SYMBOL INDEX (166 symbols across 10 files)

FILE: Utils/TimeLogger.py
  function log (line 6) | def log(msg, save=None, oneline=False):
  function marktime (line 21) | def marktime(marker):

FILE: data_handler.py
  class MultiDataHandler (line 13) | class MultiDataHandler:
    method __init__ (line 14) | def __init__(self, trn_datasets, tst_datasets_group):
    method make_joint_trn_loader (line 36) | def make_joint_trn_loader(self):
    method remake_initial_projections (line 44) | def remake_initial_projections(self):
  class DataHandler (line 49) | class DataHandler:
    method __init__ (line 50) | def __init__(self, data_name):
    method get_data_files (line 57) | def get_data_files(self):
    method load_one_file (line 68) | def load_one_file(self, filename):
    method load_feats (line 75) | def load_feats(self, filename):
    method normalize_adj (line 84) | def normalize_adj(self, mat, log=False):
    method unique_numpy (line 99) | def unique_numpy(self, row, col):
    method make_torch_adj (line 106) | def make_torch_adj(self, mat, unidirectional_for_asym=False):
    method load_data (line 148) | def load_data(self):
    method make_projectors (line 207) | def make_projectors(self):
  class TstData (line 238) | class TstData(data.Dataset):
    method __init__ (line 239) | def __init__(self, coomat, trn_mat):
    method __len__ (line 254) | def __len__(self):
    method __getitem__ (line 257) | def __getitem__(self, idx):
  class TrnData (line 260) | class TrnData(data.Dataset):
    method __init__ (line 261) | def __init__(self, coomat):
    method neg_sampling (line 269) | def neg_sampling(self):
    method __len__ (line 272) | def __len__(self):
    method __getitem__ (line 275) | def __getitem__(self, idx):
  class JointTrnData (line 278) | class JointTrnData(data.Dataset):
    method __init__ (line 279) | def __init__(self, dataset_list):
    method neg_sampling (line 291) | def neg_sampling(self):
    method __len__ (line 295) | def __len__(self):
    method __getitem__ (line 298) | def __getitem__(self, idx):

FILE: main.py
  class Exp (line 14) | class Exp:
    method __init__ (line 15) | def __init__(self, multi_handler):
    method make_print (line 31) | def make_print(self, name, ep, reses, save, data_name=None):
    method run (line 45) | def run(self):
    method print_model_size (line 120) | def print_model_size(self):
    method prepare_model (line 135) | def prepare_model(self):
    method train_epoch (line 140) | def train_epoch(self):
    method make_trn_masks (line 189) | def make_trn_masks(self, numpy_usrs, csr_mat):
    method test_epoch (line 195) | def test_epoch(self, handler, dataset_id):
    method calc_recall_ndcg (line 226) | def calc_recall_ndcg(self, topLocs, tstLocs, batIds):
    method save_history (line 245) | def save_history(self):
    method load_model (line 257) | def load_model(self):

FILE: model.py
  class FeedForwardLayer (line 13) | class FeedForwardLayer(nn.Module):
    method __init__ (line 14) | def __init__(self, in_feat, out_feat, bias=True, act=None):
    method forward (line 28) | def forward(self, embeds):
  class TopoEncoder (line 33) | class TopoEncoder(nn.Module):
    method __init__ (line 34) | def __init__(self):
    method forward (line 39) | def forward(self, adj, embeds, normed=False):
  class MLP (line 55) | class MLP(nn.Module):
    method __init__ (line 56) | def __init__(self):
    method forward (line 62) | def forward(self, embeds):
  class GTLayer (line 67) | class GTLayer(nn.Module):
    method __init__ (line 68) | def __init__(self):
    method _pick_anchors (line 76) | def _pick_anchors(self, embeds):
    method forward (line 81) | def forward(self, embeds):
  class GraphTransformer (line 91) | class GraphTransformer(nn.Module):
    method __init__ (line 92) | def __init__(self):
    method forward (line 96) | def forward(self, embeds):
  class Feat_Projector (line 101) | class Feat_Projector(nn.Module):
    method __init__ (line 102) | def __init__(self, feats):
    method svd_proj (line 116) | def svd_proj(self, feats):
    method uniform_proj (line 127) | def uniform_proj(self, feats):
    method random_proj (line 131) | def random_proj(self, feats):
    method forward (line 135) | def forward(self):
  class Adj_Projector (line 138) | class Adj_Projector(nn.Module):
    method __init__ (line 139) | def __init__(self, adj):
    method svd_proj (line 146) | def svd_proj(self, adj):
    method forward (line 164) | def forward(self):
  class Expert (line 167) | class Expert(nn.Module):
    method __init__ (line 168) | def __init__(self):
    method forward (line 178) | def forward(self, projectors, pck_nodes=None):
    method pred_norm (line 185) | def pred_norm(self, pos_preds, neg_preds):
    method cal_loss (line 194) | def cal_loss(self, batch_data, projectors):
    method pred_for_test (line 224) | def pred_for_test(self, batch_data, cand_size, projectors, rerun_embed...
    method attempt (line 251) | def attempt(self, topo_embeds, dataset):
  class AnyGraph (line 277) | class AnyGraph(nn.Module):
    method __init__ (line 278) | def __init__(self):
    method assign_experts (line 283) | def assign_experts(self, handlers, reca=True, log_assignment=False):
    method summon (line 314) | def summon(self, dataset_id):
    method summon_opt (line 317) | def summon_opt(self, dataset_id):

FILE: node_classification/Utils/TimeLogger.py
  function log (line 6) | def log(msg, save=None, oneline=False):
  function marktime (line 21) | def marktime(marker):

FILE: node_classification/data_handler.py
  class MultiDataHandler (line 13) | class MultiDataHandler:
    method __init__ (line 14) | def __init__(self, trn_datasets, tst_datasets_group):
    method make_joint_trn_loader (line 36) | def make_joint_trn_loader(self):
    method remake_initial_projections (line 44) | def remake_initial_projections(self):
  class DataHandler (line 49) | class DataHandler:
    method __init__ (line 50) | def __init__(self, data_name):
    method get_data_files (line 57) | def get_data_files(self):
    method load_one_file (line 69) | def load_one_file(self, filename):
    method load_feats (line 76) | def load_feats(self, filename):
    method normalize_adj (line 85) | def normalize_adj(self, mat, log=False):
    method unique_numpy (line 100) | def unique_numpy(self, row, col):
    method make_torch_adj (line 107) | def make_torch_adj(self, mat, unidirectional_for_asym=False):
    method load_data (line 149) | def load_data(self):
    method make_projectors (line 196) | def make_projectors(self):
  class TrnData (line 227) | class TrnData(data.Dataset):
    method __init__ (line 228) | def __init__(self, coomat):
    method neg_sampling (line 238) | def neg_sampling(self):
    method __len__ (line 250) | def __len__(self):
    method __getitem__ (line 253) | def __getitem__(self, idx):
  class NodeTstData (line 256) | class NodeTstData(data.Dataset):
    method __init__ (line 257) | def __init__(self, tst_mat):
    method __len__ (line 261) | def __len__(self):
    method __getitem__ (line 264) | def __getitem__(self, idx):
  class JointTrnData (line 267) | class JointTrnData(data.Dataset):
    method __init__ (line 268) | def __init__(self, dataset_list):
    method neg_sampling (line 280) | def neg_sampling(self):
    method __len__ (line 284) | def __len__(self):
    method __getitem__ (line 287) | def __getitem__(self, idx):

FILE: node_classification/main.py
  class Exp (line 15) | class Exp:
    method __init__ (line 16) | def __init__(self, multi_handler):
    method make_print (line 32) | def make_print(self, name, ep, reses, save, data_name=None):
    method run (line 46) | def run(self):
    method print_model_size (line 124) | def print_model_size(self):
    method prepare_model (line 139) | def prepare_model(self):
    method train_epoch (line 144) | def train_epoch(self):
    method make_trn_masks (line 196) | def make_trn_masks(self, numpy_usrs, csr_mat):
    method test_loss_epoch (line 202) | def test_loss_epoch(self, handler, dataset_id):
    method test_epoch (line 234) | def test_epoch(self, handler, dataset_id):
    method calc_recall_ndcg (line 263) | def calc_recall_ndcg(self, topLocs, tstLocs, batIds):
    method save_history (line 282) | def save_history(self):
    method load_model (line 294) | def load_model(self):

FILE: node_classification/model.py
  class FeedForwardLayer (line 14) | class FeedForwardLayer(nn.Module):
    method __init__ (line 15) | def __init__(self, in_feat, out_feat, bias=True, act=None):
    method forward (line 29) | def forward(self, embeds):
  class TopoEncoder (line 34) | class TopoEncoder(nn.Module):
    method __init__ (line 35) | def __init__(self):
    method forward (line 40) | def forward(self, adj, embeds, normed=False):
  class MLP (line 56) | class MLP(nn.Module):
    method __init__ (line 57) | def __init__(self):
    method forward (line 63) | def forward(self, embeds):
  class GTLayer (line 68) | class GTLayer(nn.Module):
    method __init__ (line 69) | def __init__(self):
    method _pick_anchors (line 77) | def _pick_anchors(self, embeds):
    method forward (line 82) | def forward(self, embeds):
  class GraphTransformer (line 92) | class GraphTransformer(nn.Module):
    method __init__ (line 93) | def __init__(self):
    method forward (line 97) | def forward(self, embeds):
  class Feat_Projector (line 102) | class Feat_Projector(nn.Module):
    method __init__ (line 103) | def __init__(self, feats):
    method svd_proj (line 117) | def svd_proj(self, feats):
    method uniform_proj (line 128) | def uniform_proj(self, feats):
    method random_proj (line 132) | def random_proj(self, feats):
    method forward (line 136) | def forward(self):
  class Adj_Projector (line 139) | class Adj_Projector(nn.Module):
    method __init__ (line 140) | def __init__(self, adj):
    method svd_proj (line 147) | def svd_proj(self, adj):
    method forward (line 165) | def forward(self):
  class Expert (line 168) | class Expert(nn.Module):
    method __init__ (line 169) | def __init__(self):
    method forward (line 179) | def forward(self, projectors, pck_nodes=None):
    method pred_norm (line 186) | def pred_norm(self, pos_preds, neg_preds):
    method cal_loss (line 195) | def cal_loss(self, batch_data, projectors):
    method pred_for_test (line 225) | def pred_for_test(self, batch_data, cand_size, projectors, rerun_embed...
    method pred_for_node_test (line 252) | def pred_for_node_test(self, nodes, cand_size, feats, rerun_embed=True):
    method attempt (line 262) | def attempt(self, topo_embeds, dataset):
  class AnyGraph (line 288) | class AnyGraph(nn.Module):
    method __init__ (line 289) | def __init__(self):
    method one_graph_one_expert (line 294) | def one_graph_one_expert(self, handlers, log_assignment=False):
    method store_history_assignment (line 301) | def store_history_assignment(self, assignment):
    method assign_experts (line 304) | def assign_experts(self, handlers, reca=True, log_assignment=False):
    method summon (line 345) | def summon(self, dataset_id):
    method summon_opt (line 348) | def summon_opt(self, dataset_id):

FILE: node_classification/params.py
  function parse_args (line 3) | def parse_args():

FILE: params.py
  function parse_args (line 3) | def parse_args():