SYMBOL INDEX (45 symbols across 3 files)

FILE: bert_siamese.py
  function to_onehot (line 72) | def to_onehot(a):
  function to_onehot (line 93) | def to_onehot(a):
  class BertLayerNorm (line 243) | class BertLayerNorm(nn.Module):
    method __init__ (line 244) | def __init__(self, hidden_size, eps=1e-12):
    method forward (line 252) | def forward(self, x):
  class BertForSequenceClassification (line 259) | class BertForSequenceClassification(nn.Module):
    method __init__ (line 297) | def __init__(self, num_labels=2): # Change number of labels here.
    method forward_once (line 313) | def forward_once(self, input_ids, token_type_ids=None, attention_mask=...
    method forward (line 320) | def forward(self, input_ids1, input_ids2, input_ids3, credit_sc):
    method freeze_bert_encoder (line 340) | def freeze_bert_encoder(self):
    method unfreeze_bert_encoder (line 344) | def unfreeze_bert_encoder(self):
  class text_dataset (line 416) | class text_dataset(Dataset):
    method __init__ (line 417) | def __init__(self,x_y_list, transform=None):
    method __getitem__ (line 422) | def __getitem__(self,index):
    method __len__ (line 501) | def __len__(self):
  function train_model (line 533) | def train_model(model, criterion, optimizer, scheduler, num_epochs=25):

FILE: bert_siamese_2branch.py
  function to_onehot (line 63) | def to_onehot(a):
  function to_onehot (line 83) | def to_onehot(a):
  class BertLayerNorm (line 227) | class BertLayerNorm(nn.Module):
    method __init__ (line 228) | def __init__(self, hidden_size, eps=1e-12):
    method forward (line 236) | def forward(self, x):
  class BertForSequenceClassification (line 243) | class BertForSequenceClassification(nn.Module):
    method __init__ (line 281) | def __init__(self, num_labels=2): # Change number of labels here.
    method forward_once (line 297) | def forward_once(self, input_ids, token_type_ids=None, attention_mask=...
    method forward (line 304) | def forward(self, input_ids1, input_ids2, credit_sc):
    method freeze_bert_encoder (line 322) | def freeze_bert_encoder(self):
    method unfreeze_bert_encoder (line 326) | def unfreeze_bert_encoder(self):
  class text_dataset (line 395) | class text_dataset(Dataset):
    method __init__ (line 396) | def __init__(self,x_y_list, transform=None):
    method __getitem__ (line 401) | def __getitem__(self,index):
    method __len__ (line 452) | def __len__(self):
  function train_model (line 483) | def train_model(model, criterion, optimizer, scheduler, num_epochs=25):

FILE: main_attention.py
  function to_onehot (line 93) | def to_onehot(a):
  function to_onehot (line 112) | def to_onehot(a):
  class Position_Embedding (line 214) | class Position_Embedding(Layer):
    method __init__ (line 216) | def __init__(self, size=None, mode='sum', **kwargs):
    method call (line 221) | def call(self, x):
    method compute_output_shape (line 238) | def compute_output_shape(self, input_shape):
  class Attention (line 249) | class Attention(Layer):
    method __init__ (line 251) | def __init__(self, nb_head, size_per_head, **kwargs):
    method build (line 257) | def build(self, input_shape):
    method Mask (line 272) | def Mask(self, inputs, seq_len, mode='mul'):
    method call (line 285) | def call(self, x):
    method compute_output_shape (line 311) | def compute_output_shape(self, input_shape):
  function build_model (line 326) | def build_model(config):