


'''simple docstring'''

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


__lowercase:		int    						=  logging.get_logger(__name__)

__lowercase:		str    						=  {
    "google/pegasus-x-base": "https://huggingface.co/google/pegasus-x-base/resolve/main/config.json",
    "google/pegasus-x-large": "https://huggingface.co/google/pegasus-x-large/resolve/main/config.json",
    # See all PEGASUS-X models at https://huggingface.co/models?filter=pegasus-x
}







class 			UpperCAmelCase			(							SCREAMING_SNAKE_CASE__):
 _lowerCamelCase			:       Dict            =       'pegasus_x'
 _lowerCamelCase			:       Union[str, Any]            =       ['past_key_values']
 _lowerCamelCase			:       Any            =       {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}

 def __init__(			self			:						List[str],       a_			:						Any=9_6103,       a_			:						Union[str, Any]=1_6384,       a_			:						Optional[Any]=16,       a_			:						Tuple=4096,       a_			:						Optional[Any]=16,       a_			:						Optional[Any]=16,       a_			:						Tuple=4096,       a_			:						int=16,       a_			:						List[str]=0.0,       a_			:						Tuple=0.0,       a_			:						Tuple=True,       a_			:						str=True,       a_			:						int="gelu",       a_			:						Optional[Any]=1024,       a_			:						List[Any]=0.1,       a_			:						List[Any]=0.0,       a_			:						Any=0.0,       a_			:						str=0.02,       a_			:						Tuple=0,       a_			:						List[Any]=True,       a_			:						Tuple=0,       a_			:						Optional[int]=1,       a_			:						List[str]=1,       a_			:						Dict=32,       a_			:						Union[str, Any]=512,       a_			:						int=True,       **a_			:						List[Any],       ):





    """simple docstring"""



    UpperCamelCase__			    =    vocab_size
    UpperCamelCase__			    =    max_position_embeddings
    UpperCamelCase__			    =    d_model
    UpperCamelCase__			    =    encoder_ffn_dim
    UpperCamelCase__			    =    encoder_layers
    UpperCamelCase__			    =    encoder_attention_heads
    UpperCamelCase__			    =    decoder_ffn_dim
    UpperCamelCase__			    =    decoder_layers
    UpperCamelCase__			    =    decoder_attention_heads
    UpperCamelCase__			    =    dropout
    UpperCamelCase__			    =    attention_dropout
    UpperCamelCase__			    =    activation_dropout
    UpperCamelCase__			    =    activation_function
    UpperCamelCase__			    =    init_std
    UpperCamelCase__			    =    encoder_layerdrop
    UpperCamelCase__			    =    decoder_layerdrop
    UpperCamelCase__			    =    use_cache
    UpperCamelCase__			    =    encoder_layers
    UpperCamelCase__			    =    scale_embedding  # scale factor will be sqrt(d_model) if True

    UpperCamelCase__			    =    num_global_tokens
    UpperCamelCase__			    =    block_size
    UpperCamelCase__			    =    stagger_local_blocks

    super().__init__(
        pad_token_id=a_,       eos_token_id=a_,       is_encoder_decoder=a_,       decoder_start_token_id=a_,       forced_eos_token_id=a_,       **a_,       )

 @property
 def 		lowercase_    (			self			:						Union[str, Any]       ):





    """simple docstring"""



    return self.encoder_attention_heads

 @property
 def 		lowercase_    (			self			:						Optional[int]       ):





    """simple docstring"""



    return self.d_model




'''simple docstring'''



def 							__UpperCAmelCase				(				UpperCamelCase__				:int   ,				UpperCamelCase__				:list			)		->						list:
				snake_case__      :   List[str]      =    sorted(UpperCamelCase__   ,				key=lambda UpperCamelCase__			: value[2]   ,				reverse=UpperCamelCase__			)

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

				# Finding the maximum profit and the count of jobs
				snake_case__      :   List[str]      =    0
				snake_case__      :   Optional[Any]      =    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__      :   Optional[Any]      =    job[0]
																count += 1
																max_profit += job[2]
																break
				return [count, max_profit]


if __name__ == "__main__":
				import doctest

				doctest.testmod()




