SYMBOL INDEX (147 symbols across 8 files)

FILE: DSAModules.py
  function conv3x3 (line 28) | def conv3x3(in_planes, out_planes, stride=1, padding=1, dilation=1):
  class BasicBlock (line 33) | class BasicBlock(nn.Module):
    method __init__ (line 36) | def __init__(self, inplanes, planes, stride=1, downsample=None,
    method forward (line 50) | def forward(self, x):
  class Bottleneck (line 69) | class Bottleneck(nn.Module):
    method __init__ (line 72) | def __init__(self, inplanes, planes, stride=1, downsample=None,
    method forward (line 87) | def forward(self, x):
  class DRN (line 110) | class DRN(nn.Module):
    method __init__ (line 112) | def __init__(self, block, layers, num_classes=1000,
    method _make_layer (line 178) | def _make_layer(self, block, planes, blocks, stride=1, dilation=1,
    method _make_conv_layers (line 206) | def _make_conv_layers(self, channels, convs, stride=1, dilation=1):
    method forward (line 219) | def forward(self, x):
  class _UpProjection (line 267) | class _UpProjection(nn.Sequential):
    method __init__ (line 269) | def __init__(self, num_input_features, num_output_features):
    method forward (line 287) | def forward(self, x, size):
  class AutoED (line 300) | class AutoED(nn.Module):
    method __init__ (line 301) | def __init__(self, model):
    method freeze_bn (line 306) | def freeze_bn(self):
    method forward (line 312) | def forward(self, x):
  class _E (line 319) | class _E(nn.Module):
    method __init__ (line 320) | def __init__(self, model):
    method forward (line 324) | def forward(self, x):
  class _D (line 338) | class _D(nn.Module):
    method __init__ (line 339) | def __init__(self):
    method forward (line 355) | def forward(self, x, size1, size2, size3):
  class DRN_A (line 369) | class DRN_A(nn.Module):
    method __init__ (line 371) | def __init__(self, block, layers, num_classes=1000):
    method _make_layer (line 404) | def _make_layer(self, block, planes, blocks, stride=1, dilation=1):
    method forward (line 422) | def forward(self, x):
  function drn_a_50 (line 440) | def drn_a_50(pretrained=False, **kwargs):
  function drn_c_26 (line 447) | def drn_c_26(pretrained=False, **kwargs):
  function drn_c_42 (line 454) | def drn_c_42(pretrained=False, **kwargs):
  function drn_c_58 (line 461) | def drn_c_58(pretrained=False, **kwargs):
  function drn_d_22 (line 468) | def drn_d_22(pretrained=False, **kwargs):
  function drn_d_24 (line 475) | def drn_d_24(pretrained=False, **kwargs):
  function drn_d_38 (line 482) | def drn_d_38(pretrained=False, **kwargs):
  function drn_d_40 (line 489) | def drn_d_40(pretrained=False, **kwargs):
  function drn_d_54 (line 496) | def drn_d_54(pretrained=False, **kwargs):
  function drn_d_56 (line 503) | def drn_d_56(pretrained=False, **kwargs):
  function drn_d_105 (line 510) | def drn_d_105(pretrained=False, **kwargs):
  function drn_d_107 (line 517) | def drn_d_107(pretrained=False, **kwargs):

FILE: loaddata.py
  function get_dataset (line 18) | def get_dataset(root, data_file='train.list',
  class KittiDataset (line 39) | class KittiDataset(data.Dataset):
    method __init__ (line 40) | def __init__(self, root='./datasets', data_file='tgt_train.list', phas...
    method __len__ (line 64) | def __len__(self):
    method read_data (line 67) | def read_data(self, datafiles):
    method __getitem__ (line 85) | def __getitem__(self, index):
  class VKittiDataset (line 123) | class VKittiDataset(data.Dataset):
    method __init__ (line 124) | def __init__(self, root='./datasets', data_file='src_train.list',
    method __len__ (line 148) | def __len__(self):
    method read_data (line 151) | def read_data(self, datafiles):
    method __getitem__ (line 159) | def __getitem__(self, index):
  class NYUD_V2Dataset (line 192) | class NYUD_V2Dataset(data.Dataset):
    method __init__ (line 193) | def __init__(self, root='./datasets', data_file='nyu_data.txt', phase=...
    method __len__ (line 204) | def __len__(self):
    method read_data (line 207) | def read_data(self, datafiles):
    method __getitem__ (line 215) | def __getitem__(self, index):
  class SUNCGDataset (line 251) | class SUNCGDataset(data.Dataset):
    method __init__ (line 252) | def __init__(self, root='./suncg_datasets', data_file='suncg_train.txt',
    method __len__ (line 275) | def __len__(self):
    method read_data (line 278) | def read_data(self, datafiles):
    method __getitem__ (line 288) | def __getitem__(self, index):
  class DepthToTensor (line 322) | class DepthToTensor(object):
    method __call__ (line 323) | def __call__(self, input):
  function creat_train_dataloader (line 330) | def creat_train_dataloader(dataset, root, data_file, batchsize, nThreads,
  function create_test_dataloader (line 349) | def create_test_dataloader(dataset, root, data_file, batchsize, nThreads...
  class KITTI (line 376) | class KITTI:
    method read_calib_file (line 377) | def read_calib_file(self, path):
    method get_fb (line 395) | def get_fb(self, calib_dir, cam=2):
    method load_velodyne_points (line 414) | def load_velodyne_points(self, file_name):
    method lin_interp (line 420) | def lin_interp(self, shape, xyd):
    method sub2ind (line 433) | def sub2ind(self, metrixSize, rowSub, colSub):
    method get_depth (line 441) | def get_depth(self, calib_dir, velo_file_name, im_shape, cam=2, interp...

FILE: models/modules.py
  class AdaptiveInstanceNorm2d (line 10) | class AdaptiveInstanceNorm2d(nn.Module):
    method __init__ (line 11) | def __init__(self, num_features, eps=1e-5, momentum=0.1):
    method forward (line 23) | def forward(self, x):
    method __repr__ (line 38) | def __repr__(self):
  class ResBlocks (line 41) | class ResBlocks(nn.Module):
    method __init__ (line 42) | def __init__(self, num_blocks, dim, norm='in', activation='relu', pad_...
    method forward (line 51) | def forward(self, x):
  class ResBlock (line 55) | class ResBlock(nn.Module):
    method __init__ (line 56) | def __init__(self, dim, norm='in', activation='relu', pad_type='zero'):
    method forward (line 84) | def forward(self, x):
  function get_nonlinearity_layer (line 96) | def get_nonlinearity_layer(activation_type='PReLU'):
  class Conv2dBlock (line 109) | class Conv2dBlock(nn.Module):
    method __init__ (line 111) | def __init__(self, input_dim ,output_dim, kernel_size, stride,
    method forward (line 164) | def forward(self, x):
  class LayerNorm (line 173) | class LayerNorm(nn.Module):
    method __init__ (line 174) | def __init__(self, num_features, eps=1e-5, affine=True):
    method forward (line 184) | def forward(self, x):
  class Struct_Encoder (line 204) | class Struct_Encoder(nn.Module):
    method __init__ (line 205) | def __init__(self, n_downsample, n_res, input_dim, dim, norm, activ, p...
    method forward (line 216) | def forward(self, x):
  class _UpProjection (line 224) | class _UpProjection(nn.Sequential):
    method __init__ (line 226) | def __init__(self, num_input_features, num_output_features):
    method forward (line 241) | def forward(self, x, size):
  class _EncoderBlock (line 253) | class _EncoderBlock(nn.Module):
    method __init__ (line 254) | def __init__(self, input_nc, middle_nc, output_nc, norm_layer=nn.Batch...
    method forward (line 268) | def forward(self, x):
  class _InceptionBlock (line 271) | class _InceptionBlock(nn.Module):
    method __init__ (line 272) | def __init__(self, input_nc, output_nc, norm_layer=nn.BatchNorm2d, non...
    method forward (line 292) | def forward(self, x):
  class GaussianNoiseLayer (line 306) | class GaussianNoiseLayer(nn.Module):
    method __init__ (line 307) | def __init__(self):
    method forward (line 310) | def forward(self, x):
  class _DecoderUpBlock (line 317) | class _DecoderUpBlock(nn.Module):
    method __init__ (line 318) | def __init__(self, input_nc, middle_nc, output_nc, norm_layer=nn.Batch...
    method forward (line 333) | def forward(self, x):
  class _OutputBlock (line 336) | class _OutputBlock(nn.Module):
    method __init__ (line 337) | def __init__(self, input_nc, output_nc, kernel_size=3, use_bias=False):
    method forward (line 347) | def forward(self, x):
  class Struct_Decoder (line 351) | class Struct_Decoder(nn.Module):
    method __init__ (line 352) | def __init__(self):
    method forward (line 366) | def forward(self, x):
  function get_norm_layer (line 373) | def get_norm_layer(norm_type='instance'):
  class Depth_Net (line 385) | class Depth_Net(nn.Module):
    method __init__ (line 386) | def __init__(self, input_nc=1, output_nc=1, ngf=64, layers=4, norm='ba...
    method forward (line 442) | def forward(self, input):

FILE: test.py
  function save_test (line 40) | def save_test(handle, result1_log):
  function kitti_metrics_preprocess (line 65) | def kitti_metrics_preprocess(pred, gt):
  function kitti_compute_metrics (line 97) | def kitti_compute_metrics(pred, gt):
  function nyu_compute_metrics (line 125) | def nyu_compute_metrics(pred, gt):
  function nyu_metrics_preprocess (line 160) | def nyu_metrics_preprocess(pred, gt):
  function main (line 190) | def main():

FILE: train.py
  function main (line 45) | def main():

FILE: train_loss.py
  function depth_loss (line 11) | def depth_loss(output, depth_gt):
  function gradient_x (line 29) | def gradient_x(img):
  function gradient_y (line 35) | def gradient_y(img):
  function struct_weighted_loss (line 44) | def struct_weighted_loss(struct_map, depth, train_iteration, hyper_w):

FILE: transform.py
  class RandomHorizontalFlip (line 10) | class RandomHorizontalFlip(object):
    method __init__ (line 11) | def __init__(self, prob=None):
    method __call__ (line 13) | def __call__(self, img):
  class RandomVerticalFlip (line 18) | class RandomVerticalFlip(object):
    method __init__ (line 19) | def __init__(self, img):
  class RandomImgAugment (line 25) | class RandomImgAugment(object):
    method __init__ (line 27) | def __init__(self, no_flip, no_rotation, no_augment, size=None, datase...
    method __call__ (line 34) | def __call__(self, inputs):

FILE: utils.py
  function makedir (line 11) | def makedir(directory):
  function colormap (line 16) | def colormap(image, cmap="jet"):
  function update_learning_rate (line 36) | def update_learning_rate(optimizers, scheduler):
  function get_scheduler (line 43) | def get_scheduler(optimizer, opt):
  function adjust_gt (line 57) | def adjust_gt(gt_depth, pred_depth):
  function init_weights (line 65) | def init_weights(net, init_type='normal', gain=0.02):
  class AverageMeter (line 88) | class AverageMeter(object):
    method __init__ (line 89) | def __init__(self):
    method reset (line 92) | def reset(self):
    method update (line 98) | def update(self, val, n=1):