





"""simple docstring"""






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 					__lowercase      (      _UpperCamelCase				):







					'''simple docstring'''




					__lowerCAmelCase	=	['''image_processor''', '''tokenizer''']
					__lowerCAmelCase	=	'''BridgeTowerImageProcessor'''
					__lowerCAmelCase	=	('''RobertaTokenizer''', '''RobertaTokenizerFast''')







					def __init__(    self						,      _UpperCAmelCase						,      _UpperCAmelCase  ):
									super().__init__(_UpperCAmelCase						,      _UpperCAmelCase  )







					def __call__(    self						,      _UpperCAmelCase						,      _UpperCAmelCase = None						,      _UpperCAmelCase = True						,      _UpperCAmelCase = False						,      _UpperCAmelCase = None						,      _UpperCAmelCase = None						,      _UpperCAmelCase = 0						,      _UpperCAmelCase = None						,      _UpperCAmelCase = None						,      _UpperCAmelCase = None						,      _UpperCAmelCase = False						,      _UpperCAmelCase = False						,      _UpperCAmelCase = False						,      _UpperCAmelCase = False						,      _UpperCAmelCase = True						,      _UpperCAmelCase = None						,      **_UpperCAmelCase						,      ):
									__a			:    Optional[Any]      							=	self.tokenizer(
									    text=_UpperCAmelCase						,      add_special_tokens=_UpperCAmelCase						,      padding=_UpperCAmelCase						,      truncation=_UpperCAmelCase						,      max_length=_UpperCAmelCase						,      stride=_UpperCAmelCase						,      pad_to_multiple_of=_UpperCAmelCase						,      return_token_type_ids=_UpperCAmelCase						,      return_attention_mask=_UpperCAmelCase						,      return_overflowing_tokens=_UpperCAmelCase						,      return_special_tokens_mask=_UpperCAmelCase						,      return_offsets_mapping=_UpperCAmelCase						,      return_length=_UpperCAmelCase						,      verbose=_UpperCAmelCase						,      return_tensors=_UpperCAmelCase						,      **_UpperCAmelCase						,      )
									# add pixel_values + pixel_mask
									__a			:    Optional[int]      							=	self.image_processor(
									    _UpperCAmelCase						,      return_tensors=_UpperCAmelCase						,      do_normalize=_UpperCAmelCase						,      do_center_crop=_UpperCAmelCase						,      **_UpperCAmelCase  )
									encoding.update(_UpperCAmelCase  )

									return encoding







					def 			_lowerCamelCase		(    self						,      *_UpperCAmelCase						,      **_UpperCAmelCase  ):
									return self.tokenizer.batch_decode(*_UpperCAmelCase						,      **_UpperCAmelCase  )







					def 			_lowerCamelCase		(    self						,      *_UpperCAmelCase						,      **_UpperCAmelCase  ):
									return self.tokenizer.decode(*_UpperCAmelCase						,      **_UpperCAmelCase  )







					@property
					def 			_lowerCamelCase		(    self  ):
									__a			:    List[str]      							=	self.tokenizer.model_input_names
									__a			:    Any      							=	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,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase__							  =						{"processing_layoutxlm": ["LayoutXLMProcessor"]}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase__							  =						["LayoutXLMTokenizer"]

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase__							  =						["LayoutXLMTokenizerFast"]

if TYPE_CHECKING:
     from .processing_layoutxlm import LayoutXLMProcessor

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_layoutxlm import LayoutXLMTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_layoutxlm_fast import LayoutXLMTokenizerFast

else:
     import sys

     UpperCAmelCase__							  =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


