code: def test_pad_unpad(shape, padding):
      x = torch.randn(shape)
  
      x_padded, pad_params = pad_image_tensor(x, pad_size=padding)
      assert x_padded.size(2) % padding == 0
      assert x_padded.size(3) % padding == 0
  
      y = unpad_image_tensor(x_padded, pad_params)
      assert (x == y).all()
  
imports: import numpy
  import pytest
  import torch
  from pytorch_toolbelt.inference.functional import unpad_xyxy_bboxes, pad_image_tensor, unpad_image_tensor, pad_tensor_to_size
  from pytorch_toolbelt.modules.encoders import make_n_channel_input
  from pytorch_toolbelt.utils import match_bboxes, match_bboxes_hungarian, get_collate_for_dataset
  from torch import nn
  from torch.utils.data import ConcatDataset
  from functools import partial
label_desc: Use image node_id 6 for calling a global function with example usage: test_pad_unpad(shape, padding) without return types