(self, index)

(self, index)

(self, index)

(self, index)

(self, index)

(self)

(self)

(self)

(self)

( self, left, right, left_disp, training, imgloader=img_loader

( self, left, right, left_disp, training, imgloader=img_loader

( self, left, right, disp_gt, occ_mask, training, imgl

( self, datapath_12: str, datapath_15: str, list_filename: str, training: bool )

(self, datapath: str, list_filename: str, training: bool)

( self, left, right, left_disp, training, imgloader=img_loader

(self, left, right, imgloader=img_loader)

(self, co_transforms)

(self, size, order=2)

(self, size)

(self, angle, px, diff_angle=0, order=2, reshape=False)

(self, in_channels: int, out_channels: int, deconv: bool=False, is_3d: bool=False, bn: bool=True, gelu: bool=T

(self, inplanes, planes, stride, downsample, pad, dilation)

(self)

(self, backbone: str)

(self, in_channels: int, add_channel: int)

(self, C: int, cf1: int, cf2: int)

(self)

(self)

(self)

(self, maxdisp: int, gwc: bool=False, norm_correlation: bool=True, backbone: str="efficientnet_b2", cv_scale

(self)

(self, backbone: str)

(self, in_channels: int, add_channel: int)

(self, C: int, cf1: int, cf2: int)

(self)

(self)

(self)

(self, C: int, fc: int)

(self, C)

(self, maxdisp: int, gwc: bool=False, norm_correlation: bool=True, backbone: str="efficientnet_b2", cv_scale

(self)

(self, backbone: str)

(self, in_channels: int, add_channel: int)

(self, C: int, cf1: int, cf2: int)

(self)

(self)

(self)

(self, maxdisp: int, gwc: bool=False, norm_correlation: bool=True, backbone: str="efficientnet_b2", cv_scale

(self, dim, mlp_ratio=4)

(self, dim: int, mlp_ratio: int=2)

(self, normalized_shape: int)

(self, normalized_shape)

(self, dim: int, LayerNorm_type: str='BiasFree')

(self, dim: int, kernel_size: int, mlp_ratio: int=2)

(self, n_feats, kernel_size, n_blocks, mlp_ratio, upscaling_factor)

(self)

(self)

(self)

(self)

(self)

(self)

(self)

(refimg_fea, targetimg_fea, maxdisp)

(ref: torch.Tensor, tgt: torch.Tensor, maxdisp: int,

(refimg_fea, targetimg_fea, maxdisp, num_groups)

(refimg_fea, targetimg_fea, maxdisp, num_groups)

(metric_func: Callable)

(depth_low, up_weights)

(model)

(model)

(model)

(filepath)

(path)

(path)

(path)

(path)

(path)

(filepath: str)

(self, x: torch.Tensor)

(self, x)

(self, x: torch.Tensor, rem: torch.Tensor)

(self, x: torch.Tensor)

(self, featL: List[ torch.Tensor], featR: Optional[List[ torch.Tensor]]=None)

(self, x: torch.Tensor)

(self, disp: torch.Tensor, left_f1x: torch.Tensor, left_f2x: torch.Tensor)

(self, left_f1x: torch.Tensor, left_f2x: torch.Tensor, left_f4x: torch.Tensor, init_disp: torch.Tensor)

(self, left_f2x, left_f4x, left_f8x, stem_f2, init_disp)

(self, left_f1x: torch.Tensor, left_f2x: torch.Tensor, left_f4x: torch.Tensor, left_f8x: torch.Tensor, init_di

(self, left: torch.Tensor, right: torch.Tensor, train_status: bool)

(self, x: torch.Tensor)

(self, featL: List[ torch.Tensor], featR: Optional[List[ torch.Tensor]]=None)

(self, x: torch.Tensor)

(self, disp: torch.Tensor, left_f1x: torch.Tensor, left_f2x: torch.Tensor)

(self, left_f1x: torch.Tensor, left_f2x: torch.Tensor, left_f4x: torch.Tensor, init_disp: torch.Tensor)

(self, left_f2x, left_f4x, left_f8x, stem_f2, init_disp)

(self, left_f1x: torch.Tensor, left_f2x: torch.Tensor, left_f4x: torch.Tensor, left_f8x: torch.Tensor, init_di

(self, left_f1x: torch.Tensor, init_conf: torch.Tensor)

(self, cost, disp, imag, left_f1x, left_f2x, device)