SYMBOL INDEX (226 symbols across 24 files)

FILE: dataloader/dataloader.py
  class StereoDataset (line 12) | class StereoDataset(Dataset):
    method __init__ (line 13) | def __init__(self, data_dir,
    method __getitem__ (line 99) | def __getitem__(self, index):
    method __len__ (line 121) | def __len__(self):

FILE: dataloader/transforms.py
  class Compose (line 9) | class Compose(object):
    method __init__ (line 10) | def __init__(self, transforms):
    method __call__ (line 13) | def __call__(self, sample):
  class ToTensor (line 19) | class ToTensor(object):
    method __call__ (line 22) | def __call__(self, sample):
  class Normalize (line 40) | class Normalize(object):
    method __init__ (line 43) | def __init__(self, mean, std):
    method __call__ (line 47) | def __call__(self, sample):
  class RandomCrop (line 59) | class RandomCrop(object):
    method __init__ (line 60) | def __init__(self, img_height, img_width, validate=False):
    method __call__ (line 65) | def __call__(self, sample):
    method crop_img (line 120) | def crop_img(self, img):
  class RandomVerticalFlip (line 125) | class RandomVerticalFlip(object):
    method __call__ (line 128) | def __call__(self, sample):
  class ToPILImage (line 141) | class ToPILImage(object):
    method __call__ (line 143) | def __call__(self, sample):
  class ToNumpyArray (line 150) | class ToNumpyArray(object):
    method __call__ (line 152) | def __call__(self, sample):
  class RandomContrast (line 160) | class RandomContrast(object):
    method __call__ (line 163) | def __call__(self, sample):
  class RandomGamma (line 173) | class RandomGamma(object):
    method __call__ (line 175) | def __call__(self, sample):
  class RandomBrightness (line 185) | class RandomBrightness(object):
    method __call__ (line 187) | def __call__(self, sample):
  class RandomHue (line 197) | class RandomHue(object):
    method __call__ (line 199) | def __call__(self, sample):
  class RandomSaturation (line 209) | class RandomSaturation(object):
    method __call__ (line 211) | def __call__(self, sample):
  class RandomColor (line 221) | class RandomColor(object):
    method __call__ (line 223) | def __call__(self, sample):

FILE: filenames/generate_filenames.py
  function gen_kitti_2015 (line 5) | def gen_kitti_2015():

FILE: inference.py
  function main (line 80) | def main():

FILE: metric.py
  function epe_metric (line 7) | def epe_metric(d_est, d_gt, mask, use_np=False):
  function d1_metric (line 17) | def d1_metric(d_est, d_gt, mask, use_np=False):
  function thres_metric (line 33) | def thres_metric(d_est, d_gt, mask, thres, use_np=False):

FILE: model.py
  class Model (line 12) | class Model(object):
    method __init__ (line 13) | def __init__(self, args, logger, optimizer, aanet, device, start_iter=...
    method train (line 29) | def train(self, train_loader):
    method validate (line 198) | def validate(self, val_loader):

FILE: nets/aanet.py
  class AANet (line 14) | class AANet(nn.Module):
    method __init__ (line 15) | def __init__(self, max_disp,
    method feature_extraction (line 133) | def feature_extraction(self, img):
    method cost_volume_construction (line 139) | def cost_volume_construction(self, left_feature, right_feature):
    method disparity_computation (line 149) | def disparity_computation(self, aggregation):
    method disparity_refinement (line 162) | def disparity_refinement(self, left_img, right_img, disparity):
    method forward (line 206) | def forward(self, left_img, right_img):

FILE: nets/aggregation.py
  function conv3d (line 8) | def conv3d(in_channels, out_channels, kernel_size=3, stride=1, dilation=...
  function convbn_3d (line 17) | def convbn_3d(in_planes, out_planes, kernel_size, stride, pad):
  function conv2d (line 23) | def conv2d(in_channels, out_channels, kernel_size=3, stride=1, dilation=...
  function conv1x1 (line 31) | def conv1x1(in_planes, out_planes):
  function conv3x3 (line 40) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1, with_...
  function conv3x3_3d (line 52) | def conv3x3_3d(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function trans_conv3x3_3d (line 60) | def trans_conv3x3_3d(in_channels, out_channels, stride=1, groups=1, dila...
  class StereoNetAggregation (line 70) | class StereoNetAggregation(nn.Module):
    method __init__ (line 71) | def __init__(self, in_channels=32):
    method forward (line 84) | def forward(self, cost_volume):
  class PSMNetBasicAggregation (line 94) | class PSMNetBasicAggregation(nn.Module):
    method __init__ (line 97) | def __init__(self, max_disp):
    method forward (line 131) | def forward(self, cost):
  class PSMNetHourglass (line 147) | class PSMNetHourglass(nn.Module):
    method __init__ (line 148) | def __init__(self, inplanes):
    method forward (line 172) | def forward(self, x, presqu, postsqu):
  class PSMNetHGAggregation (line 194) | class PSMNetHGAggregation(nn.Module):
    method __init__ (line 197) | def __init__(self, max_disp):
    method forward (line 228) | def forward(self, cost):
  class GCNetAggregation (line 260) | class GCNetAggregation(nn.Module):
    method __init__ (line 261) | def __init__(self):
    method forward (line 291) | def forward(self, cost_volume):
  class AdaptiveAggregationModule (line 313) | class AdaptiveAggregationModule(nn.Module):
    method __init__ (line 314) | def __init__(self, num_scales, num_output_branches, max_disp,
    method forward (line 375) | def forward(self, x):
  class AdaptiveAggregation (line 406) | class AdaptiveAggregation(nn.Module):
    method __init__ (line 407) | def __init__(self, max_disp, num_scales=3, num_fusions=6,
    method forward (line 451) | def forward(self, cost_volume):

FILE: nets/cost.py
  class CostVolume (line 5) | class CostVolume(nn.Module):
    method __init__ (line 6) | def __init__(self, max_disp, feature_similarity='correlation'):
    method forward (line 19) | def forward(self, left_feature, right_feature):
  class CostVolumePyramid (line 58) | class CostVolumePyramid(nn.Module):
    method __init__ (line 59) | def __init__(self, max_disp, feature_similarity='correlation'):
    method forward (line 64) | def forward(self, left_feature_pyramid, right_feature_pyramid):

FILE: nets/deform.py
  function conv3x3 (line 6) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 12) | def conv1x1(in_planes, out_planes, stride=1):
  class DeformConv2d (line 17) | class DeformConv2d(nn.Module):
    method __init__ (line 20) | def __init__(self, in_channels,
    method forward (line 71) | def forward(self, x):
  class DeformBottleneck (line 93) | class DeformBottleneck(nn.Module):
    method __init__ (line 97) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 114) | def forward(self, x):
  class SimpleBottleneck (line 137) | class SimpleBottleneck(nn.Module):
    method __init__ (line 140) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 157) | def forward(self, x):
  class DeformSimpleBottleneck (line 180) | class DeformSimpleBottleneck(nn.Module):
    method __init__ (line 183) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 209) | def forward(self, x):

FILE: nets/deform_conv/deform_conv.py
  class DeformConvFunction (line 12) | class DeformConvFunction(Function):
    method forward (line 15) | def forward(ctx,
    method backward (line 60) | def backward(ctx, grad_output):
    method _output_size (line 97) | def _output_size(input, weight, padding, dilation, stride):
  class ModulatedDeformConvFunction (line 113) | class ModulatedDeformConvFunction(Function):
    method forward (line 116) | def forward(ctx,
    method backward (line 152) | def backward(ctx, grad_output):
    method _infer_shape (line 174) | def _infer_shape(ctx, input, weight):
  class DeformConv (line 190) | class DeformConv(nn.Module):
    method __init__ (line 192) | def __init__(self,
    method reset_parameters (line 230) | def reset_parameters(self):
    method forward (line 237) | def forward(self, x, offset):
  class DeformConvPack (line 242) | class DeformConvPack(DeformConv):
    method __init__ (line 260) | def __init__(self, *args, **kwargs):
    method init_offset (line 273) | def init_offset(self):
    method forward (line 277) | def forward(self, x):
    method _load_from_state_dict (line 282) | def _load_from_state_dict(self, state_dict, prefix, local_metadata, st...
  class ModulatedDeformConv (line 304) | class ModulatedDeformConv(nn.Module):
    method __init__ (line 306) | def __init__(self,
    method reset_parameters (line 339) | def reset_parameters(self):
    method forward (line 348) | def forward(self, x, offset, mask):
  class ModulatedDeformConvPack (line 354) | class ModulatedDeformConvPack(ModulatedDeformConv):
    method __init__ (line 372) | def __init__(self, *args, **kwargs):
    method init_offset (line 385) | def init_offset(self):
    method forward (line 389) | def forward(self, x):
    method _load_from_state_dict (line 398) | def _load_from_state_dict(self, state_dict, prefix, local_metadata, st...

FILE: nets/deform_conv/src/deform_conv_cuda.cpp
  function shape_check (line 62) | void shape_check(at::Tensor input, at::Tensor offset, at::Tensor *gradOu...
  function deform_conv_forward_cuda (line 152) | int deform_conv_forward_cuda(at::Tensor input, at::Tensor weight,
  function deform_conv_backward_input_cuda (line 262) | int deform_conv_backward_input_cuda(at::Tensor input, at::Tensor offset,
  function deform_conv_backward_parameters_cuda (line 376) | int deform_conv_backward_parameters_cuda(
  function modulated_deform_conv_cuda_forward (line 490) | void modulated_deform_conv_cuda_forward(
  function modulated_deform_conv_cuda_backward (line 571) | void modulated_deform_conv_cuda_backward(
  function PYBIND11_MODULE (line 687) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: nets/estimation.py
  class DisparityEstimation (line 6) | class DisparityEstimation(nn.Module):
    method __init__ (line 7) | def __init__(self, max_disp, match_similarity=True):
    method forward (line 13) | def forward(self, cost_volume):

FILE: nets/feature.py
  function conv1x1 (line 8) | def conv1x1(in_channels, out_channels):
  function conv3x3 (line 15) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1, with_...
  function conv5x5 (line 27) | def conv5x5(in_channels, out_channels, stride=2,
  class BasicBlock (line 42) | class BasicBlock(nn.Module):
    method __init__ (line 45) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 60) | def forward(self, x):
  class StereoNetFeature (line 79) | class StereoNetFeature(nn.Module):
    method __init__ (line 80) | def __init__(self, num_downsample=3):
    method forward (line 108) | def forward(self, img):
  function convbn (line 117) | def convbn(in_planes, out_planes, kernel_size, stride, pad, dilation):
  class PSMNetBasicBlock (line 123) | class PSMNetBasicBlock(nn.Module):
    method __init__ (line 126) | def __init__(self, inplanes, planes, stride, downsample, pad, dilation):
    method forward (line 137) | def forward(self, x):
  class FeaturePyrmaid (line 149) | class FeaturePyrmaid(nn.Module):
    method __init__ (line 150) | def __init__(self, in_channel=32):
    method forward (line 173) | def forward(self, x):
  class FeaturePyramidNetwork (line 181) | class FeaturePyramidNetwork(nn.Module):
    method __init__ (line 182) | def __init__(self, in_channels, out_channels=128,
    method forward (line 211) | def forward(self, inputs):
  class PSMNetFeature (line 233) | class PSMNetFeature(nn.Module):
    method __init__ (line 234) | def __init__(self):
    method _make_layer (line 270) | def _make_layer(self, block, planes, blocks, stride, pad, dilation):
    method forward (line 286) | def forward(self, x):
  class BasicConv (line 313) | class BasicConv(nn.Module):
    method __init__ (line 315) | def __init__(self, in_channels, out_channels, deconv=False, is_3d=Fals...
    method forward (line 332) | def forward(self, x):
  class Conv2x (line 341) | class Conv2x(nn.Module):
    method __init__ (line 343) | def __init__(self, in_channels, out_channels, deconv=False, is_3d=Fals...
    method forward (line 367) | def forward(self, x, rem):
  class GANetFeature (line 378) | class GANetFeature(nn.Module):
    method __init__ (line 381) | def __init__(self, feature_mdconv=False):
    method forward (line 425) | def forward(self, x):
  class GCNetFeature (line 462) | class GCNetFeature(nn.Module):
    method __init__ (line 463) | def __init__(self):
    method _make_layer (line 471) | def _make_layer(self, block, planes, blocks, stride, pad, dilation):
    method forward (line 487) | def forward(self, x):

FILE: nets/refinement.py
  function conv2d (line 10) | def conv2d(in_channels, out_channels, kernel_size=3, stride=1, dilation=...
  class StereoNetRefinement (line 18) | class StereoNetRefinement(nn.Module):
    method __init__ (line 19) | def __init__(self):
    method forward (line 35) | def forward(self, low_disp, left_img, right_img=None):
  class StereoDRNetRefinement (line 60) | class StereoDRNetRefinement(nn.Module):
    method __init__ (line 61) | def __init__(self):
    method forward (line 80) | def forward(self, low_disp, left_img, right_img):
  class HourglassRefinement (line 109) | class HourglassRefinement(nn.Module):
    method __init__ (line 112) | def __init__(self):
    method forward (line 144) | def forward(self, low_disp, left_img, right_img):

FILE: nets/resnet.py
  function conv3x3 (line 6) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 12) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 17) | class BasicBlock(nn.Module):
    method __init__ (line 21) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 39) | def forward(self, x):
  class Bottleneck (line 58) | class Bottleneck(nn.Module):
    method __init__ (line 62) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 79) | def forward(self, x):
  class AANetFeature (line 102) | class AANetFeature(nn.Module):
    method __init__ (line 103) | def __init__(self, in_channels=32,
    method _make_layer (line 153) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
    method forward (line 177) | def forward(self, x):

FILE: nets/warp.py
  function normalize_coords (line 5) | def normalize_coords(grid):
  function meshgrid (line 18) | def meshgrid(img, homogeneous=False):
  function disp_warp (line 41) | def disp_warp(img, disp, padding_mode='border'):

FILE: predict.py
  function main (line 72) | def main():

FILE: thop/count_hooks.py
  function count_convNd (line 9) | def count_convNd(m, x, y):
  function count_dconv2d (line 21) | def count_dconv2d(m, x, y):
  function count_mdconv2d (line 41) | def count_mdconv2d(m, x, y):
  function count_conv2d (line 65) | def count_conv2d(m, x, y):
  function count_convtranspose2d (line 88) | def count_convtranspose2d(m, x, y):

FILE: thop/profile.py
  function profile (line 23) | def profile(model, inputs, custom_ops={}, verbose=True):
  function clever_format (line 84) | def clever_format(num):

FILE: train.py
  function main (line 99) | def main():

FILE: utils/file_io.py
  function read_img (line 11) | def read_img(filename):
  function read_disp (line 17) | def read_disp(filename, subset=False):
  function _read_pfm (line 34) | def _read_pfm(file):
  function write_pfm (line 72) | def write_pfm(file, image, scale=1):
  function _read_kitti_disp (line 104) | def _read_kitti_disp(filename):

FILE: utils/utils.py
  function read_text_lines (line 9) | def read_text_lines(filepath):
  function check_path (line 16) | def check_path(path):
  function save_command (line 21) | def save_command(save_path, filename='command_train.txt'):
  function save_args (line 29) | def save_args(args, filename='args.json'):
  function int_list (line 38) | def int_list(s):
  function save_checkpoint (line 43) | def save_checkpoint(save_path, optimizer, aanet, epoch, num_iter,
  function load_pretrained_net (line 73) | def load_pretrained_net(net, pretrained_path, return_epoch_iter=False, r...
  function resume_latest_ckpt (line 103) | def resume_latest_ckpt(checkpoint_dir, net, net_name):
  function fix_net_parameters (line 116) | def fix_net_parameters(net):
  function count_parameters (line 121) | def count_parameters(model):
  function filter_specific_params (line 126) | def filter_specific_params(kv):
  function filter_base_params (line 134) | def filter_base_params(kv):
  function get_logger (line 142) | def get_logger():

FILE: utils/visualization.py
  function gen_error_colormap (line 9) | def gen_error_colormap():
  function disp_error_img (line 25) | def disp_error_img(D_est_tensor, D_gt_tensor, abs_thres=3., rel_thres=0....
  function save_images (line 52) | def save_images(logger, mode_tag, images_dict, global_step):
  function tensor2numpy (line 70) | def tensor2numpy(var_dict):