import copy

from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging


_SCREAMING_SNAKE_CASE:						Tuple    	=       logging.get_logger(__name__)

class 	_SCREAMING_SNAKE_CASE							(     _a							):






		"""simple docstring"""







		A_						 =			'hybrid-clip'
		A_						 =			True



		def __init__(			self    :				Tuple  ,					__SCREAMING_SNAKE_CASE    :				List[Any]=512  ,					**__SCREAMING_SNAKE_CASE    :				Union[str, Any]   ):






					"""simple docstring"""
					super().__init__(**__SCREAMING_SNAKE_CASE   )

					if "text_config" not in kwargs:
								raise ValueError("`text_config` can not be `None`."   )

					if "vision_config" not in kwargs:
								raise ValueError("`vision_config` can not be `None`."   )

					_snake_case              =      kwargs.pop("text_config"   )
					_snake_case              =      kwargs.pop("vision_config"   )

					_snake_case              =      text_config.pop("model_type"   )
					_snake_case              =      vision_config.pop("model_type"   )

					from transformers import AutoConfig

					_snake_case              =      AutoConfig.for_model(__SCREAMING_SNAKE_CASE  ,					**__SCREAMING_SNAKE_CASE   )

					if vision_model_type == "clip":
								_snake_case              =      AutoConfig.for_model(__SCREAMING_SNAKE_CASE  ,					**__SCREAMING_SNAKE_CASE   ).vision_config
					elif vision_model_type == "clip_vision_model":
								from transformers import CLIPVisionConfig

								_snake_case              =      CLIPVisionConfig(**__SCREAMING_SNAKE_CASE   )
					else:
								_snake_case              =      AutoConfig.for_model(__SCREAMING_SNAKE_CASE  ,					**__SCREAMING_SNAKE_CASE   )

					_snake_case              =      projection_dim
					_snake_case              =      1.0



		@classmethod
		def 				_a				(			cls    :				Dict  ,					__SCREAMING_SNAKE_CASE    :				PretrainedConfig  ,					__SCREAMING_SNAKE_CASE    :				PretrainedConfig  ,					**__SCREAMING_SNAKE_CASE    :				Union[str, Any]   ):






					"""simple docstring"""
					return cls(text_config=text_config.to_dict()  ,					vision_config=vision_config.to_dict()  ,					**__SCREAMING_SNAKE_CASE   )







		def 				_a				(			self    :				Union[str, Any]   ):






					"""simple docstring"""
					_snake_case              =      copy.deepcopy(self.__dict__   )
					_snake_case              =      self.text_config.to_dict()
					_snake_case              =      self.vision_config.to_dict()
					_snake_case              =      self.__class__.model_type
					return output


def    UpperCAmelCase__(						lowerCamelCase_							,	lowerCamelCase_  ):



			"""simple docstring"""





			_snake_case              =      sorted(lowerCamelCase_							,	key=lambda lowerCamelCase_  : value[2]							,	reverse=lowerCamelCase_  )

			# Create a list of size equal to the maximum deadline
			# and initialize it with -1
			_snake_case              =      max(lowerCamelCase_							,	key=lambda lowerCamelCase_  : value[1]  )[1]
			_snake_case              =      [-1] * max_deadline

			# Finding the maximum profit and the count of jobs
			_snake_case              =      0
			_snake_case              =      0
			for job in jobs:
						# Find a free time slot for this job
						# (Note that we start from the last possible slot)
						for i in range(job[1] - 1							,	-1							,	-1  ):
									if time_slots[i] == -1:
												_snake_case              =      job[0]
												count += 1
												max_profit += job[2]
												break
			return [count, max_profit]


if __name__ == "__main__":
			import doctest

			doctest.testmod()

