code: def _seed_dataset_transform(transform, seed=None):
      if isinstance(transform, Compose):
          for subtransform in transform.transforms:
              _seed_dataset_transform(subtransform, seed=seed)
      elif hasattr(transform, "seed"):
          transform.seed(seed=seed)
  
imports: import sys
  import numpy
  import warnings
  from copy import deepcopy
  from itertools import combinations
  from ordered_set import OrderedSet
  from torchvision.transforms import Compose
  from torchmeta.utils.data.task import ConcatTask
  from torchmeta.transforms import FixedCategory, Categorical, DefaultTargetTransform
  from torchmeta.transforms.utils import wrap_transform
label_desc: Use image node_id 1 for calling a global function with example usage: _seed_dataset_transform(transform, seed) without return types