SYMBOL INDEX (199 symbols across 17 files)

FILE: DN4_2019_Version/DN4_Test_5way1shot.py
  function validate (line 93) | def validate(val_loader, model, criterion, epoch_index, F_txt):
  class AverageMeter (line 163) | class AverageMeter(object):
    method __init__ (line 165) | def __init__(self):
    method reset (line 168) | def reset(self):
    method update (line 174) | def update(self, val, n=1):
  function accuracy (line 182) | def accuracy(output, target, topk=(1,)):
  function mean_confidence_interval (line 199) | def mean_confidence_interval(data, confidence=0.95):

FILE: DN4_2019_Version/DN4_Test_5way5shot.py
  function validate (line 93) | def validate(val_loader, model, criterion, epoch_index, F_txt):
  class AverageMeter (line 163) | class AverageMeter(object):
    method __init__ (line 165) | def __init__(self):
    method reset (line 168) | def reset(self):
    method update (line 174) | def update(self, val, n=1):
  function accuracy (line 182) | def accuracy(output, target, topk=(1,)):
  function mean_confidence_interval (line 199) | def mean_confidence_interval(data, confidence=0.95):

FILE: DN4_2019_Version/DN4_Train_5way1shot.py
  function adjust_learning_rate (line 90) | def adjust_learning_rate(optimizer, epoch_num):
  function train (line 97) | def train(train_loader, model, criterion, optimizer, epoch_index, F_txt):
  function validate (line 165) | def validate(val_loader, model, criterion, epoch_index, best_prec1, F_txt):
  function save_checkpoint (line 236) | def save_checkpoint(state, filename='checkpoint.pth.tar'):
  class AverageMeter (line 240) | class AverageMeter(object):
    method __init__ (line 242) | def __init__(self):
    method reset (line 245) | def reset(self):
    method update (line 251) | def update(self, val, n=1):
  function accuracy (line 258) | def accuracy(output, target, topk=(1,)):

FILE: DN4_2019_Version/DN4_Train_5way1shot_DA.py
  function adjust_learning_rate (line 90) | def adjust_learning_rate(optimizer, epoch_num):
  function train (line 97) | def train(train_loader, model, criterion, optimizer, epoch_index, F_txt):
  function validate (line 165) | def validate(val_loader, model, criterion, epoch_index, best_prec1, F_txt):
  function save_checkpoint (line 236) | def save_checkpoint(state, filename='checkpoint.pth.tar'):
  class AverageMeter (line 240) | class AverageMeter(object):
    method __init__ (line 242) | def __init__(self):
    method reset (line 245) | def reset(self):
    method update (line 251) | def update(self, val, n=1):
  function accuracy (line 258) | def accuracy(output, target, topk=(1,)):

FILE: DN4_2019_Version/DN4_Train_5way1shot_Resnet.py
  function adjust_learning_rate (line 90) | def adjust_learning_rate(optimizer, epoch_num):
  function train (line 97) | def train(train_loader, model, criterion, optimizer, epoch_index, F_txt):
  function validate (line 165) | def validate(val_loader, model, criterion, epoch_index, best_prec1, F_txt):
  function save_checkpoint (line 236) | def save_checkpoint(state, filename='checkpoint.pth.tar'):
  class AverageMeter (line 240) | class AverageMeter(object):
    method __init__ (line 242) | def __init__(self):
    method reset (line 245) | def reset(self):
    method update (line 251) | def update(self, val, n=1):
  function accuracy (line 258) | def accuracy(output, target, topk=(1,)):

FILE: DN4_2019_Version/DN4_Train_5way5shot.py
  function adjust_learning_rate (line 90) | def adjust_learning_rate(optimizer, epoch_num):
  function train (line 97) | def train(train_loader, model, criterion, optimizer, epoch_index, F_txt):
  function validate (line 165) | def validate(val_loader, model, criterion, epoch_index, best_prec1, F_txt):
  function save_checkpoint (line 236) | def save_checkpoint(state, filename='checkpoint.pth.tar'):
  class AverageMeter (line 240) | class AverageMeter(object):
    method __init__ (line 242) | def __init__(self):
    method reset (line 245) | def reset(self):
    method update (line 251) | def update(self, val, n=1):
  function accuracy (line 258) | def accuracy(output, target, topk=(1,)):

FILE: DN4_2019_Version/DN4_Train_5way5shot_DA.py
  function adjust_learning_rate (line 90) | def adjust_learning_rate(optimizer, epoch_num):
  function train (line 97) | def train(train_loader, model, criterion, optimizer, epoch_index, F_txt):
  function validate (line 165) | def validate(val_loader, model, criterion, epoch_index, best_prec1, F_txt):
  function save_checkpoint (line 236) | def save_checkpoint(state, filename='checkpoint.pth.tar'):
  class AverageMeter (line 240) | class AverageMeter(object):
    method __init__ (line 242) | def __init__(self):
    method reset (line 245) | def reset(self):
    method update (line 251) | def update(self, val, n=1):
  function accuracy (line 258) | def accuracy(output, target, topk=(1,)):

FILE: DN4_2019_Version/DN4_Train_5way5shot_Resnet.py
  function adjust_learning_rate (line 90) | def adjust_learning_rate(optimizer, epoch_num):
  function train (line 97) | def train(train_loader, model, criterion, optimizer, epoch_index, F_txt):
  function validate (line 165) | def validate(val_loader, model, criterion, epoch_index, best_prec1, F_txt):
  function save_checkpoint (line 236) | def save_checkpoint(state, filename='checkpoint.pth.tar'):
  class AverageMeter (line 240) | class AverageMeter(object):
    method __init__ (line 242) | def __init__(self):
    method reset (line 245) | def reset(self):
    method update (line 251) | def update(self, val, n=1):
  function accuracy (line 258) | def accuracy(output, target, topk=(1,)):

FILE: DN4_2019_Version/dataset/datasets_csv.py
  function pil_loader (line 16) | def pil_loader(path):
  function accimage_loader (line 23) | def accimage_loader(path):
  function gray_loader (line 32) | def gray_loader(path):
  function default_loader (line 38) | def default_loader(path):
  function find_classes (line 46) | def find_classes(dir):
  class Imagefolder_csv (line 54) | class Imagefolder_csv(object):
    method __init__ (line 61) | def __init__(self, data_dir="", mode="train", image_size=84, data_name...
    method __len__ (line 238) | def __len__(self):
    method __getitem__ (line 242) | def __getitem__(self, index):

FILE: DN4_2019_Version/models/network.py
  function weights_init_normal (line 22) | def weights_init_normal(m):
  function weights_init_xavier (line 34) | def weights_init_xavier(m):
  function weights_init_kaiming (line 46) | def weights_init_kaiming(m):
  function weights_init_orthogonal (line 58) | def weights_init_orthogonal(m):
  function init_weights (line 70) | def init_weights(net, init_type='normal'):
  function get_norm_layer (line 84) | def get_norm_layer(norm_type='instance'):
  function define_DN4Net (line 97) | def define_DN4Net(pretrained=False, model_root=None, which_model='Conv64...
  function print_network (line 122) | def print_network(net):
  class FourLayer_64F (line 143) | class FourLayer_64F(nn.Module):
    method __init__ (line 144) | def __init__(self, norm_layer=nn.BatchNorm2d, num_classes=5, neighbor_...
    method forward (line 176) | def forward(self, input1, input2):
  class ImgtoClass_Metric (line 199) | class ImgtoClass_Metric(nn.Module):
    method __init__ (line 200) | def __init__(self, neighbor_k=3):
    method cal_cosinesimilarity (line 206) | def cal_cosinesimilarity(self, input1, input2):
    method forward (line 239) | def forward(self, x1, x2):
  class ResBlock (line 261) | class ResBlock(nn.Module):
    method __init__ (line 262) | def __init__(self, nFin, nFout):
    method forward (line 279) | def forward(self, x):
  class ResNetLike (line 284) | class ResNetLike(nn.Module):
    method __init__ (line 285) | def __init__(self, opt, neighbor_k=3):
    method forward (line 330) | def forward(self, input1, input2):

FILE: Test_DN4.py
  function test (line 111) | def test(test_loader, model, criterion, epoch_index, best_prec1, F_txt):

FILE: Train_DN4.py
  function train (line 108) | def train(train_loader, model, criterion, optimizer, epoch_index, F_txt):
  function validate (line 175) | def validate(val_loader, model, criterion, epoch_index, best_prec1, F_txt):

FILE: dataset/general_dataloader.py
  function pil_loader (line 18) | def pil_loader(path):
  function RGB_loader (line 24) | def RGB_loader(path):
  function accimage_loader (line 28) | def accimage_loader(path):
  function gray_loader (line 37) | def gray_loader(path):
  function default_loader (line 43) | def default_loader(path):
  function find_classes (line 51) | def find_classes(dir):
  function load_csv2dict (line 59) | def load_csv2dict(csv_path):
  function data_split (line 82) | def data_split(data_dir, class_img_dict, class_list, class_to_idx, mode):
  function read_dataset (line 149) | def read_dataset(data_dir):
  function episode_sampling (line 158) | def episode_sampling(data_dir, class_list, class_img_dict, episode_num, ...
  class GeneralDataSet (line 197) | class GeneralDataSet(object):
    method __init__ (line 201) | def __init__(self, opt, transform=None, mode='train', loader=RGB_loader):
    method __len__ (line 241) | def __len__(self):
    method __getitem__ (line 245) | def __getitem__(self, index):
  class FewShotDataSet (line 263) | class FewShotDataSet(object):
    method __init__ (line 267) | def __init__(self, opt, transform=None, support_transform=None, mode='...
    method __len__ (line 309) | def __len__(self):
    method __getitem__ (line 313) | def __getitem__(self, index):
  function get_dataloader (line 415) | def get_dataloader(opt, modes):
  function get_Fewshot_dataloader (line 481) | def get_Fewshot_dataloader(opt, modes):

FILE: models/backbone.py
  class Conv64F (line 17) | class Conv64F(nn.Module):
    method __init__ (line 26) | def __init__(self):
    method forward (line 65) | def forward(self, x):
  class Conv64F_Local (line 73) | class Conv64F_Local(nn.Module):
    method __init__ (line 81) | def __init__(self):
    method forward (line 118) | def forward(self, x):
  function init_layer (line 135) | def init_layer(L):
  class Flatten (line 145) | class Flatten(nn.Module):
    method __init__ (line 146) | def __init__(self):
    method forward (line 149) | def forward(self, x):
  class SimpleBlock (line 154) | class SimpleBlock(nn.Module):
    method __init__ (line 156) | def __init__(self, indim, outdim, half_res):
    method forward (line 195) | def forward(self, x):
  class BottleneckBlock (line 209) | class BottleneckBlock(nn.Module):
    method __init__ (line 211) | def __init__(self, indim, outdim, half_res):
    method forward (line 252) | def forward(self, x):
  class ResNet_224 (line 270) | class ResNet_224(nn.Module):
    method __init__ (line 272) | def __init__(self,block,list_of_num_layers, list_of_out_dims, No_pool=...
    method forward (line 317) | def forward(self,x):
  function conv3x3 (line 331) | def conv3x3(in_planes, out_planes, stride=1):
  class SELayer (line 337) | class SELayer(nn.Module):
    method __init__ (line 338) | def __init__(self, channel, reduction=16):
    method forward (line 348) | def forward(self, x):
  class DropBlock (line 355) | class DropBlock(nn.Module):
    method __init__ (line 356) | def __init__(self, block_size):
    method forward (line 363) | def forward(self, x, gamma):
    method _compute_block_mask (line 379) | def _compute_block_mask(self, mask):
  class BasicBlock (line 412) | class BasicBlock(nn.Module):
    method __init__ (line 415) | def __init__(self, inplanes, planes, stride=1, downsample=None, drop_r...
    method forward (line 438) | def forward(self, x):
  class ResNet_84 (line 475) | class ResNet_84(nn.Module):
    method __init__ (line 477) | def __init__(self, block, n_blocks, keep_prob=1.0, avg_pool=False, fla...
    method _make_layer (line 512) | def _make_layer(self, block, n_block, planes, stride=1, drop_rate=0.0,...
    method forward (line 539) | def forward(self, x, is_feat=False, rot=False):
  function ResNet12 (line 568) | def ResNet12(keep_prob=1.0, avg_pool=False, flatten=False, **kwargs):
  function SeResNet12 (line 573) | def SeResNet12(keep_prob=1.0, avg_pool=False, flatten=False, **kwargs):
  function ResNet10 (line 578) | def ResNet10(flatten = False):
  function ResNet18 (line 581) | def ResNet18(flatten = False):
  function ResNet34 (line 584) | def ResNet34(flatten = False):
  function ResNet50 (line 587) | def ResNet50(flatten = False):
  function ResNet101 (line 590) | def ResNet101(flatten = False):

FILE: models/classifier.py
  class Prototype_Metric (line 14) | class Prototype_Metric(nn.Module):
    method __init__ (line 20) | def __init__(self, way_num=5, shot_num=5, neighbor_k=3):
    method cal_EuclideanDis (line 27) | def cal_EuclideanDis(self, input1, input2):
    method forward (line 53) | def forward(self, x1, x2):
  class ImgtoClass_Metric (line 62) | class ImgtoClass_Metric(nn.Module):
    method __init__ (line 67) | def __init__(self, way_num=5, shot_num=5, neighbor_k=3):
    method cal_cosinesimilarity (line 74) | def cal_cosinesimilarity(self, input1, input2):
    method forward (line 115) | def forward(self, x1, x2):

FILE: models/network.py
  function weights_init_normal (line 47) | def weights_init_normal(m):
  function weights_init_xavier (line 60) | def weights_init_xavier(m):
  function weights_init_kaiming (line 72) | def weights_init_kaiming(m):
  function weights_init_orthogonal (line 84) | def weights_init_orthogonal(m):
  function init_weights (line 96) | def init_weights(net, init_type='normal'):
  function get_norm_layer (line 110) | def get_norm_layer(norm_type='instance'):
  function print_network (line 122) | def print_network(net):
  function define_model (line 131) | def define_model(pretrained=False, model_root=None, encoder_model='Conv6...
  class Fewshot_model (line 158) | class Fewshot_model(nn.Module):
    method __init__ (line 162) | def __init__(self, encoder_model='Conv64F', classifier_model='DN4', cl...
    method forward (line 200) | def forward(self, input1, input2, is_feature=False):
  class Model_with_reused_Encoder (line 214) | class Model_with_reused_Encoder(nn.Module):
    method __init__ (line 218) | def __init__(self, pre_trained_model, new_classifier='DN4', way_num=5,...
    method forward (line 234) | def forward(self, input1, input2):

FILE: utils.py
  function adjust_learning_rate (line 12) | def adjust_learning_rate(opt, optimizer, epoch, F_txt):
  function adjust_learning_rate2 (line 24) | def adjust_learning_rate2(opt, optimizer, epoch, F_txt):
  function count_parameters (line 35) | def count_parameters(model):
  function save_checkpoint (line 40) | def save_checkpoint(state, filename='checkpoint.pth.tar'):
  class AverageMeter (line 44) | class AverageMeter(object):
    method __init__ (line 46) | def __init__(self):
    method reset (line 49) | def reset(self):
    method update (line 55) | def update(self, val, n=1):
  function accuracy (line 62) | def accuracy(output, target, topk=(1,)):
  function mean_confidence_interval (line 79) | def mean_confidence_interval(data, confidence=0.95):
  function set_save_path (line 88) | def set_save_path(opt):
  function set_save_test_path (line 110) | def set_save_test_path(opt, finetune=False):
  function set_save_test_path2 (line 132) | def set_save_test_path2(opt, finetune=False):
  function get_resume_file (line 159) | def get_resume_file(checkpoint_dir, F_txt):
  function plot_loss_curve (line 176) | def plot_loss_curve(opt, train_loss, val_loss, test_loss=None):