construction (line 111) | def subgraph_construction(self):
    method get_ego_embeddings (line 135) | def get_ego_embeddings(self):
    method forward (line 145) | def forward(self, graph=None):
    method user_view_forward (line 165) | def user_view_forward(self):
    method label_prediction (line 189) | def label_prediction(self, emb, aug_emb):
    method sampling (line 194) | def sampling(self, logits):
    method generate_pesudo_labels (line 197) | def generate_pesudo_labels(self, prob1, prob2):
    method calculate_ssl_loss (line 202) | def calculate_ssl_loss(self, aug_emb, positive, emb):
    method calculate_rec_loss (line 211) | def calculate_rec_loss(self, interaction):
    method calculate_loss (line 240) | def calculate_loss(self, interaction):
    method predict (line 281) | def predict(self, interaction):
    method full_sort_predict (line 292) | def full_sort_predict(self, interaction):

FILE: recbole_gnn/quick_start.py
  function run_recbole_gnn (line 9) | def run_recbole_gnn(model=None, dataset=None, config_file_list=None, con...
  function objective_function (line 66) | def objective_function(config_dict=None, config_file_list=None, saved=Tr...

FILE: recbole_gnn/trainer.py
  class NCLTrainer (line 9) | class NCLTrainer(Trainer):
    method __init__ (line 10) | def __init__(self, config, model):
    method fit (line 16) | def fit(self, train_data, valid_data=None, verbose=True, saved=True, s...
    method _train_epoch (line 100) | def _train_epoch(self, train_data, epoch_idx, loss_func=None, show_pro...
  class HMLETTrainer (line 147) | class HMLETTrainer(Trainer):
    method __init__ (line 148) | def __init__(self, config, model):
    method _train_epoch (line 157) | def _train_epoch(self, train_data, epoch_idx, loss_func=None, show_pro...
  class SEPTTrainer (line 169) | class SEPTTrainer(Trainer):
    method __init__ (line 170) | def __init__(self, config, model):
    method _train_epoch (line 174) | def _train_epoch(self, train_data, epoch_idx, loss_func=None, show_pro...

FILE: recbole_gnn/utils.py
  function create_dataset (line 16) | def create_dataset(config):
  function get_model (line 62) | def get_model(model_name):
  function _get_customized_dataloader (line 88) | def _get_customized_dataloader(config, phase):
  function data_preparation (line 99) | def data_preparation(config, dataset):
  function get_trainer (line 145) | def get_trainer(model_type, model_name):
  class ModelType (line 159) | class ModelType(Enum):

FILE: run_hyper.py
  function main (line 7) | def main():

FILE: tests/test_model.py
  function quick_test (line 10) | def quick_test(config_dict):
  class TestGeneralRecommender (line 14) | class TestGeneralRecommender(unittest.TestCase):
    method test_bpr (line 15) | def test_bpr(self):
    method test_neumf (line 21) | def test_neumf(self):
    method test_ngcf (line 27) | def test_ngcf(self):
    method test_lightgcn (line 33) | def test_lightgcn(self):
    method test_sgl (line 39) | def test_sgl(self):
    method test_hmlet (line 45) | def test_hmlet(self):
    method test_ncl (line 51) | def test_ncl(self):
    method test_simgcl (line 58) | def test_simgcl(self):
    method test_xsimgcl (line 64) | def test_xsimgcl(self):
    method test_lightgcl (line 70) | def test_lightgcl(self):
    method test_directau (line 76) | def test_directau(self):
    method test_ssl4rec (line 82) | def test_ssl4rec(self):
  class TestSequentialRecommender (line 89) | class TestSequentialRecommender(unittest.TestCase):
    method test_gru4rec (line 90) | def test_gru4rec(self):
    method test_narm (line 96) | def test_narm(self):
    method test_sasrec (line 102) | def test_sasrec(self):
    method test_srgnn (line 108) | def test_srgnn(self):
    method test_srgnn_uni100 (line 114) | def test_srgnn_uni100(self):
    method test_gcsan (line 125) | def test_gcsan(self):
    method test_niser (line 131) | def test_niser(self):
    method test_lessr (line 137) | def test_lessr(self):
    method test_tagnn (line 143) | def test_tagnn(self):
    method test_gcegnn (line 149) | def test_gcegnn(self):
    method test_sgnnhn (line 155) | def test_sgnnhn(self):
  class TestSocialRecommender (line 162) | class TestSocialRecommender(unittest.TestCase):
    method test_diffnet (line 163) | def test_diffnet(self):
    method test_mhcn (line 169) | def test_mhcn(self):
    method test_sept (line 175) | def test_sept(self):