class_docstr: A Batch sampler to group mentions in batches with close number of pairs to be padded together
      
class_docstr_tok: ["A","Batch","sampler","to","group","mentions","in","batches","with","close","number","of","pairs","to","be","padded","together"]
code: def get_batch_info(self):
      return self.batches, self.batches_pairs
  
imports: import os
  import io
  import numpy
  import torch
  import torch.utils.data
  from torch.utils.data.sampler import Sampler
  from torch.utils.data import Dataset
  from neuralcoref.train.utils import encode_distance, BATCH_SIZE_PATH, SIZE_FP, SIZE_FP_COMPRESSED, SIZE_FS, SIZE_FS_COMPRESSED, SIZE_GENRE, SIZE_PAIR_IN, SIZE_SINGLE_IN
  from neuralcoref.train.conllparser import FEATURES_NAMES
label_desc: Use image node_id 2 for calling the NCBatchSampler obj's underlying member method code with example usage: obj.get_batch_info() and returns: self,  self