class_docstr: Wraps another sampler to yield a mini-batch of indices.
  It enforces that the batch only contain elements from the same group.
  It also tries to provide mini-batches which follows an ordering which is
  as close as possible to the ordering from the original sampler.
code: def __len__(self):
      raise NotImplementedError(
          "len() of GroupedBatchSampler is not well-defined."
      )
  
imports: import numpy
  from torch.utils.data.sampler import BatchSampler, Sampler
label_desc: Use image node_id 3 for calling the GroupedBatchSampler obj's underlying member method code with example usage: obj.__len__() without return types