class_docstr: Constructs a ViLT processor which wraps a BERT tokenizer and ViLT image processor into a single processor.
  
  [`ViltProcessor`] offers all the functionalities of [`ViltImageProcessor`] and [`BertTokenizerFast`]. See the
  docstring of [`~ViltProcessor.__call__`] and [`~ViltProcessor.decode`] for more information.
  
  Args:
      image_processor (`ViltImageProcessor`, *optional*):
          An instance of [`ViltImageProcessor`]. The image processor is a required input.
      tokenizer (`BertTokenizerFast`, *optional*):
          An instance of ['BertTokenizerFast`]. The tokenizer is a required input.
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docstr: This method forwards all its arguments to BertTokenizerFast's [`~PreTrainedTokenizer.batch_decode`]. Please
  refer to the docstring of this method for more information.
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code: def batch_decode(self, *args, **kwargs):
      """
      This method forwards all its arguments to BertTokenizerFast's [`~PreTrainedTokenizer.batch_decode`]. Please
      refer to the docstring of this method for more information.
      """
      return self.tokenizer.batch_decode(*args, **kwargs)
  
file_path: transformers/src/transformers/models/vilt/processing_vilt.py
imports: import warnings
  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 3 for calling the ViltProcessor obj's underlying member method code with example usage: obj.batch_decode() and returns: self