(self)

(self, val, n=1)

(self, chans: List[int], vol_size: int)

(vars)

(vars)

(self, chans: List[int], vol_size: int)

(self, chans: List[int], vol_size: int)

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

(self, val, n=1)

(D_est, D_gt, mask, thres)

(x, maxdisp)

( logger: SummaryWriter, mode_tag: str, scalar_dict: Dict[str, Union[float, List[float]]], glo

(filename)

(D_est, D_gt, mask)

(D_est, D_gt, mask)

()

(refimg_fea: torch.Tensor, targetimg_fea: torch.Tensor, maxdisp: int, num_groups: int)

(refimg_fea, targetimg_fea, maxdisp)

(img)

(filename: str)

(cost: torch.Tensor, disparity_samples: torch.Tensor, k: int)

(D_est_np, D_gt_np, abs_thres=3., rel_thres=0.05, dilate_radius=1)

(self, in_channels: int, out_channels: int, deconv: bool=False, is_3d: bool=False, concat: bool=True, keep_con

( optimizer: Adam, epoch: int, base_lr: float, lrepochs: str )

(vars)

(fea1: torch.Tensor, fea2: torch.Tensor, num_groups: int)

(fea1, fea2, num_groups)

(fea1, fea2, num_groups)

(self, filename)

(self, filename)

(self)

(disp_ests, disp_gts,img_masks)

(disp_ests, disp_gts, img_masks, cv_scale)

(fea1, fea2)

(self, x: Dict[str, Union[float, List[float]]])

(self, x)

(*vars)

(model)

(model)

(model)

()

(self, filename)

(self, filename)

(list_filename)

(self, list_filename: str)

(self, list_filename: str)

(dummy_input1, dummy_input2)

(self)

(self)

()

()

(sample, compute_metrics=True)

(sample)

(im_left, im_right)

(sample, compute_metrics=True)

()

(x: torch.Tensor)

(x: torch.Tensor, h: int, w: int)

()

()

(sample, compute_metrics=False)

(sample, compute_metrics=False)

(self)

(self)

(self)

(D_est, D_gt, mask, thres)

(self, input, target)

(self, inputs, target)

(self, inputs, target)

(self, inputs, target)

(self, index)

(self, index)