SYMBOL INDEX (45 symbols across 5 files)

FILE: src/layers.py
  function uniform (line 7) | def uniform(size, tensor):
  class SparseNGCNLayer (line 17) | class SparseNGCNLayer(torch.nn.Module):
    method __init__ (line 25) | def __init__(self, in_channels, out_channels, iterations, dropout_rate):
    method define_parameters (line 34) | def define_parameters(self):
    method init_parameters (line 41) | def init_parameters(self):
    method forward (line 48) | def forward(self, normalized_adjacency_matrix, features):
  class DenseNGCNLayer (line 75) | class DenseNGCNLayer(torch.nn.Module):
    method __init__ (line 83) | def __init__(self, in_channels, out_channels, iterations, dropout_rate):
    method define_parameters (line 92) | def define_parameters(self):
    method init_parameters (line 99) | def init_parameters(self):
    method forward (line 106) | def forward(self, normalized_adjacency_matrix, features):
  class ListModule (line 126) | class ListModule(torch.nn.Module):
    method __init__ (line 130) | def __init__(self, *args):
    method __getitem__ (line 140) | def __getitem__(self, idx):
    method __iter__ (line 151) | def __iter__(self):
    method __len__ (line 157) | def __len__(self):

FILE: src/main.py
  function main (line 8) | def main():

FILE: src/param_parser.py
  function parameter_parser (line 5) | def parameter_parser():

FILE: src/trainer_and_networks.py
  class NGCNNetwork (line 7) | class NGCNNetwork(torch.nn.Module):
    method __init__ (line 14) | def __init__(self, args, feature_number, class_number):
    method setup_layer_structure (line 22) | def setup_layer_structure(self):
    method forward (line 30) | def forward(self, normalized_adjacency_matrix, features):
  class MixHopNetwork (line 42) | class MixHopNetwork(torch.nn.Module):
    method __init__ (line 49) | def __init__(self, args, feature_number, class_number):
    method calculate_layer_sizes (line 57) | def calculate_layer_sizes(self):
    method setup_layer_structure (line 63) | def setup_layer_structure(self):
    method calculate_group_loss (line 73) | def calculate_group_loss(self):
    method calculate_loss (line 88) | def calculate_loss(self):
    method forward (line 101) | def forward(self, normalized_adjacency_matrix, features):
  class Trainer (line 113) | class Trainer(object):
    method __init__ (line 122) | def __init__(self, args, graph, features, target, base_run):
    method train_test_split (line 132) | def train_test_split(self):
    method setup_features (line 143) | def setup_features(self):
    method setup_model (line 152) | def setup_model(self):
    method fit (line 161) | def fit(self):
    method score (line 193) | def score(self, indices):
    method evaluate_architecture (line 205) | def evaluate_architecture(self):
    method reset_architecture (line 231) | def reset_architecture(self):

FILE: src/utils.py
  function tab_printer (line 11) | def tab_printer(args):
  function graph_reader (line 23) | def graph_reader(path):
  function feature_reader (line 33) | def feature_reader(path):
  function target_reader (line 56) | def target_reader(path):
  function create_adjacency_matrix (line 65) | def create_adjacency_matrix(graph):
  function normalize_adjacency_matrix (line 80) | def normalize_adjacency_matrix(A, I):
  function create_propagator_matrix (line 94) | def create_propagator_matrix(graph):