


from __future__ import annotations

from typing import Generic, TypeVar

snake_case__			 =						TypeVar('''T''')


class 					lowerCAmelCase_ (       Generic[T]):




						def __init__(	self						:   Optional[int]   ,     __A						:   T						)      ->None:






									"""simple docstring"""






									a__ :Tuple						  =    data
									a__ :List[Any]						  =    self
									a__ :Optional[Any]						  =    0






class 					lowerCAmelCase_ (       Generic[T]):




						def __init__(	self						:   Optional[Any]						)      ->None:






									"""simple docstring"""






									a__ :dict[T, DisjointSetTreeNode[T]]						  =    {}




						def  _snake_case					(	self						:   Dict   ,     __A						:   T						)      ->None:






									"""simple docstring"""






									a__ :List[Any]						  =    DisjointSetTreeNode(__A						)




						def  _snake_case					(	self						:   str   ,     __A						:   T						)      ->DisjointSetTreeNode[T]:






									"""simple docstring"""






									a__ :Optional[Any]						  =    self.map[data]
									if elem_ref != elem_ref.parent:
												a__ :List[str]						  =    self.find_set(elem_ref.parent.data						)
									return elem_ref.parent




						def  _snake_case					(	self						:   int   ,     __A						:   DisjointSetTreeNode[T]   ,     __A						:   DisjointSetTreeNode[T]						)      ->None:






									"""simple docstring"""






									if nodea.rank > nodea.rank:
												a__ :Union[str, Any]						  =    nodea
									else:
												a__ :Optional[Any]						  =    nodea
												if nodea.rank == nodea.rank:
															nodea.rank += 1






						def  _snake_case					(	self						:   List[str]   ,     __A						:   T   ,     __A						:   T						)      ->None:






									"""simple docstring"""






									self.link(self.find_set(__A						)   ,     self.find_set(__A						)						)






class 					lowerCAmelCase_ (       Generic[T]):




						def __init__(	self						:   List[str]						)      ->None:






									"""simple docstring"""






									a__ :dict[T, dict[T, int]]						  =    {}




						def  _snake_case					(	self						:   List[Any]   ,     __A						:   T						)      ->None:






									"""simple docstring"""






									if node not in self.connections:
												a__ :Dict						  =    {}




						def  _snake_case					(	self						:   int   ,     __A						:   T   ,     __A						:   T   ,     __A						:   int						)      ->None:






									"""simple docstring"""






									self.add_node(__A						)
									self.add_node(__A						)
									a__ :Any						  =    weight
									a__ :List[str]						  =    weight






						def  _snake_case					(	self						:   str						)      ->GraphUndirectedWeighted[T]:






									"""simple docstring"""






									a__ :int						  =    []
									a__ :List[Any]						  =    set()
									for start in self.connections:
												for end in self.connections[start]:
															if (start, end) not in seen:
																		seen.add((end, start)						)
																		edges.append((start, end, self.connections[start][end])						)
									edges.sort(key=lambda __A						: x[2]						)

									# creating the disjoint set
									a__ :int						  =    DisjointSetTree[T]()
									for node in self.connections:
												disjoint_set.make_set(__A						)

									# MST generation
									a__ :int						  =    0
									a__ :Union[str, Any]						  =    0
									a__ :int						  =    GraphUndirectedWeighted[T]()
									while num_edges < len(self.connections						) - 1:
												a__  ,  a__  ,  a__ :List[Any]						  =    edges[index]
												index += 1
												a__ :int						  =    disjoint_set.find_set(__A						)
												a__ :Dict						  =    disjoint_set.find_set(__A						)
												if parent_u != parent_v:
															num_edges += 1
															graph.add_edge(__A   ,     __A   ,     __A						)
															disjoint_set.union(__A   ,     __A						)
									return graph






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


snake_case__			 =						logging.get_logger(__name__)

snake_case__			 =						{
    '''google/pegasus-large''': '''https://huggingface.co/google/pegasus-large/resolve/main/config.json''',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}


class 					lowerCAmelCase_ (       _a):
						lowerCamelCase_         =     'pegasus'
						lowerCamelCase_         =     ['past_key_values']
						lowerCamelCase_         =     {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}




						def __init__(	self						:   Any   ,     __A						:   Dict=50265   ,     __A						:   List[Any]=1024   ,     __A						:   int=12   ,     __A						:   Optional[Any]=4096   ,     __A						:   Optional[int]=16   ,     __A						:   Dict=12   ,     __A						:   List[Any]=4096   ,     __A						:   List[str]=16   ,     __A						:   Optional[int]=0.0   ,     __A						:   List[Any]=0.0   ,     __A						:   List[str]=True   ,     __A						:   Optional[int]=True   ,     __A						:   str="gelu"   ,     __A						:   Tuple=1024   ,     __A						:   Any=0.1   ,     __A						:   List[Any]=0.0   ,     __A						:   List[str]=0.0   ,     __A						:   Tuple=0.02   ,     __A						:   Union[str, Any]=0   ,     __A						:   Union[str, Any]=False   ,     __A						:   Optional[Any]=0   ,     __A						:   Tuple=1   ,     __A						:   str=1   ,     **__A						:   Any   ,     )      ->Union[str, Any]:






									"""simple docstring"""






									a__ :Any						  =    vocab_size
									a__ :List[str]						  =    max_position_embeddings
									a__ :int						  =    d_model
									a__ :Union[str, Any]						  =    encoder_ffn_dim
									a__ :List[Any]						  =    encoder_layers
									a__ :Union[str, Any]						  =    encoder_attention_heads
									a__ :Tuple						  =    decoder_ffn_dim
									a__ :List[Any]						  =    decoder_layers
									a__ :Tuple						  =    decoder_attention_heads
									a__ :Optional[int]						  =    dropout
									a__ :str						  =    attention_dropout
									a__ :Optional[int]						  =    activation_dropout
									a__ :str						  =    activation_function
									a__ :Dict						  =    init_std
									a__ :Any						  =    encoder_layerdrop
									a__ :int						  =    decoder_layerdrop
									a__ :Union[str, Any]						  =    use_cache
									a__ :List[Any]						  =    encoder_layers
									a__ :Dict						  =    scale_embedding  # scale factor will be sqrt(d_model) if True
									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  _snake_case					(	self						:   Optional[Any]						)      ->int:






									"""simple docstring"""






									return self.encoder_attention_heads






						@property
						def  _snake_case					(	self						:   Union[str, Any]						)      ->int:






									"""simple docstring"""






									return self.d_model


