class_docstr: An updater for a chainer LM
  
  :param chainer.dataset.Iterator train_iter : The train iterator
  :param optimizer:
  :param schedulers:
  :param int device : The device id
  :param int accum_grad :
class_docstr_tok: ["An","updater","for","a","chainer","LM",":","param","chainer.dataset.Iterator","train_iter",":","The","train","iterator",":","param","optimizer",":",":","param","schedulers",":",":","param","int","device",":","The","device","id",":","param","int","accum_grad",":"]
code: def __init__(
      self, train_iter, optimizer, schedulers, device, accum_grad
  ):
      super(BPTTUpdater, self).__init__(
          train_iter, optimizer, device=device
      )
      self.scheduler = ChainerScheduler(schedulers, optimizer)
      self.accum_grad = accum_grad
  
imports: import copy
  import json
  import logging
  import chainer
  import chainer.functions
  import chainer.links
  import numpy
  from chainer import link, reporter, training
  from chainer.dataset import convert
  from chainer.functions.loss import softmax_cross_entropy
  from chainer.training import extensions
  import espnet.nets.chainer_backend.deterministic_embed_id
  from espnet.lm.lm_utils import MakeSymlinkToBestModel, ParallelSentenceIterator, compute_perplexity, count_tokens, read_tokens
  from espnet.nets.lm_interface import LMInterface
  from espnet.optimizer.factory import dynamic_import_optimizer
  from espnet.scheduler.chainer import ChainerScheduler
  from espnet.scheduler.scheduler import dynamic_import_scheduler
  from espnet.utils.deterministic_utils import set_deterministic_chainer
  from espnet.utils.training.evaluator import BaseEvaluator
  from espnet.utils.training.iterators import ShufflingEnabler
  from espnet.utils.training.tensorboard_logger import TensorboardLogger
  from espnet.utils.training.train_utils import check_early_stop, set_early_stop
label_desc: Use image node_id 1 to create a new BPTTUpdater object from inherited base classes: training.updaters with example: obj = BPTTUpdater(train_iter, optimizer, schedulers, device, accum_grad)