SYMBOL INDEX (171 symbols across 33 files)

FILE: data/SBMs.py
  class load_SBMsDataSetDGL (line 18) | class load_SBMsDataSetDGL(torch.utils.data.Dataset):
    method __init__ (line 20) | def __init__(self,
    method _prepare (line 35) | def _prepare(self):
    method __len__ (line 60) | def __len__(self):
    method __getitem__ (line 64) | def __getitem__(self, idx):
  class SBMsDatasetDGL (line 80) | class SBMsDatasetDGL(torch.utils.data.Dataset):
    method __init__ (line 82) | def __init__(self, name):
  function laplace_decomp (line 98) | def laplace_decomp(g, max_freqs):
  function make_full_graph (line 137) | def make_full_graph(g):
  function add_edge_laplace_feats (line 162) | def add_edge_laplace_feats(g):
  class SBMsDataset (line 184) | class SBMsDataset(torch.utils.data.Dataset):
    method __init__ (line 186) | def __init__(self, name):
    method collate (line 205) | def collate(self, samples):
    method _laplace_decomp (line 214) | def _laplace_decomp(self, max_freqs):
    method _make_full_graph (line 220) | def _make_full_graph(self):
    method _add_edge_laplace_feats (line 226) | def _add_edge_laplace_feats(self):

FILE: data/data.py
  function LoadData (line 9) | def LoadData(DATASET_NAME):

FILE: data/molecules.py
  class MoleculeDGL (line 21) | class MoleculeDGL(torch.utils.data.Dataset):
    method __init__ (line 22) | def __init__(self, data_dir, split, num_graphs=None):
    method _prepare (line 53) | def _prepare(self):
    method __len__ (line 77) | def __len__(self):
    method __getitem__ (line 81) | def __getitem__(self, idx):
  class MoleculeDatasetDGL (line 97) | class MoleculeDatasetDGL(torch.utils.data.Dataset):
    method __init__ (line 98) | def __init__(self, name='Zinc'):
  function laplace_decomp (line 120) | def laplace_decomp(g, max_freqs):
  function make_full_graph (line 159) | def make_full_graph(g):
  function add_edge_laplace_feats (line 184) | def add_edge_laplace_feats(g):
  class MoleculeDataset (line 205) | class MoleculeDataset(torch.utils.data.Dataset):
    method __init__ (line 207) | def __init__(self, name):
    method collate (line 227) | def collate(self, samples):
    method _laplace_decomp (line 235) | def _laplace_decomp(self, max_freqs):
    method _make_full_graph (line 241) | def _make_full_graph(self):
    method _add_edge_laplace_feats (line 247) | def _add_edge_laplace_feats(self):

FILE: data/molhiv.py
  function laplace_decomp (line 19) | def laplace_decomp(graph, max_freqs):
  function make_full_graph (line 56) | def make_full_graph(graph):
  function add_edge_laplace_feats (line 82) | def add_edge_laplace_feats(graph):
  class MolHIVDataset (line 104) | class MolHIVDataset(torch.utils.data.Dataset):
    method __init__ (line 106) | def __init__(self, name):
    method collate (line 129) | def collate(self, samples):
    method _laplace_decomp (line 136) | def _laplace_decomp(self, max_freqs):
    method _make_full_graph (line 141) | def _make_full_graph(self):
    method _add_edge_laplace_feats (line 146) | def _add_edge_laplace_feats(self):

FILE: data/molpcba.py
  function laplace_decomp (line 21) | def laplace_decomp(graph, max_freqs):
  function make_full_graph (line 62) | def make_full_graph(graph):
  function add_edge_laplace_feats (line 88) | def add_edge_laplace_feats(graph):
  class MolPCBADataset (line 110) | class MolPCBADataset(torch.utils.data.Dataset):
    method __init__ (line 112) | def __init__(self, name):
    method collate (line 135) | def collate(self, samples):
    method _laplace_decomp (line 142) | def _laplace_decomp(self, max_freqs):
    method _make_full_graph (line 147) | def _make_full_graph(self):
    method _add_edge_laplace_feats (line 152) | def _add_edge_laplace_feats(self):

FILE: layers/graph_transformer_layer.py
  function src_dot_dst (line 17) | def src_dot_dst(src_field, dst_field, out_field):
  function scaling (line 23) | def scaling(field, scale_constant):
  function imp_exp_attn (line 29) | def imp_exp_attn(implicit_attn, explicit_edge):
  function exp_real (line 39) | def exp_real(field, L):
  function exp_fake (line 46) | def exp_fake(field, L):
  function exp (line 52) | def exp(field):
  class MultiHeadAttentionLayer (line 63) | class MultiHeadAttentionLayer(nn.Module):
    method __init__ (line 64) | def __init__(self, gamma, in_dim, out_dim, num_heads, full_graph, use_...
    method propagate_attention (line 97) | def propagate_attention(self, g):
    method forward (line 137) | def forward(self, g, h, e):
  class GraphTransformerLayer (line 172) | class GraphTransformerLayer(nn.Module):
    method __init__ (line 176) | def __init__(self, gamma, in_dim, out_dim, num_heads, full_graph, drop...
    method forward (line 208) | def forward(self, g, h, e):
    method __repr__ (line 249) | def __repr__(self):

FILE: layers/mlp_readout_layer.py
  class MLPReadout (line 9) | class MLPReadout(nn.Module):
    method __init__ (line 11) | def __init__(self, input_dim, output_dim, L=2):  # L=nb_hidden_layers
    method forward (line 18) | def forward(self, x):

FILE: main_SBMs_node_classification.py
  class DotDict (line 25) | class DotDict(dict):
    method __init__ (line 26) | def __init__(self, **kwds):
  function gpu_setup (line 42) | def gpu_setup(use_gpu, gpu_id):
  function view_model_param (line 59) | def view_model_param(LPE, net_params):
  function train_val_pipeline (line 79) | def train_val_pipeline(MODEL_NAME, dataset, params, net_params, dirs):
  function main (line 243) | def main():

FILE: main_ZINC_graph_regression.py
  function gpu_setup (line 38) | def gpu_setup(use_gpu, gpu_id):
  function view_model_param (line 55) | def view_model_param(LPE, net_params):
  function train_val_pipeline (line 75) | def train_val_pipeline(MODEL_NAME, dataset, params, net_params, dirs):
  function main (line 240) | def main():

FILE: main_molhiv.py
  function gpu_setup (line 37) | def gpu_setup(use_gpu, gpu_id):
  function view_model_param (line 54) | def view_model_param(LPE, net_params):
  function train_val_pipeline (line 74) | def train_val_pipeline(MODEL_NAME, dataset, params, net_params, dirs):
  function main (line 247) | def main():

FILE: main_molpcba.py
  function gpu_setup (line 37) | def gpu_setup(use_gpu, gpu_id):
  function view_model_param (line 54) | def view_model_param(LPE, net_params):
  function train_val_pipeline (line 74) | def train_val_pipeline(MODEL_NAME, dataset, params, net_params, dirs):
  function main (line 247) | def main():

FILE: nets/SBMs_node_classification/SAN.py
  class SAN (line 15) | class SAN(nn.Module):
    method __init__ (line 17) | def __init__(self, net_params):
    method forward (line 55) | def forward(self, g, h, e):
    method loss (line 73) | def loss(self, pred, label):

FILE: nets/SBMs_node_classification/SAN_EdgeLPE.py
  class SAN_EdgeLPE (line 15) | class SAN_EdgeLPE(nn.Module):
    method __init__ (line 17) | def __init__(self, net_params):
    method forward (line 60) | def forward(self, g, h, e, diff, product, EigVals):
    method loss (line 97) | def loss(self, pred, label):

FILE: nets/SBMs_node_classification/SAN_NodeLPE.py
  class SAN_NodeLPE (line 15) | class SAN_NodeLPE(nn.Module):
    method __init__ (line 17) | def __init__(self, net_params):
    method forward (line 61) | def forward(self, g, h, e, EigVecs, EigVals):
    method loss (line 99) | def loss(self, pred, label):

FILE: nets/SBMs_node_classification/load_net.py
  function NodeLPE (line 11) | def NodeLPE(net_params):
  function EdgeLPE (line 14) | def EdgeLPE(net_params):
  function NoLPE (line 17) | def NoLPE(net_params):
  function gnn_model (line 20) | def gnn_model(LPE, net_params):

FILE: nets/ZINC_graph_regression/SAN.py
  class SAN (line 15) | class SAN(nn.Module):
    method __init__ (line 16) | def __init__(self, net_params):
    method forward (line 51) | def forward(self, g, h, e):
    method loss (line 74) | def loss(self, scores, targets):

FILE: nets/ZINC_graph_regression/SAN_EdgeLPE.py
  class SAN_EdgeLPE (line 15) | class SAN_EdgeLPE(nn.Module):
    method __init__ (line 16) | def __init__(self, net_params):
    method forward (line 59) | def forward(self, g, h, e, diff, product, EigVals):
    method loss (line 102) | def loss(self, scores, targets):

FILE: nets/ZINC_graph_regression/SAN_NodeLPE.py
  class SAN_NodeLPE (line 15) | class SAN_NodeLPE(nn.Module):
    method __init__ (line 16) | def __init__(self, net_params):
    method forward (line 59) | def forward(self, g, h, e, EigVecs, EigVals):
    method loss (line 104) | def loss(self, scores, targets):

FILE: nets/ZINC_graph_regression/load_net.py
  function NodeLPE (line 7) | def NodeLPE(net_params):
  function EdgeLPE (line 10) | def EdgeLPE(net_params):
  function NoLPE (line 13) | def NoLPE(net_params):
  function gnn_model (line 16) | def gnn_model(LPE, net_params):

FILE: nets/molhiv_graph_regression/SAN.py
  class SAN (line 17) | class SAN(nn.Module):
    method __init__ (line 18) | def __init__(self, net_params):
    method forward (line 51) | def forward(self, g, h, e):
    method loss (line 76) | def loss(self, scores, targets):

FILE: nets/molhiv_graph_regression/SAN_EdgeLPE.py
  class SAN_EdgeLPE (line 17) | class SAN_EdgeLPE(nn.Module):
    method __init__ (line 18) | def __init__(self, net_params):
    method forward (line 58) | def forward(self, g, h, e, diff, product, EigVals):
    method loss (line 104) | def loss(self, scores, targets):

FILE: nets/molhiv_graph_regression/SAN_NodeLPE.py
  class SAN_NodeLPE (line 17) | class SAN_NodeLPE(nn.Module):
    method __init__ (line 18) | def __init__(self, net_params):
    method forward (line 59) | def forward(self, g, h, e, EigVecs, EigVals):
    method loss (line 106) | def loss(self, scores, targets):

FILE: nets/molhiv_graph_regression/load_net.py
  function NodeLPE (line 6) | def NodeLPE(net_params):
  function EdgeLPE (line 9) | def EdgeLPE(net_params):
  function NoLPE (line 12) | def NoLPE(net_params):
  function gnn_model (line 15) | def gnn_model(LPE, net_params):

FILE: nets/molpcba/SAN.py
  class SAN (line 17) | class SAN(nn.Module):
    method __init__ (line 18) | def __init__(self, net_params):
    method forward (line 51) | def forward(self, g, h, e):
    method loss (line 76) | def loss(self, scores, targets):

FILE: nets/molpcba/SAN_EdgeLPE.py
  class SAN_EdgeLPE (line 17) | class SAN_EdgeLPE(nn.Module):
    method __init__ (line 18) | def __init__(self, net_params):
    method forward (line 58) | def forward(self, g, h, e, diff, product, EigVals):
    method loss (line 104) | def loss(self, scores, targets):

FILE: nets/molpcba/SAN_NodeLPE.py
  class SAN_NodeLPE (line 17) | class SAN_NodeLPE(nn.Module):
    method __init__ (line 18) | def __init__(self, net_params):
    method forward (line 69) | def forward(self, g, h, e, EigVecs, EigVals):
    method loss (line 126) | def loss(self, scores, targets):

FILE: nets/molpcba/load_net.py
  function NodeLPE (line 6) | def NodeLPE(net_params):
  function EdgeLPE (line 9) | def EdgeLPE(net_params):
  function NoLPE (line 12) | def NoLPE(net_params):
  function gnn_model (line 15) | def gnn_model(LPE, net_params):

FILE: train/MetricWrapper.py
  class MetricWrapper (line 6) | class MetricWrapper:
    method __init__ (line 12) | def __init__(
    method compute (line 45) | def compute(self, preds: torch.Tensor, target: torch.Tensor) -> torch....
    method __call__ (line 93) | def __call__(self, preds: torch.Tensor, target: torch.Tensor) -> torch...
    method __repr__ (line 99) | def __repr__(self):
    method nan_mean (line 107) | def nan_mean(self, input: Tensor, **kwargs) -> Tensor:

FILE: train/metrics.py
  function MAE (line 10) | def MAE(scores, targets):
  function accuracy_TU (line 16) | def accuracy_TU(scores, targets):
  function accuracy_MNIST_CIFAR (line 22) | def accuracy_MNIST_CIFAR(scores, targets):
  function accuracy_CITATION_GRAPH (line 27) | def accuracy_CITATION_GRAPH(scores, targets):
  function accuracy_SBM (line 34) | def accuracy_SBM(scores, targets):
  function binary_f1_score (line 54) | def binary_f1_score(scores, targets):
  function accuracy_VOC (line 64) | def accuracy_VOC(scores, targets):

FILE: train/train_SBMs_node_classification.py
  function train_epoch (line 12) | def train_epoch(model, optimizer, device, data_loader, epoch, LPE):
  function evaluate_network (line 55) | def evaluate_network(model, device, data_loader, epoch, LPE):

FILE: train/train_ZINC_graph_regression.py
  function train_epoch (line 11) | def train_epoch(model, optimizer, device, data_loader, epoch, LPE):
  function evaluate_network (line 53) | def evaluate_network(model, device, data_loader, epoch, LPE):

FILE: train/train_molhiv.py
  function train_epoch (line 11) | def train_epoch(model, optimizer, device, data_loader, epoch, LPE):
  function evaluate_network (line 68) | def evaluate_network(model, device, data_loader, epoch, LPE):

FILE: train/train_molpcba.py
  function train_epoch (line 14) | def train_epoch(model, optimizer, device, data_loader, epoch, LPE, batch...
  function evaluate_network (line 76) | def evaluate_network(model, device, data_loader, epoch, LPE):