class_docstr: Constructs a FLAVA processor which wraps a FLAVA feature extractor and a FLAVA tokenizer into a single processor.
  
  [`FlavaProcessor`] offers all the functionalities of [`FlavaFeatureExtractor`] and [`BertTokenizerFast`]. See the
  [`~FlavaProcessor.__call__`] and [`~FlavaProcessor.decode`] for more information.
  
  Args:
      feature_extractor ([`FlavaFeatureExtractor`]): The feature extractor is a required input.
      tokenizer ([`BertTokenizerFast`]): The tokenizer is a required input.
class_docstr_tok: ["Constructs","a","FLAVA","processor","which","wraps","a","FLAVA","feature","extractor","and","a","FLAVA","tokenizer","into","a","single","processor",".","[","`","FlavaProcessor","`","]","offers","all","the","functionalities","of","[","`","FlavaFeatureExtractor","`","]","and","[","`","BertTokenizerFast","`","]",".","See","the","[","`","~FlavaProcessor.__call__","`","]","and","[","`","~FlavaProcessor.decode","`","]","for","more","information",".","Args",":","feature_extractor","(","[","`","FlavaFeatureExtractor","`","]",")",":","The","feature","extractor","is","a","required","input",".","tokenizer","(","[","`","BertTokenizerFast","`","]",")",":","The","tokenizer","is","a","required","input","."]
code: def __init__(self, feature_extractor, tokenizer):
      super().__init__(feature_extractor, tokenizer)
      self.current_processor = self.feature_extractor
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/flava/processing_flava.py
imports: from typing import List, Optional, Union
  from ...image_utils import ImageInput
  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 1 to create a new FlavaProcessor object from inherited base classes: ProcessorMixin with example: obj = FlavaProcessor(feature_extractor, tokenizer)