class_docstr: Engine class of Text Robustness.
  
  Support run entrance which automatically finish data loading,
  transformation/subpopulation/attack generation and robustness
  report generation.
  
  Also provide interfaces of each layer to practitioners.
docstr: Load data input, config file and FlintModel.
  
  :param dict|list|string data_input: json object or json/csv file
  :param string|textflint.Config config: json file or Config object
  :param str task: task name which will be helpful without config input.
  :param textflint.FlintModel model: model wrapper which implements
      FlintModel abstract methods, not a necessary input.
  :return: textflint.Dataset, textflint.Config, textflint.FlintModel
docstr_tok: ["Load","data","input",",","config","file","and","FlintModel",".",":","param","dict|list|string","data_input",":","json","object","or","json\/csv","file",":","param","string|textflint.Config","config",":","json","file","or","Config","object",":","param","str","task",":","task","name","which","will","be","helpful","without","config","input",".",":","param","textflint.FlintModel","model",":","model","wrapper","which","implements","FlintModel","abstract","methods",",","not","a","necessary","input",".",":","return",":","textflint.Dataset",",","textflint.Config",",","textflint.FlintModel"]
code: def load(self, data_input, config=None, task=None, model=None):
      r"""
      Load data input, config file and FlintModel.
  
      :param dict|list|string data_input: json object or json/csv file
      :param string|textflint.Config config: json file or Config object
      :param str task: task name which will be helpful without config input.
      :param textflint.FlintModel model: model wrapper which implements
          FlintModel abstract methods, not a necessary input.
      :return: textflint.Dataset, textflint.Config, textflint.FlintModel
  
      """
      config = auto_config(config=config, task=task)
  
      dataset = auto_dataset(data_input=data_input, task=config.task)
      # Prefer to use the model passed from parameter
      model = model if model else config.flint_model
      model = auto_flintmodel(model=model, task=config.task)
  
      return dataset, config, model
  
imports: import os
  from .common import logger
  from .adapter import *
label_desc: Use image node_id 2 for calling the Engine obj's underlying member method code with example usage: obj.load(data_input, config, task, model) and returns: dataset,  config,  model