
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






class UpperCAmelCase   (						SCREAMING_SNAKE_CASE__   ):





   '''simple docstring'''
   __UpperCamelCase		:    str 				=    ['''image_processor''', '''tokenizer''']
   __UpperCamelCase		:    List[Any] 				=    '''BridgeTowerImageProcessor'''
   __UpperCamelCase		:    str 				=    ('''RobertaTokenizer''', '''RobertaTokenizerFast''')


   def __init__(					self     :							Tuple			,			lowerCAmelCase_     :							List[str]			,			lowerCAmelCase_     :							Any     ):

      """simple docstring"""
      super().__init__(lowerCAmelCase_			,			lowerCAmelCase_     )


   def __call__(					self     :							Union[str, Any]			,			lowerCAmelCase_     :							str			,			lowerCAmelCase_     :							Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None			,			lowerCAmelCase_     :							bool = True			,			lowerCAmelCase_     :							Union[bool, str, PaddingStrategy] = False			,			lowerCAmelCase_     :							Union[bool, str, TruncationStrategy] = None			,			lowerCAmelCase_     :							Optional[int] = None			,			lowerCAmelCase_     :							int = 0			,			lowerCAmelCase_     :							Optional[int] = None			,			lowerCAmelCase_     :							Optional[bool] = None			,			lowerCAmelCase_     :							Optional[bool] = None			,			lowerCAmelCase_     :							bool = False			,			lowerCAmelCase_     :							bool = False			,			lowerCAmelCase_     :							bool = False			,			lowerCAmelCase_     :							bool = False			,			lowerCAmelCase_     :							bool = True			,			lowerCAmelCase_     :							Optional[Union[str, TensorType]] = None			,			**lowerCAmelCase_     :							Any			,			):

      """simple docstring"""
      _A:  Dict					=       self.tokenizer(
          text=lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_			,			padding=lowerCAmelCase_			,			truncation=lowerCAmelCase_			,			max_length=lowerCAmelCase_			,			stride=lowerCAmelCase_			,			pad_to_multiple_of=lowerCAmelCase_			,			return_token_type_ids=lowerCAmelCase_			,			return_attention_mask=lowerCAmelCase_			,			return_overflowing_tokens=lowerCAmelCase_			,			return_special_tokens_mask=lowerCAmelCase_			,			return_offsets_mapping=lowerCAmelCase_			,			return_length=lowerCAmelCase_			,			verbose=lowerCAmelCase_			,			return_tensors=lowerCAmelCase_			,			**lowerCAmelCase_			,			)
      # add pixel_values + pixel_mask
      _A:  Dict					=       self.image_processor(
          lowerCAmelCase_			,			return_tensors=lowerCAmelCase_			,			do_normalize=lowerCAmelCase_			,			do_center_crop=lowerCAmelCase_			,			**lowerCAmelCase_     )
      encoding.update(lowerCAmelCase_     )

      return encoding


   def  __magic_name__				(					self     :							Optional[int]			,			*lowerCAmelCase_     :							Union[str, Any]			,			**lowerCAmelCase_     :							Optional[int]     ):

      """simple docstring"""
      return self.tokenizer.batch_decode(*lowerCAmelCase_			,			**lowerCAmelCase_     )


   def  __magic_name__				(					self     :							Tuple			,			*lowerCAmelCase_     :							Dict			,			**lowerCAmelCase_     :							Any     ):

      """simple docstring"""
      return self.tokenizer.decode(*lowerCAmelCase_			,			**lowerCAmelCase_     )


   @property
   def  __magic_name__				(					self     :							Optional[int]     ):

      """simple docstring"""
      _A:  Optional[Any]					=       self.tokenizer.model_input_names
      _A:  Dict					=       self.image_processor.model_input_names
      return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names     )     )





from .imports import is_tqdm_available


if is_tqdm_available():
   from tqdm.auto import tqdm as _tqdm

from ..state import PartialState






def   lowerCamelCase__							(					a = True		,		*a		,		**a      )      ->   Optional[Any]:
   if not is_tqdm_available():
      raise ImportError('''Accelerate\'s `tqdm` module requires `tqdm` to be installed. Please run `pip install tqdm`.'''      )
   _A:  Optional[Any]					=       False
   if main_process_only:
      _A:  Union[str, Any]					=       PartialState().local_process_index == 0
   return _tqdm(*a		,		**a		,		disable=a      )



