"""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 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

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







					def __init__(				self   :	List[str]    ,lowerCamelCase__   :	Dict    ,lowerCamelCase__   :	Union[str, Any]			):
									super().__init__(lowerCamelCase__    ,lowerCamelCase__			)







					def __call__(				self   :	Optional[int]    ,lowerCamelCase__   :	Tuple    ,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__   :	Tuple    ,):
									UpperCAmelCase__             =							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
									UpperCAmelCase__             =							self.image_processor(
									    lowerCamelCase__    ,return_tensors=lowerCamelCase__    ,do_normalize=lowerCamelCase__    ,do_center_crop=lowerCamelCase__    ,**lowerCamelCase__			)
									encoding.update(lowerCamelCase__			)

									return encoding







					def 		__lowerCAmelCase						(				self   :	Union[str, Any]    ,*lowerCamelCase__   :	Optional[int]    ,**lowerCamelCase__   :	Optional[Any]			):
									return self.tokenizer.batch_decode(*lowerCamelCase__    ,**lowerCamelCase__			)







					def 		__lowerCAmelCase						(				self   :	List[str]    ,*lowerCamelCase__   :	Union[str, Any]    ,**lowerCamelCase__   :	List[str]			):
									return self.tokenizer.decode(*lowerCamelCase__    ,**lowerCamelCase__			)







					@property
					def 		__lowerCAmelCase						(				self   :	int			):
									UpperCAmelCase__             =							self.tokenizer.model_input_names
									UpperCAmelCase__             =							self.image_processor.model_input_names
									return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names			)			)




"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase__  :  str						     =	{
    'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'],
    'tokenization_roc_bert': ['RoCBertTokenizer'],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						pass

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__  :  List[str]						     =	[
						    'ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'RoCBertForCausalLM',
						    'RoCBertForMaskedLM',
						    'RoCBertForMultipleChoice',
						    'RoCBertForPreTraining',
						    'RoCBertForQuestionAnswering',
						    'RoCBertForSequenceClassification',
						    'RoCBertForTokenClassification',
						    'RoCBertLayer',
						    'RoCBertModel',
						    'RoCBertPreTrainedModel',
						    'load_tf_weights_in_roc_bert',
						]

if TYPE_CHECKING:
						from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
						from .tokenization_roc_bert import RoCBertTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												raise OptionalDependencyNotAvailable()

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_roc_bert import (
												    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    RoCBertForCausalLM,
												    RoCBertForMaskedLM,
												    RoCBertForMultipleChoice,
												    RoCBertForPreTraining,
												    RoCBertForQuestionAnswering,
												    RoCBertForSequenceClassification,
												    RoCBertForTokenClassification,
												    RoCBertLayer,
												    RoCBertModel,
												    RoCBertPreTrainedModel,
												    load_tf_weights_in_roc_bert,
												)


else:
						import sys

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



