code: def fill_tail_dims(y: torch.Tensor, y_like: torch.Tensor):
      """Fill in missing trailing dimensions for y according to y_like."""
      return y[(...,) + (None,) * (y_like.dim() - y.dim())]
  
imports: import abc
  import logging
  import math
  import os
  import fire
  import torch
  import torchdiffeq
  import torchvision
  import tqdm
  from torch import nn, optim
  from torch.utils import data
  import torchsde
  from .None import unet
label_desc: Use image node_id 1 for calling a global function with example usage: fill_tail_dims(y, y_like) and returns: y