code: def build_dataloader(
      dataset,
      template,
      tokenizer,
      tokenizer_wrapper_class,
      config,
      split,
  ):
      dataloader = PromptDataLoader(
          dataset=dataset,
          template=template,
          tokenizer=tokenizer,
          tokenizer_wrapper_class=tokenizer_wrapper_class,
          batch_size=config[split].batch_size,
          shuffle=config[split].shuffle_data,
          teacher_forcing=config[split].teacher_forcing
          if hasattr(config[split], "teacher_forcing")
          else None,
          predict_eos_token=True
          if config.task == "generation"
          else False,
          **config.dataloader,
      )
      return dataloader
  
file_path: OpenPrompt/experiments/cli.py
imports: import os
  import sys
  import argparse
  from openprompt.trainer import ClassificationRunner, GenerationRunner
  from openprompt.lm_bff_trainer import LMBFFClassificationRunner
  from openprompt.protoverb_trainer import ProtoVerbClassificationRunner
  from re import template
  from openprompt.pipeline_base import PromptForClassification, PromptForGeneration
  from openprompt.utils.reproduciblity import set_seed
  from openprompt import PromptDataLoader
  from openprompt.prompts import load_template, load_verbalizer, load_template_generator, load_verbalizer_generator
  from openprompt.data_utils import FewShotSampler
  from openprompt.utils.logging import config_experiment_dir, init_logger, logger
  from openprompt.config import get_config, save_config_to_yaml
  from openprompt.plms import load_plm_from_config
  from openprompt.data_utils import load_dataset
  from openprompt.utils.cuda import model_to_device
label_desc: Use image node_id 1 for calling a global function with example usage: build_dataloader(dataset, template, tokenizer, tokenizer_wrapper_class, config, split) and returns: dataloader