class_docstr: Dataset used for testing. Wraps a real dataset with a
  batchsize_per_replica, but allows us to delete samples on return
  to simulate errors (similar to what happens with Everstore)
class_docstr_tok: ["Dataset","used","for","testing",".","Wraps","a","real","dataset","with","a","batchsize_per_replica",",","but","allows","us","to","delete","samples","on","return","to","simulate","errors","(","similar","to","what","happens","with","Everstore",")"]
code: def __init__(self, dataset):
      self.rebatch_map = {}
      self.dataset = dataset
      self.batchsize_per_replica = dataset.batchsize_per_replica
  
imports: import os
  import unittest
  from functools import wraps
  import torch
  from classy_vision.hooks import ClassyHook
  from classy_vision.tasks import ClassyTask
  from classy_vision.trainer import ClassyTrainer
label_desc: Use image node_id 1 to create a new MockErrorDataset object  with example: obj = MockErrorDataset(dataset)