class_docstr: Simply forward the list of input data.
  
  This is particularly useful when the Dataset contains textual data
  and in conjunction with the `Tuple` collate function.
class_docstr_tok: ["Simply","forward","the","list","of","input","data",".","This","is","particularly","useful","when","the","Dataset","contains","textual","data","and","in","conjunction","with","the","`","Tuple","`","collate","function","."]
docstr: Parameters
  ----------
      data (list): The list of samples
  
  Returns
  -------
      ret (list): The input list
docstr_tok: ["Parameters","--","--","--","--","--","data","(","list",")",":","The","list","of","samples","Returns","--","--","--","-","ret","(","list",")",":","The","input","list"]
code: def __call__(self, data):
      """
      Parameters
      ----------
          data (list): The list of samples
  
      Returns
      -------
          ret (list): The input list
      """
      return list(data)
  
file_path: autogluon/multimodal/src/autogluon/multimodal/data/collator.py
imports: import math
  import warnings
  import numpy
  import torch
label_desc: Use image node_id 1 for calling the ListCollator obj's underlying member method code with example usage: obj.__call__(data) and returns: list