SYMBOL INDEX (93 symbols across 8 files)

FILE: code/AVA/dataset.py
  class AVADataset (line 14) | class AVADataset(Dataset):
    method __init__ (line 15) | def __init__(self, path_to_csv, images_path, if_train):
    method __len__ (line 32) | def __len__(self):
    method __getitem__ (line 35) | def __getitem__(self, item):

FILE: code/AVA/option.py
  function init (line 3) | def init():

FILE: code/AVA/train_nni.py
  function adjust_learning_rate (line 25) | def adjust_learning_rate(params, optimizer, epoch):
  function conv_bn (line 32) | def conv_bn(inp, oup, stride):
  function conv_1x1_bn (line 39) | def conv_1x1_bn(inp, oup):
  class InvertedResidual (line 46) | class InvertedResidual(nn.Module):
    method __init__ (line 47) | def __init__(self, inp, oup, stride, expand_ratio):
    method forward (line 68) | def forward(self, x):
  class MobileNetV2 (line 74) | class MobileNetV2(nn.Module):
    method __init__ (line 75) | def __init__(self, n_class=1000, input_size=224, width_mult=1.):
    method forward (line 120) | def forward(self, x):
    method _initialize_weights (line 127) | def _initialize_weights(self):
  function resnet365_backbone (line 142) | def resnet365_backbone():
  function mobile_net_v2 (line 153) | def mobile_net_v2(pretrained=False):
  function Attention (line 162) | def Attention(x):
  function MV2 (line 175) | def MV2():
  class L5 (line 181) | class L5(nn.Module):
    method __init__ (line 182) | def __init__(self):
    method forward (line 193) | def forward(self, x):
  class L1 (line 199) | class L1(nn.Module):
    method __init__ (line 201) | def __init__(self):
    method forward (line 210) | def forward(self, x):
  class TargetNet (line 219) | class TargetNet(nn.Module):
    method __init__ (line 220) | def __init__(self):
    method forward (line 236) | def forward(self, x, paras):
  class TargetFC (line 251) | class TargetFC(nn.Module):
    method __init__ (line 252) | def __init__(self, weight, bias):
    method forward (line 257) | def forward(self, input_):
  class TANet (line 261) | class TANet(nn.Module):
    method __init__ (line 262) | def __init__(self):
    method forward (line 292) | def forward(self, x):
  function get_score (line 312) | def get_score(opt, y_pred):
  function create_data_part (line 323) | def create_data_part(opt):
  function train (line 338) | def train(opt, model, loader, optimizer, criterion, writer=None, global_...
  function validate (line 360) | def validate(opt,model, loader, criterion, writer=None, global_step=None...
  function start_train (line 390) | def start_train(opt):

FILE: code/AVA/util.py
  function download_file (line 7) | def download_file(url, local_filename, chunk_size=1024):
  class AverageMeter (line 17) | class AverageMeter(object):
    method __init__ (line 18) | def __init__(self):
    method reset (line 20) | def reset(self):
    method update (line 26) | def update(self, val, n=1):
  class EDMLoss (line 32) | class EDMLoss(nn.Module):
    method __init__ (line 33) | def __init__(self):
    method forward (line 36) | def forward(self, p_target, p_estimate):

FILE: code/TAD66K/dataset.py
  class AVADataset (line 14) | class AVADataset(Dataset):
    method __init__ (line 15) | def __init__(self, path_to_csv, images_path,if_train):
    method __len__ (line 32) | def __len__(self):
    method __getitem__ (line 35) | def __getitem__(self, item):

FILE: code/TAD66K/option.py
  function init (line 3) | def init():

FILE: code/TAD66K/train_nni.py
  function adjust_learning_rate (line 26) | def adjust_learning_rate(params, optimizer, epoch):
  function conv_bn (line 33) | def conv_bn(inp, oup, stride):
  function conv_1x1_bn (line 40) | def conv_1x1_bn(inp, oup):
  class InvertedResidual (line 47) | class InvertedResidual(nn.Module):
    method __init__ (line 48) | def __init__(self, inp, oup, stride, expand_ratio):
    method forward (line 69) | def forward(self, x):
  class MobileNetV2 (line 75) | class MobileNetV2(nn.Module):
    method __init__ (line 76) | def __init__(self, n_class=1000, input_size=224, width_mult=1.):
    method forward (line 121) | def forward(self, x):
    method _initialize_weights (line 128) | def _initialize_weights(self):
  function resnet365_backbone (line 143) | def resnet365_backbone():
  function mobile_net_v2 (line 154) | def mobile_net_v2(pretrained=False):
  function Attention (line 164) | def Attention(x):
  function MV2 (line 178) | def MV2():
  class L5 (line 183) | class L5(nn.Module):
    method __init__ (line 184) | def __init__(self):
    method forward (line 196) | def forward(self, x):
  class L1 (line 202) | class L1(nn.Module):
    method __init__ (line 204) | def __init__(self):
    method forward (line 215) | def forward(self, x):
  class TargetNet (line 224) | class TargetNet(nn.Module):
    method __init__ (line 226) | def __init__(self):
    method forward (line 242) | def forward(self, x, paras):
  class TargetFC (line 255) | class TargetFC(nn.Module):
    method __init__ (line 256) | def __init__(self, weight, bias):
    method forward (line 261) | def forward(self, input_):
  class TANet (line 265) | class TANet(nn.Module):
    method __init__ (line 266) | def __init__(self):
    method forward (line 296) | def forward(self, x):
  function create_data_part (line 319) | def create_data_part(opt):
  function train (line 330) | def train(opt, model, loader, optimizer, criterion, writer=None, global_...
  function validate (line 351) | def validate(opt,model, loader, criterion, writer=None, global_step=None...
  function start_train (line 381) | def start_train(opt):

FILE: code/TAD66K/util.py
  function download_file (line 7) | def download_file(url, local_filename, chunk_size=1024):
  class AverageMeter (line 17) | class AverageMeter(object):
    method __init__ (line 18) | def __init__(self):
    method reset (line 20) | def reset(self):
    method update (line 26) | def update(self, val, n=1):
  class EDMLoss (line 32) | class EDMLoss(nn.Module):
    method __init__ (line 33) | def __init__(self):
    method forward (line 36) | def forward(self, p_target, p_estimate):