code: def test_pad_tensor_to_size_1d():
      x = torch.randn((1, 3, 32))
  
      x_padded, unpad = pad_tensor_to_size(x, (48,))
  
      assert x_padded.size(2) == 48
      print(x_padded[unpad].size())
      assert (x_padded[unpad] == x).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 1 for calling a global function with example usage: test_pad_tensor_to_size_1d() without return types