
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'''





	snake_case_					    =     ["image_processor", "tokenizer"]
	snake_case_					    =     "BridgeTowerImageProcessor"
	snake_case_					    =     ("RobertaTokenizer", "RobertaTokenizerFast")






	def __init__(       self					: Any							,A					: str							,A					: int ):
					super().__init__(A							,A )






	def __call__(       self					: Optional[int]							,A					: Tuple							,A					: Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None							,A					: bool = True							,A					: Union[bool, str, PaddingStrategy] = False							,A					: Union[bool, str, TruncationStrategy] = None							,A					: Optional[int] = None							,A					: int = 0							,A					: Optional[int] = None							,A					: Optional[bool] = None							,A					: Optional[bool] = None							,A					: bool = False							,A					: bool = False							,A					: bool = False							,A					: bool = False							,A					: bool = True							,A					: Optional[Union[str, TensorType]] = None							,**A					: List[str]							,):
					__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							,do_normalize=A							,do_center_crop=A							,**A )
					encoding.update(A )

					return encoding






	def 				UpperCamelCase_  (       self					: Optional[Any]							,*A					: Optional[Any]							,**A					: str ):
					return self.tokenizer.batch_decode(*A							,**A )






	def 				UpperCamelCase_  (       self					: Tuple							,*A					: str							,**A					: Any ):
					return self.tokenizer.decode(*A							,**A )







	@property
	def 				UpperCamelCase_  (       self					: Tuple ):
					__A   			= self.tokenizer.model_input_names
					__A   			= self.image_processor.model_input_names
					return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names ) )


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


SCREAMING_SNAKE_CASE							:List[Any]							 =				{}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE							:List[str]							 =				['BartphoTokenizer']

if TYPE_CHECKING:
					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_bartpho import BartphoTokenizer

else:
					import sys

					SCREAMING_SNAKE_CASE							:Union[str, Any]							 =				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
