docstr: Return a history filled with epoch and batch data.
docstr_tok: ["Return","a","history","filled","with","epoch","and","batch","data","."]
code: def history(self, history_cls):
      """Return a history filled with epoch and batch data."""
      h = history_cls()
      for num_epoch in range(self.test_epochs):
          h.new_epoch()
          h.record("duration", 1)
          h.record("total_loss", num_epoch + self.test_batches)
          if num_epoch == 2:
              h.record("extra", 42)
          for num_batch in range(self.test_batches):
              h.new_batch()
              h.record_batch("loss", num_epoch + num_batch)
              if (
                  num_batch % 2 == 0
                  and (num_epoch + 1) != self.test_epochs
              ):
                  h.record_batch("extra_batch", 23)
      return h
  
imports: import pickle
  import time
  import multiprocessing
  from functools import partial
  import numpy
  import pytest
  import torch
  from torch.distributed import TCPStore
  from sklearn.datasets import make_classification
label_desc: Use image node_id 2 for calling the TestHistory obj's underlying member method code with example usage: obj.history(history_cls) and returns: h