SYMBOL INDEX (131 symbols across 15 files)

FILE: dev.py
  function evaluate (line 29) | def evaluate(opt):

FILE: ensemble_predict.py
  function base_attribution_predict (line 32) | def base_attribution_predict(examples, model, device, tokenizer, desc):
  function ensemble_attribution (line 94) | def ensemble_attribution(version):

FILE: predict_preliminary.py
  function trigger_evaluation_v1 (line 33) | def trigger_evaluation_v1(model, dev_info, device, **kwargs):
  function role_evaluation (line 92) | def role_evaluation(model, dev_info, device, **kwargs):
  function attribution_evaluation (line 178) | def attribution_evaluation(model, dev_info, device, **kwargs):
  function evaluate (line 260) | def evaluate(opt,dev_file='dev.json',force_one=True,model_name=None,dev_...

FILE: src_final/preprocess/convert_raw_data.py
  function load_examples (line 18) | def load_examples(file_path):
  function save_info (line 24) | def save_info(data_dir, data, desc):
  function find_pair (line 29) | def find_pair(before, role, nexts, pair=("《", "》")):
  function clean_data (line 54) | def clean_data(raw_pre_examples):
  function convert_raw_data (line 79) | def convert_raw_data(data_dir, save_data=False, save_dict=False):
  function split_preliminary_trigger_data (line 235) | def split_preliminary_trigger_data(base_dir, save_dir):
  function split_preliminary_trigger_third_data (line 277) | def split_preliminary_trigger_third_data(bert_dir, base_dir, ckpt_path):
  function split_preliminary_role_data (line 387) | def split_preliminary_role_data(base_dir, save_dir):

FILE: src_final/preprocess/convert_raw_data_preliminary.py
  function convert_raw_data (line 20) | def convert_raw_data(data_dir, save_data=False, save_dict=False,use_clea...

FILE: src_final/preprocess/processor.py
  class BaseExample (line 38) | class BaseExample:
    method __init__ (line 39) | def __init__(self,
  class TriggerExample (line 48) | class TriggerExample(BaseExample):
    method __init__ (line 49) | def __init__(self,
  class RoleExample (line 60) | class RoleExample(BaseExample):
    method __init__ (line 61) | def __init__(self,
  class AttributionExample (line 73) | class AttributionExample(BaseExample):
    method __init__ (line 74) | def __init__(self,
  class BaseFeature (line 85) | class BaseFeature:
    method __init__ (line 86) | def __init__(self,
  class TriggerFeature (line 97) | class TriggerFeature(BaseFeature):
    method __init__ (line 98) | def __init__(self,
  class RoleFeature (line 111) | class RoleFeature(BaseFeature):
    method __init__ (line 112) | def __init__(self,
  class AttributionFeature (line 132) | class AttributionFeature(BaseFeature):
    method __init__ (line 133) | def __init__(self,
  class BaseProcessor (line 148) | class BaseProcessor:
    method read_json (line 150) | def read_json(file_path):
  class TriggerProcessor (line 156) | class TriggerProcessor(BaseProcessor):
    method _example_generator (line 159) | def _example_generator(raw_examples, set_type):
    method get_train_examples (line 182) | def get_train_examples(self, raw_examples):
    method get_dev_examples (line 185) | def get_dev_examples(self, raw_examples):
  class RoleProcessor (line 189) | class RoleProcessor(BaseProcessor):
    method _example_generator (line 192) | def _example_generator(raw_examples, set_type):
    method get_train_examples (line 237) | def get_train_examples(self, raw_examples):
    method get_dev_examples (line 240) | def get_dev_examples(self, raw_examples):
  class AttributionProcessor (line 244) | class AttributionProcessor(BaseProcessor):
    method _example_generator (line 247) | def _example_generator(raw_examples, set_type):
    method get_train_examples (line 271) | def get_train_examples(self, raw_examples):
    method get_dev_examples (line 274) | def get_dev_examples(self, raw_examples):
  function search_label_index (line 278) | def search_label_index(tokens, label_tokens):
  function fine_grade_tokenize (line 297) | def fine_grade_tokenize(raw_text, tokenizer):
  function convert_trigger_example (line 316) | def convert_trigger_example(ex_idx, example: TriggerExample, max_seq_len...
  function convert_role1_example (line 396) | def convert_role1_example(ex_idx, example: RoleExample, max_seq_len, tok...
  function convert_role2_example (line 496) | def convert_role2_example(ex_idx, example: RoleExample, max_seq_len, tok...
  function convert_attribution_example (line 592) | def convert_attribution_example(ex_idx, example: AttributionExample, max...
  function convert_examples_to_features (line 650) | def convert_examples_to_features(task_type, examples, bert_dir, max_seq_...

FILE: src_final/utils/attack_train_utils.py
  class FGM (line 15) | class FGM:
    method __init__ (line 16) | def __init__(self, model: nn.Module, eps=1.):
    method attack (line 24) | def attack(self, emb_name='word_embeddings'):
    method restore (line 33) | def restore(self, emb_name='word_embeddings'):
  class PGD (line 43) | class PGD:
    method __init__ (line 44) | def __init__(self, model, eps=1., alpha=0.3):
    method attack (line 53) | def attack(self, emb_name='word_embeddings', is_first_attack=False):
    method restore (line 64) | def restore(self, emb_name='word_embeddings'):
    method project (line 71) | def project(self, param_name, param_data):
    method backup_grad (line 77) | def backup_grad(self):
    method restore_grad (line 82) | def restore_grad(self):

FILE: src_final/utils/dataset_utils.py
  class BaseDataset (line 14) | class BaseDataset(Dataset):
    method __init__ (line 15) | def __init__(self, features, mode):
    method __len__ (line 26) | def __len__(self):
  class TriggerDataset (line 30) | class TriggerDataset(BaseDataset):
    method __init__ (line 31) | def __init__(self,
    method __getitem__ (line 43) | def __getitem__(self, index):
  class RoleDataset (line 57) | class RoleDataset(BaseDataset):
    method __init__ (line 58) | def __init__(self,
    method __getitem__ (line 70) | def __getitem__(self, index):
  class AttributionDataset (line 85) | class AttributionDataset(BaseDataset):
    method __init__ (line 86) | def __init__(self,
    method __getitem__ (line 95) | def __getitem__(self, index):
  function build_dataset (line 108) | def build_dataset(task_type, features, mode, **kwargs):

FILE: src_final/utils/evaluator.py
  function get_base_out (line 20) | def get_base_out(model, loader, device, task_type):
  function pointer_trigger_decode (line 37) | def pointer_trigger_decode(logits, raw_text, distant_triggers, start_thr...
  function pointer_decode (line 88) | def pointer_decode(logits, raw_text, start_threshold=0.5, end_threshold=...
  function crf_decode (line 141) | def crf_decode(decode_tokens, raw_text, id2label):
  function calculate_metric (line 197) | def calculate_metric(gt, predict):
  function get_p_r_f (line 217) | def get_p_r_f(tp, fp, fn):
  function trigger_evaluation (line 224) | def trigger_evaluation(model, dev_info, device, **kwargs):
  function role1_evaluation (line 275) | def role1_evaluation(model, dev_info, device, **kwargs):
  function role2_evaluation (line 331) | def role2_evaluation(model, dev_info, device):
  function attribution_evaluation (line 381) | def attribution_evaluation(model, dev_info, device, **kwargs):

FILE: src_final/utils/functions_utils.py
  function set_seed (line 21) | def set_seed(seed):
  function prepare_info (line 33) | def prepare_info(task_type, mid_data_dir):
  function prepare_para_dict (line 57) | def prepare_para_dict(opt, info_dict):
  function load_model_and_parallel (line 78) | def load_model_and_parallel(model, gpu_ids, ckpt_path=None, strict=True):
  function get_model_path_list (line 104) | def get_model_path_list(base_dir):
  function swa (line 121) | def swa(model, model_dir, swa_start=1):

FILE: src_final/utils/model_utils.py
  class ConditionalLayerNorm (line 17) | class ConditionalLayerNorm(nn.Module):
    method __init__ (line 18) | def __init__(self,
    method reset_weight_and_bias (line 33) | def reset_weight_and_bias(self):
    method forward (line 43) | def forward(self, inputs, cond=None):
  class BaseModel (line 63) | class BaseModel(nn.Module):
    method __init__ (line 64) | def __init__(self,
    method _init_weights (line 80) | def _init_weights(blocks, **kwargs):
    method _batch_gather (line 95) | def _batch_gather(data: torch.Tensor, index: torch.Tensor):
  class TriggerExtractor (line 107) | class TriggerExtractor(BaseModel):
    method __init__ (line 108) | def __init__(self,
    method forward (line 146) | def forward(self,
  class Role1Extractor (line 182) | class Role1Extractor(BaseModel):
    method __init__ (line 183) | def __init__(self,
    method forward (line 228) | def forward(self,
  class Role2Extractor (line 282) | class Role2Extractor(BaseModel):
    method __init__ (line 283) | def __init__(self,
    method forward (line 325) | def forward(self,
  class AttributionClassifier (line 376) | class AttributionClassifier(BaseModel):
    method __init__ (line 377) | def __init__(self,
    method forward (line 396) | def forward(self,
  function build_model (line 441) | def build_model(task_type, bert_dir, **kwargs):

FILE: src_final/utils/options.py
  class BaseArgs (line 13) | class BaseArgs:
    method parse (line 15) | def parse():
    method initialize (line 20) | def initialize(parser: argparse.ArgumentParser):
    method get_parser (line 76) | def get_parser(self):
  class TrainArgs (line 82) | class TrainArgs(BaseArgs):
    method initialize (line 84) | def initialize(parser: argparse.ArgumentParser):
  class DevArgs (line 119) | class DevArgs(BaseArgs):
    method initialize (line 121) | def initialize(parser: argparse.ArgumentParser):
  class TestArgs (line 133) | class TestArgs(BaseArgs):
    method initialize (line 135) | def initialize(parser: argparse.ArgumentParser):

FILE: src_final/utils/trainer.py
  function save_model (line 23) | def save_model(opt, model, global_step):
  function build_optimizer_and_scheduler (line 36) | def build_optimizer_and_scheduler(opt, model, t_total):
  function train (line 77) | def train(opt, model, train_dataset):

FILE: test.py
  function pipeline_predict (line 35) | def pipeline_predict(opt):

FILE: train.py
  function train_base (line 32) | def train_base(opt, info_dict, train_examples, dev_info=None):
  function training (line 112) | def training(opt):
  function stacking (line 155) | def stacking(opt):