class_docstr: Constructs a Bros processor which wraps a BERT tokenizer.
  
  [`BrosProcessor`] offers all the functionalities of [`BertTokenizerFast`]. See the docstring of
  [`~BrosProcessor.__call__`] and [`~BrosProcessor.decode`] for more information.
  
  Args:
      tokenizer (`BertTokenizerFast`, *optional*):
          An instance of ['BertTokenizerFast`]. The tokenizer is a required input.
class_docstr_tok: ["Constructs","a","Bros","processor","which","wraps","a","BERT","tokenizer",".","[","`","BrosProcessor","`","]","offers","all","the","functionalities","of","[","`","BertTokenizerFast","`","]",".","See","the","docstring","of","[","`","~BrosProcessor.__call__","`","]","and","[","`","~BrosProcessor.decode","`","]","for","more","information",".","Args",":","tokenizer","(","`","BertTokenizerFast","`",",","*","optional","*",")",":","An","instance","of","[","'BertTokenizerFast","`","]",".","The","tokenizer","is","a","required","input","."]
code: def model_input_names(self):
      tokenizer_input_names = self.tokenizer.model_input_names
      return list(dict.fromkeys(tokenizer_input_names))
  
file_path: transformers/src/transformers/models/bros/processing_bros.py
imports: from typing import List, Optional, Union
  from ...processing_utils import ProcessorMixin
  from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
  from ...utils import TensorType
label_desc: Use image node_id 5 for calling the BrosProcessor obj's underlying member method code with example usage: obj.model_input_names() and returns: list