code: def sequential_train_loader(c: NLPAutoRegressionConfigs):
      """
      ### Sequential training data loader
      """
      return SequentialDataLoader(
          text=c.text.train,
          dataset=c.text,
          batch_size=c.batch_size,
          seq_len=c.seq_len,
      )
  
imports: from typing import Callable
  import torch
  import torch.nn
  from torch.utils.data import DataLoader, RandomSampler
  from labml import lab, monit, logger, tracker
  from labml.configs import option
  from labml.logger import Text
  from labml_helpers.datasets.text import TextDataset, SequentialDataLoader, SequentialUnBatchedDataset, TextFileDataset
  from labml_helpers.device import DeviceConfigs
  from labml_helpers.metrics.accuracy import Accuracy
  from labml_helpers.module import Module
  from labml_helpers.train_valid import TrainValidConfigs, hook_model_outputs, BatchIndex
  from labml_nn.optimizers.configs import OptimizerConfigs
label_desc: Use image node_id 7 for calling a global function with example usage: sequential_train_loader(c) and returns: SequentialDataLoader