code: def test_pad_collation(self, t_type, collate_method, transform):
      if t_type == dict:
          dataset = CacheDataset(
              self.dict_data, transform, progress=False
          )
      else:
          dataset = _Dataset(
              self.list_data, self.list_labels, transform
          )
  
      # Default collation should raise an error
      loader_fail = DataLoader(dataset, batch_size=10)
      with self.assertRaises(RuntimeError):
          for _ in loader_fail:
              pass
  
      # Padded collation shouldn't
      loader = DataLoader(
          dataset, batch_size=10, collate_fn=collate_method
      )
      # check collation in forward direction
      for data in loader:
          if t_type == dict:
              shapes = []
              decollated_data = decollate_batch(data)
              for d in decollated_data:
                  output = PadListDataCollate.inverse(d)
                  shapes.append(output["image"].shape)
                  self.assertTrue(
                      len(output["image"].applied_operations),
                      len(dataset.transform.transforms),
                  )
              self.assertTrue(
                  len(set(shapes)) > 1
              )  # inverted shapes must be different because of random xforms
  
      if t_type == dict:
          batch_inverse = BatchInverseTransform(
              dataset.transform, loader
          )
          for data in loader:
              output = batch_inverse(data)
              self.assertTrue(output[0]["image"].shape, (1, 10, 9))
  
imports: from __future__ import annotations
  import random
  import unittest
  from functools import wraps
  import numpy
  import torch
  from parameterized import parameterized
  from monai.data import CacheDataset, DataLoader
  from monai.data.utils import decollate_batch, pad_list_data_collate
  from monai.transforms import BatchInverseTransform, Compose, PadListDataCollate, RandRotate, RandRotate90, RandRotate90d, RandRotated, RandSpatialCrop, RandSpatialCropd, RandZoom, RandZoomd, ToTensor
  from monai.utils import set_determinism
label_desc: Use image node_id 3 for calling the TestPadCollation obj's underlying member method code with example usage: obj.test_pad_collation(t_type, collate_method, transform) without return types