class_docstr: Pads images such that dimensions are divisible by 8
class_docstr_tok: ["Pads","images","such","that","dimensions","are","divisible","by","8"]
code: def __init__(self, dims, mode="sintel"):
      self.ht, self.wd = dims[-2:]
      pad_ht = (((self.ht // 8) + 1) * 8 - self.ht) % 8
      pad_wd = (((self.wd // 8) + 1) * 8 - self.wd) % 8
      if mode == "sintel":
          self._pad = [
              pad_wd // 2,
              pad_wd - pad_wd // 2,
              pad_ht // 2,
              pad_ht - pad_ht // 2,
          ]
      else:
          self._pad = [pad_wd // 2, pad_wd - pad_wd // 2, 0, pad_ht]
  
imports: import datetime
  import os
  import time
  from collections import defaultdict, deque
  import torch
  import torch.distributed
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new InputPadder object  with example: obj = InputPadder(dims, mode)