SYMBOL INDEX (442 symbols across 44 files)

FILE: CityCode/Base/base_dataloader.py
  class BaseDataLoader (line 8) | class BaseDataLoader(DataLoader):
    method __init__ (line 9) | def __init__(self, dataset, batch_size, shuffle, num_workers, val_spli...
    method _split_sampler (line 28) | def _split_sampler(self, split):
    method get_val_loader (line 47) | def get_val_loader(self):

FILE: CityCode/Base/base_dataset.py
  class BaseDataSet (line 10) | class BaseDataSet(Dataset):
    method __init__ (line 11) | def __init__(self, data_dir, split, mean, std, ignore_index, base_size...
    method _set_files (line 46) | def _set_files(self):
    method _load_data (line 49) | def _load_data(self, index):
    method _rotate (line 52) | def _rotate(self, image, label):
    method _crop (line 62) | def _crop(self, image, label):
    method _flip (line 94) | def _flip(self, image, label):
    method _resize (line 101) | def _resize(self, image, label, bigger_side_to_base_size=True):
    method data_aug (line 135) | def data_aug(images, flag="weak"):
    method _val_augmentation (line 160) | def _val_augmentation(self, image, label):
    method _augmentation (line 169) | def _augmentation(self, image, label):
    method __len__ (line 188) | def __len__(self):
    method __getitem__ (line 191) | def __getitem__(self, index):
    method __repr__ (line 204) | def __repr__(self):

FILE: CityCode/Base/base_model.py
  class BaseModel (line 6) | class BaseModel(nn.Module):
    method __init__ (line 7) | def __init__(self):
    method forward (line 11) | def forward(self):
    method summary (line 14) | def summary(self):
    method __str__ (line 19) | def __str__(self):

FILE: CityCode/Base/base_trainer.py
  function get_instance (line 17) | def get_instance(module, name, config, *args):
  class BaseTrainer (line 21) | class BaseTrainer:
    method __init__ (line 22) | def __init__(self, model, config, iters_per_epoch, train_logger=None, ...
    method train (line 137) | def train(self):
    method _save_checkpoint (line 170) | def _save_checkpoint(self, epoch, name=""):
    method _get_available_devices (line 192) | def _get_available_devices(self, n_gpu):
    method _train_epoch (line 206) | def _train_epoch(self, epoch, id):
    method _valid_epoch (line 209) | def _valid_epoch(self, epoch):
    method _eval_metrics (line 212) | def _eval_metrics(self, output, target):
    method _warm_up (line 215) | def _warm_up(self, epoch, id):

FILE: CityCode/DataLoader/city.py
  class CityDataset (line 11) | class CityDataset(BaseDataSet):
    method __init__ (line 12) | def __init__(self, ddp_training, dgx, **kwargs):
    method _set_files (line 19) | def _set_files(self):
    method _load_data (line 32) | def _load_data(self, index):
  class City (line 44) | class City(BaseDataLoader):
    method __init__ (line 45) | def __init__(self, kwargs, ddp_training=False, dgx=False):

FILE: CityCode/Model/Deeplabv3_plus/Backbones/resnet.py
  function conv3x3 (line 11) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 17) | class BasicBlock(nn.Module):
    method __init__ (line 20) | def __init__(self, inplanes, planes, stride=1, norm_layer=None,
    method forward (line 33) | def forward(self, x):
  class Bottleneck (line 55) | class Bottleneck(nn.Module):
    method __init__ (line 58) | def __init__(self, inplanes, planes, stride=1,
    method forward (line 77) | def forward(self, x):
  class ResNet (line 103) | class ResNet(nn.Module):
    method __init__ (line 104) | def __init__(self, block, layers, norm_layer=nn.BatchNorm2d, bn_eps=1e-5,
    method _make_layer (line 144) | def _make_layer(self, block, norm_layer, planes, blocks, inplace=True,
    method forward (line 166) | def forward(self, x):
  function resnet18 (line 185) | def resnet18(pretrained_model=None, **kwargs):
  function resnet34 (line 193) | def resnet34(pretrained_model=None, **kwargs):
  function resnet50 (line 201) | def resnet50(pretrained_model=None, **kwargs):
  function resnet101 (line 211) | def resnet101(pretrained_model=None, **kwargs):
  function resnet152 (line 219) | def resnet152(pretrained_model=None, **kwargs):

FILE: CityCode/Model/Deeplabv3_plus/EntireModel.py
  class EntireModel (line 11) | class EntireModel(BaseModel):
    method __init__ (line 12) | def __init__(self, num_classes, config, sup_loss=None, cons_w_unsup=No...
    method freeze_teachers_parameters (line 31) | def freeze_teachers_parameters(self):
    method warm_up_forward (line 42) | def warm_up_forward(self, id, x, y):
    method forward (line 55) | def forward(self, x_l=None, target_l=None, x_ul=None, target_ul=None, ...
    method get_other_params (line 84) | def get_other_params(self, id):
    method get_backbone_params (line 92) | def get_backbone_params(self, id):

FILE: CityCode/Model/Deeplabv3_plus/encoder_decoder.py
  class EncoderNetwork (line 11) | class EncoderNetwork(nn.Module):
    method __init__ (line 12) | def __init__(self, num_classes, norm_layer=nn.BatchNorm2d, back_bone=N...
    method _nostride_dilate (line 34) | def _nostride_dilate(self, m, dilate):
    method forward (line 47) | def forward(self, data):
  function _l2_normalize (line 53) | def _l2_normalize(d):
  function get_r_adv_t (line 60) | def get_r_adv_t(x, decoder1, decoder2, it=1, xi=1e-1, eps=10.0):
  class upsample (line 93) | class upsample(nn.Module):
    method __init__ (line 94) | def __init__(self, in_channels, out_channels, data_shape,
    method forward (line 106) | def forward(self, x, data_shape=None):
  class DecoderNetwork (line 120) | class DecoderNetwork(nn.Module):
    method __init__ (line 121) | def __init__(self, num_classes,
    method forward (line 132) | def forward(self, f, data_shape=None):
  class VATDecoderNetwork (line 137) | class VATDecoderNetwork(nn.Module):
    method __init__ (line 138) | def __init__(self, num_classes,
    method forward (line 149) | def forward(self, f, data_shape=None, t_model=None):
  class ASPP (line 158) | class ASPP(nn.Module):
    method __init__ (line 159) | def __init__(self,
    method forward (line 189) | def forward(self, x):
    method _global_pooling (line 210) | def _global_pooling(self, x):
  class Head (line 219) | class Head(nn.Module):
    method __init__ (line 220) | def __init__(self, classify_classes, norm_act=nn.BatchNorm2d, bn_momen...
    method forward (line 239) | def forward(self, f_list):

FILE: CityCode/Model/Deeplabv3_plus/resnet.py
  function conv3x3 (line 11) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 17) | class BasicBlock(nn.Module):
    method __init__ (line 20) | def __init__(self, inplanes, planes, stride=1, norm_layer=None,
    method forward (line 33) | def forward(self, x):
  class Bottleneck (line 55) | class Bottleneck(nn.Module):
    method __init__ (line 58) | def __init__(self, inplanes, planes, stride=1,
    method forward (line 77) | def forward(self, x):
  class ResNet (line 103) | class ResNet(nn.Module):
    method __init__ (line 104) | def __init__(self, block, layers, norm_layer=nn.BatchNorm2d, bn_eps=1e-5,
    method _make_layer (line 144) | def _make_layer(self, block, norm_layer, planes, blocks, inplace=True,
    method forward (line 166) | def forward(self, x):
  function resnet18 (line 185) | def resnet18(pretrained_model=None, **kwargs):
  function resnet34 (line 193) | def resnet34(pretrained_model=None, **kwargs):
  function resnet50 (line 201) | def resnet50(pretrained_model=None, **kwargs):
  function resnet101 (line 211) | def resnet101(pretrained_model=None, **kwargs):
  function resnet152 (line 222) | def resnet152(pretrained_model=None, **kwargs):

FILE: CityCode/Utils/conv_2_5d.py
  function _ntuple (line 15) | def _ntuple(n):
  class Conv2_5D_disp (line 24) | class Conv2_5D_disp(nn.Module):
    method __init__ (line 25) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, p...
    method forward (line 51) | def forward(self, x, disp, camera_params):
    method extra_repr (line 93) | def extra_repr(self):
  class Conv2_5D_depth (line 105) | class Conv2_5D_depth(nn.Module):
    method __init__ (line 106) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, p...
    method forward (line 137) | def forward(self, x, depth, camera_params):
    method extra_repr (line 182) | def extra_repr(self):

FILE: CityCode/Utils/helpers.py
  function __init_weight (line 8) | def __init_weight(feature, conv_init, norm_layer, bn_eps, bn_momentum,
  function init_weight (line 28) | def init_weight(module_list, conv_init, norm_layer, bn_eps, bn_momentum,
  function group_weight (line 38) | def group_weight(weight_group, module, norm_layer, lr):
  function get_voc_pallete (line 79) | def get_voc_pallete(num_classes):
  class DeNormalize (line 97) | class DeNormalize(object):
    method __init__ (line 98) | def __init__(self, mean, std):
    method __call__ (line 102) | def __call__(self, tensor):
  function dir_exists (line 108) | def dir_exists(path):
  function initialize_weights (line 113) | def initialize_weights(*models):
  function colorize_mask (line 128) | def colorize_mask(mask, palette):
  function set_trainable_attr (line 138) | def set_trainable_attr(m, b):
  function apply_leaf (line 143) | def apply_leaf(m, f):
  function set_trainable (line 152) | def set_trainable(l, b):

FILE: CityCode/Utils/logger.py
  class Logger (line 9) | class Logger:
    method __init__ (line 17) | def __init__(self):
    method add_entry (line 20) | def add_entry(self, entry):
    method __str__ (line 23) | def __str__(self):
  function formatter_message (line 36) | def formatter_message(message, use_color=True):
  class ColoredFormatter (line 53) | class ColoredFormatter(logging.Formatter):
    method __init__ (line 54) | def __init__(self, msg, use_color=True):
    method format (line 58) | def format(self, record):
  class ColoredLogger (line 68) | class ColoredLogger(logging.Logger):
    method __init__ (line 72) | def __init__(self, name):

FILE: CityCode/Utils/losses.py
  class ProbOhemCrossEntropy2d (line 8) | class ProbOhemCrossEntropy2d(nn.Module):
    method __init__ (line 9) | def __init__(self, ignore_label, reduction='mean', thresh=0.6, min_kep...
    method forward (line 19) | def forward(self, pred, target):
  class consistency_weight (line 49) | class consistency_weight(object):
    method __init__ (line 54) | def __init__(self, final_w, iters_per_epoch, rampup_starts=0, rampup_e...
    method __call__ (line 63) | def __call__(self, epoch, curr_iter):
  function CE_loss (line 71) | def CE_loss(input_logits, target_targets, ignore_index, temperature=1):
  function softmax_helper (line 79) | def softmax_helper(x):
  function get_alpha (line 88) | def get_alpha(supervised_loader):
  function softmax_helper (line 111) | def softmax_helper(x):
  class FocalLoss (line 120) | class FocalLoss(nn.Module):
    method __init__ (line 135) | def __init__(self, apply_nonlin=None, alpha=None, gamma=2, balance_ind...
    method forward (line 148) | def forward(self, logit, target):
  class abCE_loss (line 211) | class abCE_loss(nn.Module):
    method __init__ (line 216) | def __init__(self, iters_per_epoch, epochs, num_classes, weight=None,
    method threshold (line 233) | def threshold(self, curr_iter, epoch):
    method forward (line 238) | def forward(self, predict, target, ignore_index, curr_iter, epoch):
  function semi_ce_loss (line 268) | def semi_ce_loss(inputs, targets,
  function softmax_mse_loss (line 327) | def softmax_mse_loss(inputs, targets,
  function softmax_kl_loss (line 358) | def softmax_kl_loss(inputs, targets, conf_mask=False, threshold=None, us...
  function softmax_js_loss (line 375) | def softmax_js_loss(inputs, targets, **_):
  function pair_wise_loss (line 386) | def pair_wise_loss(unsup_outputs, size_average=True, nbr_of_pairs=8):

FILE: CityCode/Utils/lr_scheduler.py
  class Step (line 5) | class Step(_LRScheduler):
    method __init__ (line 6) | def __init__(self, optimizer, num_epochs, steps=2, gamma=0.1, last_epo...
    method get_lr (line 12) | def get_lr(self):
  class Poly (line 19) | class Poly(_LRScheduler):
    method __init__ (line 20) | def __init__(self, optimizer, num_epochs, iters_per_epoch, warmup_epoc...
    method get_lr (line 27) | def get_lr(self):
  class OneCycle (line 39) | class OneCycle(_LRScheduler):
    method __init__ (line 40) | def __init__(self, optimizer, num_epochs, iters_per_epoch=0, last_epoc...
    method get_lr (line 54) | def get_lr(self):

FILE: CityCode/Utils/metrics.py
  class AverageMeter (line 7) | class AverageMeter(object):
    method __init__ (line 10) | def __init__(self):
    method initialize (line 17) | def initialize(self, val, weight):
    method update (line 24) | def update(self, val, weight=1):
    method add (line 30) | def add(self, val, weight):
    method value (line 37) | def value(self):
    method average (line 41) | def average(self):
  function batch_pix_accuracy (line 45) | def batch_pix_accuracy(output, target):
  function batch_intersection_union (line 57) | def batch_intersection_union(output, target, num_class):
  function eval_metrics (line 73) | def eval_metrics(output, target, num_classes, ignore_index):
  function pixel_accuracy (line 83) | def pixel_accuracy(output, target):
  function inter_over_union (line 91) | def inter_over_union(output, target, num_class):

FILE: CityCode/Utils/pyt_utils.py
  function load_model (line 25) | def load_model(model, model_file, is_restore=False):
  function load_dualpath_model (line 60) | def load_dualpath_model(model, model_file, is_restore=False):
  function parse_devices (line 127) | def parse_devices(input_devices):
  function extant_file (line 154) | def extant_file(x):
  function link_file (line 165) | def link_file(src, target):
  function ensure_dir (line 171) | def ensure_dir(path):
  function _dbg_interactive (line 181) | def _dbg_interactive(var, value):

FILE: CityCode/Utils/ramps.py
  function gaussian_rampup (line 4) | def gaussian_rampup(start, current, rampup_length):
  function sigmoid_rampup (line 14) | def sigmoid_rampup(current, rampup_length):
  function linear_rampup (line 23) | def linear_rampup(current, rampup_length):
  function cosine_rampup (line 30) | def cosine_rampup(current, rampup_length):
  function log_rampup (line 37) | def log_rampup(current, rampup_length):
  function exp_rampup (line 44) | def exp_rampup(current, rampup_length):

FILE: CityCode/Utils/sliding_evaluator.py
  class SlidingEval (line 7) | class SlidingEval(torch.nn.Module):
    method __init__ (line 8) | def __init__(self, model, crop_size, stride_rate, device, class_number...
    method forward (line 17) | def forward(self, img):
    method process_image (line 25) | def process_image(self, img, crop_size=None):
    method get_2dshape (line 42) | def get_2dshape(self, shape, *, zero=True):
    method pad_image_to_shape (line 57) | def pad_image_to_shape(self, img, shape, border_mode, value):
    method scale_process (line 73) | def scale_process(self, img, ori_shape, device=None):

FILE: CityCode/Utils/tensor_board.py
  class Tensorboard (line 12) | class Tensorboard:
    method __init__ (line 13) | def __init__(self, config, online=False):
    method step_forward (line 29) | def step_forward(self, global_step):
    method upload_single_info (line 32) | def upload_single_info(self, info):
    method upload_wandb_info (line 38) | def upload_wandb_info(self, info_dict):
    method get_class_colors (line 45) | def get_class_colors(*args):
    method set_img_color (line 54) | def set_img_color(colors, background, img, pred):
    method update_wandb_city_image (line 67) | def update_wandb_city_image(self, images,
    method update_table (line 128) | def update_table(self, table_info, axis_name, title=""):
    method de_normalize (line 134) | def de_normalize(self, image):
    method colorize_mask (line 139) | def colorize_mask(self, mask, palette):
    method get_voc_pallete (line 149) | def get_voc_pallete(num_classes):
    method finish (line 167) | def finish():

FILE: CityCode/dgx/download_to_pvc.py
  function get_bucket (line 18) | def get_bucket(bucket_namespace: str, bucket_name: str):
  function download_city_unzip (line 24) | def download_city_unzip(data_dir: str, prefix, pvc=False):
  function upload_checkpoint (line 49) | def upload_checkpoint(local_path: str, prefix: str, checkpoint_filepath:...
  function download_checkpoint (line 61) | def download_checkpoint(checkpoint_filepath: str, prefix: str, bucket_na...

FILE: CityCode/main.py
  function main (line 18) | def main(gpu,  ngpus_per_node, config, args):

FILE: CityCode/train.py
  class Trainer (line 13) | class Trainer(BaseTrainer):
    method __init__ (line 14) | def __init__(self, model, config, supervised_loader, unsupervised_load...
    method update_teachers (line 40) | def update_teachers(self, teacher_encoder, teacher_decoder, keep_rate=...
    method rand_bbox_2 (line 67) | def rand_bbox_2(size, n_boxes=1,
    method cut_mix (line 91) | def cut_mix(self, labeled_image, labeled_mask,
    method predict_with_out_grad (line 115) | def predict_with_out_grad(self, image):
    method assist_mask_calculate (line 135) | def assist_mask_calculate(self, core_predict, assist_predict, topk=1):
    method _warm_up (line 153) | def _warm_up(self, epoch, id):
    method _train_epoch (line 202) | def _train_epoch(self, epoch, id):
    method _valid_epoch (line 315) | def _valid_epoch(self, epoch):
    method _reset_metrics (line 379) | def _reset_metrics(self):
    method _update_losses (line 392) | def _update_losses(self, cur_losses):
    method _compute_metrics (line 402) | def _compute_metrics(self, outputs, target_l, target_ul, sup=False):
    method _update_seg_metrics (line 417) | def _update_seg_metrics(self, correct, labeled, inter, union, supervis...
    method _get_seg_metrics (line 429) | def _get_seg_metrics(self, supervised=True):
    method _log_values (line 443) | def _log_values(self, cur_losses):

FILE: VocCode/Base/base_dataloader.py
  class BaseDataLoader (line 6) | class BaseDataLoader(DataLoader):
    method __init__ (line 7) | def __init__(self, dataset, batch_size, shuffle, num_workers, val_spli...
    method _split_sampler (line 26) | def _split_sampler(self, split):
    method get_val_loader (line 45) | def get_val_loader(self):

FILE: VocCode/Base/base_dataset.py
  class BaseDataSet (line 10) | class BaseDataSet(Dataset):
    method __init__ (line 11) | def __init__(self, data_dir, split, mean, std, ignore_index, base_size...
    method _set_files (line 44) | def _set_files(self):
    method _load_data (line 47) | def _load_data(self, index):
    method _rotate (line 50) | def _rotate(self, image, label):
    method _crop (line 60) | def _crop(self, image, label):
    method _flip (line 92) | def _flip(self, image, label):
    method _resize (line 99) | def _resize(self, image, label, bigger_side_to_base_size=True):
    method data_aug (line 132) | def data_aug(images):
    method _val_augmentation (line 155) | def _val_augmentation(self, image, label):
    method _augmentation (line 164) | def _augmentation(self, image, label):
    method __len__ (line 181) | def __len__(self):
    method __getitem__ (line 184) | def __getitem__(self, index):
    method __repr__ (line 197) | def __repr__(self):

FILE: VocCode/Base/base_model.py
  class BaseModel (line 6) | class BaseModel(nn.Module):
    method __init__ (line 7) | def __init__(self):
    method forward (line 11) | def forward(self):
    method summary (line 14) | def summary(self):
    method __str__ (line 19) | def __str__(self):

FILE: VocCode/Base/base_trainer.py
  function get_instance (line 16) | def get_instance(module, name, config, *args):
  class BaseTrainer (line 20) | class BaseTrainer:
    method __init__ (line 21) | def __init__(self, model, config, iters_per_epoch, train_logger=None, ...
    method train (line 136) | def train(self):
    method _save_checkpoint (line 171) | def _save_checkpoint(self, epoch, name=""):
    method _get_available_devices (line 191) | def _get_available_devices(self, n_gpu):
    method _train_epoch (line 205) | def _train_epoch(self, epoch, id):
    method _valid_epoch (line 208) | def _valid_epoch(self, epoch, id):
    method _eval_metrics (line 211) | def _eval_metrics(self, output, target):
    method _warm_up (line 214) | def _warm_up(self, epoch, id):

FILE: VocCode/DataLoader/voc.py
  function get_voc_pallete (line 11) | def get_voc_pallete(num_classes):
  class VOCDataset (line 29) | class VOCDataset(BaseDataSet):
    method __init__ (line 30) | def __init__(self, ddp_training, dgx, **kwargs):
    method _set_files (line 37) | def _set_files(self):
    method _load_data (line 51) | def _load_data(self, index):
  class VOC (line 63) | class VOC(BaseDataLoader):
    method __init__ (line 64) | def __init__(self, kwargs, ddp_training=False, dgx=False):

FILE: VocCode/Model/Deeplabv3_plus/Backbones/resnet.py
  function conv3x3 (line 11) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 17) | class BasicBlock(nn.Module):
    method __init__ (line 20) | def __init__(self, inplanes, planes, stride=1, norm_layer=None,
    method forward (line 33) | def forward(self, x):
  class Bottleneck (line 55) | class Bottleneck(nn.Module):
    method __init__ (line 58) | def __init__(self, inplanes, planes, stride=1,
    method forward (line 77) | def forward(self, x):
  class ResNet (line 103) | class ResNet(nn.Module):
    method __init__ (line 104) | def __init__(self, block, layers, norm_layer=nn.BatchNorm2d, bn_eps=1e-5,
    method _make_layer (line 144) | def _make_layer(self, block, norm_layer, planes, blocks, inplace=True,
    method forward (line 166) | def forward(self, x):
  function resnet18 (line 185) | def resnet18(pretrained_model=None, **kwargs):
  function resnet34 (line 193) | def resnet34(pretrained_model=None, **kwargs):
  function resnet50 (line 201) | def resnet50(pretrained_model=None, **kwargs):
  function resnet101 (line 211) | def resnet101(pretrained_model=None, **kwargs):
  function resnet152 (line 219) | def resnet152(pretrained_model=None, **kwargs):

FILE: VocCode/Model/Deeplabv3_plus/EntireModel.py
  class EntireModel (line 11) | class EntireModel(BaseModel):
    method __init__ (line 12) | def __init__(self, num_classes, config, sup_loss=None, cons_w_unsup=No...
    method freeze_teachers_parameters (line 31) | def freeze_teachers_parameters(self):
    method warm_up_forward (line 42) | def warm_up_forward(self, id, x, y):
    method forward (line 55) | def forward(self, x_l=None, target_l=None, x_ul=None, target_ul=None, ...
    method get_other_params (line 102) | def get_other_params(self, id):
    method get_backbone_params (line 110) | def get_backbone_params(self, id):

FILE: VocCode/Model/Deeplabv3_plus/encoder_decoder.py
  class EncoderNetwork (line 11) | class EncoderNetwork(nn.Module):
    method __init__ (line 12) | def __init__(self, num_classes, norm_layer=nn.BatchNorm2d, back_bone=N...
    method _nostride_dilate (line 34) | def _nostride_dilate(self, m, dilate):
    method forward (line 47) | def forward(self, data):
  function _l2_normalize (line 53) | def _l2_normalize(d):
  function get_r_adv_t (line 59) | def get_r_adv_t(x, decoder1, decoder2, it=1, xi=1e-1, eps=10.0):
  class upsample (line 92) | class upsample(nn.Module):
    method __init__ (line 93) | def __init__(self, in_channels, out_channels, data_shape,
    method forward (line 105) | def forward(self, x, data_shape=None):
  class DecoderNetwork (line 119) | class DecoderNetwork(nn.Module):
    method __init__ (line 120) | def __init__(self, num_classes,
    method forward (line 131) | def forward(self, f, data_shape=None):
  class VATDecoderNetwork (line 136) | class VATDecoderNetwork(nn.Module):
    method __init__ (line 137) | def __init__(self, num_classes,
    method forward (line 148) | def forward(self, f, data_shape=None, t_model=None):
  class ASPP (line 157) | class ASPP(nn.Module):
    method __init__ (line 158) | def __init__(self,
    method forward (line 188) | def forward(self, x):
    method _global_pooling (line 209) | def _global_pooling(self, x):
  class Head (line 218) | class Head(nn.Module):
    method __init__ (line 219) | def __init__(self, classify_classes, norm_act=nn.BatchNorm2d, bn_momen...
    method forward (line 238) | def forward(self, f_list):

FILE: VocCode/Model/Deeplabv3_plus/resnet.py
  function conv3x3 (line 11) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 17) | class BasicBlock(nn.Module):
    method __init__ (line 20) | def __init__(self, inplanes, planes, stride=1, norm_layer=None,
    method forward (line 33) | def forward(self, x):
  class Bottleneck (line 55) | class Bottleneck(nn.Module):
    method __init__ (line 58) | def __init__(self, inplanes, planes, stride=1,
    method forward (line 77) | def forward(self, x):
  class ResNet (line 103) | class ResNet(nn.Module):
    method __init__ (line 104) | def __init__(self, block, layers, norm_layer=nn.BatchNorm2d, bn_eps=1e-5,
    method _make_layer (line 144) | def _make_layer(self, block, norm_layer, planes, blocks, inplace=True,
    method forward (line 166) | def forward(self, x):
  function resnet18 (line 185) | def resnet18(pretrained_model=None, **kwargs):
  function resnet34 (line 193) | def resnet34(pretrained_model=None, **kwargs):
  function resnet50 (line 201) | def resnet50(pretrained_model=None, **kwargs):
  function resnet101 (line 211) | def resnet101(pretrained_model=None, **kwargs):
  function resnet152 (line 222) | def resnet152(pretrained_model=None, **kwargs):

FILE: VocCode/Utils/conv_2_5d.py
  function _ntuple (line 15) | def _ntuple(n):
  class Conv2_5D_disp (line 24) | class Conv2_5D_disp(nn.Module):
    method __init__ (line 25) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, p...
    method forward (line 51) | def forward(self, x, disp, camera_params):
    method extra_repr (line 93) | def extra_repr(self):
  class Conv2_5D_depth (line 105) | class Conv2_5D_depth(nn.Module):
    method __init__ (line 106) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, p...
    method forward (line 137) | def forward(self, x, depth, camera_params):
    method extra_repr (line 182) | def extra_repr(self):

FILE: VocCode/Utils/helpers.py
  function __init_weight (line 8) | def __init_weight(feature, conv_init, norm_layer, bn_eps, bn_momentum,
  function init_weight (line 28) | def init_weight(module_list, conv_init, norm_layer, bn_eps, bn_momentum,
  function group_weight (line 38) | def group_weight(weight_group, module, norm_layer, lr):
  function get_voc_pallete (line 79) | def get_voc_pallete(num_classes):
  class DeNormalize (line 97) | class DeNormalize(object):
    method __init__ (line 98) | def __init__(self, mean, std):
    method __call__ (line 102) | def __call__(self, tensor):
  function dir_exists (line 108) | def dir_exists(path):
  function initialize_weights (line 113) | def initialize_weights(*models):
  function colorize_mask (line 128) | def colorize_mask(mask, palette):
  function set_trainable_attr (line 138) | def set_trainable_attr(m, b):
  function apply_leaf (line 143) | def apply_leaf(m, f):
  function set_trainable (line 152) | def set_trainable(l, b):

FILE: VocCode/Utils/logger.py
  class Logger (line 9) | class Logger:
    method __init__ (line 17) | def __init__(self):
    method add_entry (line 20) | def add_entry(self, entry):
    method __str__ (line 23) | def __str__(self):
  function formatter_message (line 36) | def formatter_message(message, use_color=True):
  class ColoredFormatter (line 53) | class ColoredFormatter(logging.Formatter):
    method __init__ (line 54) | def __init__(self, msg, use_color=True):
    method format (line 58) | def format(self, record):
  class ColoredLogger (line 68) | class ColoredLogger(logging.Logger):
    method __init__ (line 72) | def __init__(self, name):

FILE: VocCode/Utils/losses.py
  class ConsistencyWeight (line 6) | class ConsistencyWeight(object):
    method __init__ (line 11) | def __init__(self, final_w, iters_per_epoch, rampup_starts=0, rampup_e...
    method __call__ (line 20) | def __call__(self, epoch, curr_iter):
  function CE_loss (line 28) | def CE_loss(input_logits, target_targets, ignore_index, temperature=1):
  function semi_ce_loss (line 35) | def semi_ce_loss(inputs, targets,

FILE: VocCode/Utils/lr_scheduler.py
  class Step (line 5) | class Step(_LRScheduler):
    method __init__ (line 6) | def __init__(self, optimizer, num_epochs, steps=2, gamma=0.1, last_epo...
    method get_lr (line 12) | def get_lr(self):
  class Poly (line 19) | class Poly(_LRScheduler):
    method __init__ (line 20) | def __init__(self, optimizer, num_epochs, iters_per_epoch, warmup_epoc...
    method get_lr (line 27) | def get_lr(self):
  class OneCycle (line 39) | class OneCycle(_LRScheduler):
    method __init__ (line 40) | def __init__(self, optimizer, num_epochs, iters_per_epoch=0, last_epoc...
    method get_lr (line 54) | def get_lr(self):

FILE: VocCode/Utils/metrics.py
  class AverageMeter (line 7) | class AverageMeter(object):
    method __init__ (line 10) | def __init__(self):
    method initialize (line 17) | def initialize(self, val, weight):
    method update (line 24) | def update(self, val, weight=1):
    method add (line 30) | def add(self, val, weight):
    method value (line 37) | def value(self):
    method average (line 41) | def average(self):
  function batch_pix_accuracy (line 45) | def batch_pix_accuracy(output, target):
  function batch_intersection_union (line 57) | def batch_intersection_union(output, target, num_class):
  function eval_metrics (line 73) | def eval_metrics(output, target, num_classes, ignore_index):
  function pixel_accuracy (line 83) | def pixel_accuracy(output, target):
  function inter_over_union (line 91) | def inter_over_union(output, target, num_class):

FILE: VocCode/Utils/pyt_utils.py
  function load_model (line 21) | def load_model(model, model_file, is_restore=False):
  class SquarePad (line 54) | class SquarePad:
    method __call__ (line 55) | def __call__(self, image, output_size):
  class PostAug (line 70) | class PostAug(torch.nn.Module):
    method __init__ (line 71) | def __init__(self, width_size, height_size):
    method zoom_in_operation (line 84) | def zoom_in_operation(self, x, y, y_hat):
    method zoom_out_operation (line 93) | def zoom_out_operation(self, x, y, y_hat):
    method forward (line 111) | def forward(self, x, y, y_hat):

FILE: VocCode/Utils/ramps.py
  function gaussian_rampup (line 4) | def gaussian_rampup(start, current, rampup_length):
  function sigmoid_rampup (line 14) | def sigmoid_rampup(current, rampup_length):
  function linear_rampup (line 23) | def linear_rampup(current, rampup_length):
  function cosine_rampup (line 30) | def cosine_rampup(current, rampup_length):
  function log_rampup (line 37) | def log_rampup(current, rampup_length):
  function exp_rampup (line 44) | def exp_rampup(current, rampup_length):

FILE: VocCode/Utils/tensor_board.py
  class Tensorboard (line 12) | class Tensorboard:
    method __init__ (line 13) | def __init__(self, config, online=False, root_dir="./"):
    method step_forward (line 29) | def step_forward(self, global_step):
    method upload_single_info (line 32) | def upload_single_info(self, info):
    method upload_wandb_info (line 38) | def upload_wandb_info(self, info_dict):
    method update_wandb_voc_bar (line 44) | def update_wandb_voc_bar(self, info_dict, columns, title):
    method update_wandb_image (line 56) | def update_wandb_image(self, images,
    method update_table (line 136) | def update_table(self, table_info, axis_name, title=""):
    method de_normalize (line 142) | def de_normalize(self, image):
    method colorize_mask (line 147) | def colorize_mask(self, mask, palette):
    method get_voc_pallete (line 157) | def get_voc_pallete(num_classes):
    method finish (line 175) | def finish():

FILE: VocCode/dgx/download_to_pvc.py
  function get_bucket (line 18) | def get_bucket(bucket_namespace: str, bucket_name: str):
  function download_voc_unzip (line 24) | def download_voc_unzip(data_dir: str, prefix, pvc=False):
  function upload_checkpoint (line 49) | def upload_checkpoint(local_path: str, prefix: str, checkpoint_filepath:...
  function download_checkpoint (line 62) | def download_checkpoint(checkpoint_filepath: str, prefix: str,

FILE: VocCode/inference.py
  function get_voc_pallete (line 21) | def get_voc_pallete(num_classes):
  class DeNormalize (line 39) | class DeNormalize(object):
    method __init__ (line 40) | def __init__(self, mean, std):
    method __call__ (line 44) | def __call__(self, tensor):
  function running_inference (line 56) | def running_inference(loader, model, folder_name, save_img=False):
  function parse_arguments (line 107) | def parse_arguments():
  function main (line 119) | def main():

FILE: VocCode/main.py
  function main (line 19) | def main(gpu,  ngpus_per_node, config, args):

FILE: VocCode/train.py
  class Trainer (line 14) | class Trainer(BaseTrainer):
    method __init__ (line 15) | def __init__(self, model, config, supervised_loader, unsupervised_load...
    method update_teachers (line 36) | def update_teachers(self, teacher_encoder, teacher_decoder, keep_rate=...
    method rand_bbox_1 (line 63) | def rand_bbox_1(size, lam=None):
    method cut_mix (line 83) | def cut_mix(self, labeled_image, labeled_mask,
    method predict_with_out_grad (line 101) | def predict_with_out_grad(self, image):
    method assist_mask_calculate (line 121) | def assist_mask_calculate(self, core_predict, assist_predict, topk=1):
    method _warm_up (line 139) | def _warm_up(self, epoch, id):
    method _train_epoch (line 189) | def _train_epoch(self, epoch, id):
    method _valid_epoch (line 313) | def _valid_epoch(self, epoch, id):
    method _reset_metrics (line 372) | def _reset_metrics(self):
    method _update_losses (line 385) | def _update_losses(self, cur_losses):
    method _compute_metrics (line 395) | def _compute_metrics(self, outputs, target_l, target_ul, sup=False):
    method _update_seg_metrics (line 410) | def _update_seg_metrics(self, correct, labeled, inter, union, supervis...
    method _get_seg_metrics (line 422) | def _get_seg_metrics(self, supervised=True):
    method _log_values (line 436) | def _log_values(self, cur_losses):