class_docstr: At every iteration, this will return m samples per class. For example,
  if dataloader's batchsize is 100, and m = 5, then 20 classes with 5 samples
  each will be returned
code: def __len__(self):
      return self.list_size
  
file_path: pytorch-metric-learning/src/pytorch_metric_learning/samplers/m_per_class_sampler.py
imports: import torch
  from torch.utils.data.sampler import Sampler
  from ..utils import common_functions
label_desc: Use image node_id 2 for calling the MPerClassSampler obj's underlying member method code with example usage: obj.__len__() and returns: self