code: def compute_aspect_ratios(dataset, indices=None):
      if hasattr(dataset, "get_height_and_width"):
          return _compute_aspect_ratios_custom_dataset(dataset, indices)
  
      if isinstance(dataset, torchvision.datasets.CocoDetection):
          return _compute_aspect_ratios_coco_dataset(dataset, indices)
  
      if isinstance(dataset, torchvision.datasets.VOCDetection):
          return _compute_aspect_ratios_voc_dataset(dataset, indices)
  
      if isinstance(dataset, torch.utils.data.Subset):
          return _compute_aspect_ratios_subset_dataset(dataset, indices)
  
      # slow path
      return _compute_aspect_ratios_slow(dataset, indices)
  
imports: import bisect
  from collections import defaultdict
  import copy
  from itertools import repeat, chain
  import math
  import numpy
  import torch
  import torch.utils.data
  from torch.utils.data.sampler import BatchSampler, Sampler
  from torch.utils.model_zoo import tqdm
  import torchvision
  from PIL import Image
label_desc: Use image node_id 7 for calling a global function with example usage: compute_aspect_ratios(dataset, indices) and returns: _compute_aspect_ratios_slow, _compute_aspect_ratios_custom_dataset, _compute_aspect_ratios_coco_dataset, _compute_aspect_ratios_voc_dataset, _compute_aspect_ratios_subset_dataset