
'''simple docstring'''



class     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE					):






						'''simple docstring'''






						pass






class     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE					):






						'''simple docstring'''






						pass






class     UpperCAmelCase_	:






						'''simple docstring'''






						def __init__(   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					[
												    [],
												    [],
												    [],
												]




						def    _lowercase      (   self       ,  _lowercase       ,  _lowercase ):

												"""simple docstring"""



												try:
																		if len(self.queues[priority] ) >= 100:
																								raise OverflowError("""Maximum queue size is 100""" )
																		self.queues[priority].append(_lowercase )
												except IndexError:
																		raise ValueError("""Valid priorities are 0, 1, and 2""" )




						def    _lowercase      (   self ):

												"""simple docstring"""



												for queue in self.queues:
																		if queue:
																								return queue.pop(0 )
												raise UnderFlowError("""All queues are empty""" )




						def __str__(   self ):

												"""simple docstring"""



												return "\n".join(F'Priority {i}: {q}' for i, q in enumerate(self.queues ) )






class     UpperCAmelCase_	:






						'''simple docstring'''






						def __init__(   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					[]




						def    _lowercase      (   self       ,  _lowercase ):

												"""simple docstring"""



												if len(self.queue ) == 100:
																		raise OverFlowError("""Maximum queue size is 100""" )
												self.queue.append(_lowercase )




						def    _lowercase      (   self ):

												"""simple docstring"""



												if not self.queue:
																		raise UnderFlowError("""The queue is empty""" )
												else:
																		_lowerCAmelCase    		=					min(self.queue )
																		self.queue.remove(_lowercase )
																		return data




						def __str__(   self ):

												"""simple docstring"""



												return str(self.queue )






def A ():
						_lowerCAmelCase    		=					FixedPriorityQueue()
						fpq.enqueue(0					,      10						)
						fpq.enqueue(1					,      70						)
						fpq.enqueue(0					,      100						)
						fpq.enqueue(2					,      1						)
						fpq.enqueue(2					,      5						)
						fpq.enqueue(1					,      7						)
						fpq.enqueue(2					,      4						)
						fpq.enqueue(1					,      64						)
						fpq.enqueue(0					,      128						)
						print(__lowerCamelCase						)
						print(fpq.dequeue()						)
						print(fpq.dequeue()						)
						print(fpq.dequeue()						)
						print(fpq.dequeue()						)
						print(fpq.dequeue()						)
						print(__lowerCamelCase						)
						print(fpq.dequeue()						)
						print(fpq.dequeue()						)
						print(fpq.dequeue()						)
						print(fpq.dequeue()						)
						print(fpq.dequeue()						)


def A ():
						_lowerCAmelCase    		=					ElementPriorityQueue()
						epq.enqueue(10						)
						epq.enqueue(70						)
						epq.enqueue(100						)
						epq.enqueue(1						)
						epq.enqueue(5						)
						epq.enqueue(7						)
						epq.enqueue(4						)
						epq.enqueue(64						)
						epq.enqueue(128						)
						print(__lowerCamelCase						)
						print(epq.dequeue()						)
						print(epq.dequeue()						)
						print(epq.dequeue()						)
						print(epq.dequeue()						)
						print(epq.dequeue()						)
						print(__lowerCamelCase						)
						print(epq.dequeue()						)
						print(epq.dequeue()						)
						print(epq.dequeue()						)
						print(epq.dequeue()						)
						print(epq.dequeue()						)


if __name__ == "__main__":
						fixed_priority_queue()
						element_priority_queue()


'''simple docstring'''



from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
						if not (is_transformers_available() and is_torch_available()):
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						from ...utils.dummy_torch_and_transformers_objects import (
						    ImageTextPipelineOutput,
						    UniDiffuserPipeline,
						)
else:
						from .modeling_text_decoder import UniDiffuserTextDecoder
						from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
						from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline
