





'''simple docstring'''

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






class        UpperCAmelCase     (	__lowercase    ):
 __lowercase       		=    ["image_processor", "tokenizer"]
 __lowercase       		=    "ViltImageProcessor"
 __lowercase       		=    ("BertTokenizer", "BertTokenizerFast")
 def __init__(    self				:str						,	lowercase_				:Optional[int]=None						,	lowercase_				:Optional[int]=None						,	**lowercase_				:List[str]							)->							Any:
     A__    =      None
     if "feature_extractor" in kwargs:
         warnings.warn(
             "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
             " instead."						,	_a						,	)
         A__    =      kwargs.pop("feature_extractor"							)

     A__    =      image_processor if image_processor is not None else feature_extractor
     if image_processor is None:
         raise ValueError("You need to specify an `image_processor`."							)
     if tokenizer is None:
         raise ValueError("You need to specify a `tokenizer`."							)

     super().__init__(_a						,	_a							)
     A__    =      self.image_processor
 def __call__(    self				:int						,	lowercase_				:Tuple						,	lowercase_				:Tuple = None						,	lowercase_				:Optional[Any] = True						,	lowercase_				:Tuple = False						,	lowercase_				:Union[str, Any] = None						,	lowercase_				:List[Any] = None						,	lowercase_				:List[str] = 0						,	lowercase_				:int = None						,	lowercase_				:Dict = None						,	lowercase_				:Optional[Any] = None						,	lowercase_				:int = False						,	lowercase_				:Any = False						,	lowercase_				:Union[str, Any] = False						,	lowercase_				:Tuple = False						,	lowercase_				:List[str] = True						,	lowercase_				:List[str] = None						,	**lowercase_				:List[Any]						,	)->							BatchEncoding:
     A__    =      self.tokenizer(
         text=_a						,	add_special_tokens=_a						,	padding=_a						,	truncation=_a						,	max_length=_a						,	stride=_a						,	pad_to_multiple_of=_a						,	return_token_type_ids=_a						,	return_attention_mask=_a						,	return_overflowing_tokens=_a						,	return_special_tokens_mask=_a						,	return_offsets_mapping=_a						,	return_length=_a						,	verbose=_a						,	return_tensors=_a						,	**_a						,	)
     # add pixel_values + pixel_mask
     A__    =      self.image_processor(_a						,	return_tensors=_a							)
     encoding.update(_a							)

     return encoding
 def 					UpperCAmelCase_							(    self				:Union[str, Any]						,	*lowercase_				:List[Any]						,	**lowercase_				:Any							)->							Optional[Any]:
     return self.tokenizer.batch_decode(*_a						,	**_a							)
 def 					UpperCAmelCase_							(    self				:List[Any]						,	*lowercase_				:int						,	**lowercase_				:str							)->							str:
     return self.tokenizer.decode(*_a						,	**_a							)
 @property
 def 					UpperCAmelCase_							(    self				:List[Any]							)->							Optional[int]:
     A__    =      self.tokenizer.model_input_names
     A__    =      self.image_processor.model_input_names
     return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)
 @property
 def 					UpperCAmelCase_							(    self				:str							)->							Optional[Any]:
     warnings.warn(
         "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."						,	_a						,	)
     return self.image_processor_class



 @property
 def 					UpperCAmelCase_							(    self				:List[str]							)->							Any:
     warnings.warn(
         "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."						,	_a						,	)
     return self.image_processor










'''simple docstring'''

from .imports import is_tqdm_available


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

from ..state import PartialState





def 						UpperCamelCase    (							_lowerCamelCase : bool = True						,	*_lowerCamelCase : Optional[int]						,	**_lowerCamelCase : Optional[Any]	):
    if not is_tqdm_available():
        raise ImportError("Accelerate's `tqdm` module requires `tqdm` to be installed. Please run `pip install tqdm`."	)
    A__    =      False
    if main_process_only:
        A__    =      PartialState().local_process_index == 0
    return _tqdm(*_lowerCamelCase						,	**_lowerCamelCase						,	disable=_lowerCamelCase	)



