

"""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 		_A       (			__a					):
      __a								=	['image_processor', 'tokenizer']
      __a								=	'ViltImageProcessor'
      __a								=	('BertTokenizer', 'BertTokenizerFast')





      def __init__(  self    ,						SCREAMING_SNAKE_CASE__=None    ,						SCREAMING_SNAKE_CASE__=None    ,						**SCREAMING_SNAKE_CASE__		)   ->					Optional[Any]:
         lowerCamelCase__						=			None
         if "feature_extractor" in kwargs:
            warnings.warn(
                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
                " instead."    ,						SCREAMING_SNAKE_CASE__    ,						)
            lowerCamelCase__						=			kwargs.pop("feature_extractor"		)

         lowerCamelCase__						=			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__(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			self.image_processor





      def __call__(  self    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = True    ,						SCREAMING_SNAKE_CASE__ = False    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = 0    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = None    ,						SCREAMING_SNAKE_CASE__ = False    ,						SCREAMING_SNAKE_CASE__ = False    ,						SCREAMING_SNAKE_CASE__ = False    ,						SCREAMING_SNAKE_CASE__ = False    ,						SCREAMING_SNAKE_CASE__ = True    ,						SCREAMING_SNAKE_CASE__ = None    ,						**SCREAMING_SNAKE_CASE__    ,						)   ->					BatchEncoding:
         lowerCamelCase__						=			self.tokenizer(
             text=SCREAMING_SNAKE_CASE__    ,						add_special_tokens=SCREAMING_SNAKE_CASE__    ,						padding=SCREAMING_SNAKE_CASE__    ,						truncation=SCREAMING_SNAKE_CASE__    ,						max_length=SCREAMING_SNAKE_CASE__    ,						stride=SCREAMING_SNAKE_CASE__    ,						pad_to_multiple_of=SCREAMING_SNAKE_CASE__    ,						return_token_type_ids=SCREAMING_SNAKE_CASE__    ,						return_attention_mask=SCREAMING_SNAKE_CASE__    ,						return_overflowing_tokens=SCREAMING_SNAKE_CASE__    ,						return_special_tokens_mask=SCREAMING_SNAKE_CASE__    ,						return_offsets_mapping=SCREAMING_SNAKE_CASE__    ,						return_length=SCREAMING_SNAKE_CASE__    ,						verbose=SCREAMING_SNAKE_CASE__    ,						return_tensors=SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__    ,						)
         # add pixel_values + pixel_mask
         lowerCamelCase__						=			self.image_processor(SCREAMING_SNAKE_CASE__    ,						return_tensors=SCREAMING_SNAKE_CASE__		)
         encoding.update(SCREAMING_SNAKE_CASE__		)

         return encoding





      def 					_lowerCamelCase  (  self    ,						*SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)   ->					int:
         return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)





      def 					_lowerCamelCase  (  self    ,						*SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)   ->					Optional[Any]:
         return self.tokenizer.decode(*SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)





      @property
      def 					_lowerCamelCase  (  self		)   ->					List[Any]:
         lowerCamelCase__						=			self.tokenizer.model_input_names
         lowerCamelCase__						=			self.image_processor.model_input_names
         return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names		)		)





      @property
      def 					_lowerCamelCase  (  self		)   ->					Optional[Any]:
         warnings.warn(
             "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."    ,						SCREAMING_SNAKE_CASE__    ,						)
         return self.image_processor_class





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







"""simple docstring"""




from __future__ import annotations

from typing import Any



def 	UpperCAmelCase__   (				A__   )      ->      None:




   """simple docstring"""
   create_state_space_tree(A__	,    []	,    0   )



def 	UpperCAmelCase__   (				A__	,    A__	,    A__   )      ->      None:




   """simple docstring"""

   if index == len(A__   ):
      print(A__   )
      return

   create_state_space_tree(A__	,    A__	,    index + 1   )
   current_subsequence.append(sequence[index]   )
   create_state_space_tree(A__	,    A__	,    index + 1   )
   current_subsequence.pop()


if __name__ == "__main__":
     SCREAMING_SNAKE_CASE_     :			list[Any]	  =			[3, 1, 2, 4]
     generate_all_subsequences(seq)

     seq.clear()
     seq.extend(['''A''', '''B''', '''C'''])
     generate_all_subsequences(seq)




