code: def _is_supported_batch_sampler(sampler: Sampler):
      return (
          isinstance(sampler, BatchSampler)
          or isinstance(sampler, UniformWithReplacementSampler)
          or isinstance(
              sampler, DistributedUniformWithReplacementSampler
          )
      )
  
file_path: opacus/opacus/data_loader.py
imports: import logging
  from functools import partial
  from typing import Any, List, Optional, Sequence, Tuple, Type, Union
  import torch
  from opacus.utils.uniform_sampler import DistributedUniformWithReplacementSampler, UniformWithReplacementSampler
  from torch.utils.data import BatchSampler, DataLoader, Dataset, IterableDataset, Sampler
  from torch.utils.data._utils.collate import default_collate
  from torch.utils.data.dataloader import _collate_fn_t
label_desc: Use image node_id 5 for calling a global function with example usage: _is_supported_batch_sampler(sampler) and returns: unknown