"""simple docstring"""



import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class 						__UpperCAmelCase    (__A     ):







			'''simple docstring'''
			_UpperCamelCase  :						Dict					     =				['image_processor', 'tokenizer']
			_UpperCamelCase  :						str					     =				'CLIPImageProcessor'
			_UpperCamelCase  :						str					     =				('XLMRobertaTokenizer', 'XLMRobertaTokenizerFast')





			def __init__(			self   ,      snake_case_=None   ,      snake_case_=None   ,      **snake_case_							):







										'''simple docstring'''


										A__       :     int								=			None
										if "feature_extractor" in kwargs:
																	warnings.warn(
																	    """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
																	    """ instead."""   ,      snake_case_   ,      )
																	A__       :     List[Any]								=			kwargs.pop("""feature_extractor"""							)

										A__       :     Any								=			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__(snake_case_   ,      snake_case_							)





			def __call__(			self   ,      snake_case_=None   ,      snake_case_=None   ,      snake_case_=None   ,      **snake_case_							):







										'''simple docstring'''


										if text is None and images is None:
																	raise ValueError("""You have to specify either text or images. Both cannot be none."""							)

										if text is not None:
																	A__       :     Dict								=			self.tokenizer(snake_case_   ,      return_tensors=snake_case_   ,      **snake_case_							)

										if images is not None:
																	A__       :     Dict								=			self.image_processor(snake_case_   ,      return_tensors=snake_case_   ,      **snake_case_							)

										if text is not None and images is not None:
																	A__       :     Tuple								=			image_features.pixel_values
																	return encoding
										elif text is not None:
																	return encoding
										else:
																	return BatchEncoding(data=dict(**snake_case_							)   ,      tensor_type=snake_case_							)





			def 		lowerCamelCase					(			self   ,      *snake_case_   ,      **snake_case_							):







										'''simple docstring'''


										return self.tokenizer.batch_decode(*snake_case_   ,      **snake_case_							)





			def 		lowerCamelCase					(			self   ,      *snake_case_   ,      **snake_case_							):







										'''simple docstring'''


										return self.tokenizer.decode(*snake_case_   ,      **snake_case_							)





			@property
			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Dict								=			self.tokenizer.model_input_names
										A__       :     List[str]								=			self.image_processor.model_input_names
										return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)






"""simple docstring"""



from typing import List

from .keymap import KEYMAP, get_character

def  _A(		lowerCAmelCase							):

							def decorator(lowerCAmelCase							):
														A__       :     Any								=			getattr(lowerCAmelCase			,  """handle_key"""			,  []							)
														handle += [key]
														setattr(lowerCAmelCase			,  """handle_key"""			,  lowerCAmelCase							)
														return func

							return decorator

def  _A(		*lowerCAmelCase							):

							def decorator(lowerCAmelCase							):
														A__       :     Optional[Any]								=			getattr(lowerCAmelCase			,  """handle_key"""			,  []							)
														handle += keys
														setattr(lowerCAmelCase			,  """handle_key"""			,  lowerCAmelCase							)
														return func

							return decorator
class 						__UpperCAmelCase    (__A     ):







			'''simple docstring'''





			def __new__(			cls   ,      snake_case_   ,      snake_case_   ,      snake_case_							):







										'''simple docstring'''


										A__       :     Union[str, Any]								=			super().__new__(cls   ,      snake_case_   ,      snake_case_   ,      snake_case_							)
										if not hasattr(snake_case_   ,      """key_handler"""							):
																	setattr(snake_case_   ,      """key_handler"""   ,      {}							)
										setattr(snake_case_   ,      """handle_input"""   ,      KeyHandler.handle_input							)

										for value in attrs.values():
																	A__       :     Dict								=			getattr(snake_case_   ,      """handle_key"""   ,      []							)
																	for key in handled_keys:
																								A__       :     Optional[Any]								=			value
										return new_cls





			@staticmethod
			def 		lowerCamelCase					(			cls							):







										'''simple docstring'''


										A__       :     int								=			get_character()
										if char != KEYMAP["undefined"]:
																	A__       :     Union[str, Any]								=			ord(snake_case_							)
										A__       :     int								=			cls.key_handler.get(snake_case_							)
										if handler:
																	A__       :     int								=			char
																	return handler(cls							)
										else:
																	return None





def  _A(		cls							):
							return KeyHandler(cls.__name__			,  cls.__bases__			,  cls.__dict__.copy()							)





