


class       lowercase_					:





				def __init__(				self)  -> str:
											a__      =0
											a__      =0
											a__      ={}





				def 						__UpperCamelCase    (				self       ,  lowercase_)  -> Dict:
											if vertex not in self.adjacency:
																		a__      ={}
																		self.num_vertices += 1





				def 						__UpperCamelCase    (				self       ,  lowercase_       ,  lowercase_       ,  lowercase_)  -> Dict:
											self.add_vertex(lowercase_)
											self.add_vertex(lowercase_)

											if head == tail:
																		return

											a__      =weight
											a__      =weight





				def 						__UpperCamelCase    (				self)  -> Optional[int]:
											a__      =self.get_edges()
											for edge in edges:
																		a__    ,     a__    ,     a__      =edge
																		edges.remove((tail, head, weight))
											for i in range(len(lowercase_)):
																		a__      =list(edges[i])

											edges.sort(key=lambda lowercase_: e[2])
											for i in range(len(lowercase_) - 1):
																		if edges[i][2] >= edges[i + 1][2]:
																									a__      =edges[i][2] + 1
											for edge in edges:
																		a__    ,     a__    ,     a__      =edge
																		a__      =weight
																		a__      =weight





				def __str__(				self)  -> Tuple:
											a__      =''
											for tail in self.adjacency:
																		for head in self.adjacency[tail]:
																									a__      =self.adjacency[head][tail]
																									string += F"""{head} -> {tail} == {weight}\n"""
											return string.rstrip('\n')





				def 						__UpperCamelCase    (				self)  -> Union[str, Any]:
											a__      =[]
											for tail in self.adjacency:
																		for head in self.adjacency[tail]:
																									output.append((tail, head, self.adjacency[head][tail]))
											return output





				def 						__UpperCamelCase    (				self)  -> int:
											return self.adjacency.keys()





				@staticmethod
				def 						__UpperCamelCase    (				lowercase_=None       ,  lowercase_=None)  -> Dict:
											a__      =Graph()
											if vertices is None:
																		a__      =[]
											if edges is None:
																		a__      =[]
											for vertex in vertices:
																		g.add_vertex(lowercase_)
											for edge in edges:
																		g.add_edge(*lowercase_)
											return g




				class       lowercase_					:





								def __init__(				self)  -> Tuple:
															a__      ={}
															a__      ={}





								def __len__(				self)  -> Dict:
															return len(self.parent)





								def 						__UpperCamelCase    (				self       ,  lowercase_)  -> Dict:
															if item in self.parent:
																						return self.find(lowercase_)

															a__      =item
															a__      =0
															return item





								def 						__UpperCamelCase    (				self       ,  lowercase_)  -> Optional[Any]:
															if item not in self.parent:
																						return self.make_set(lowercase_)
															if item != self.parent[item]:
																						a__      =self.find(self.parent[item])
															return self.parent[item]





								def 						__UpperCamelCase    (				self       ,  lowercase_       ,  lowercase_)  -> Dict:
															a__      =self.find(lowercase_)
															a__      =self.find(lowercase_)

															if roota == roota:
																						return roota

															if self.rank[roota] > self.rank[roota]:
																						a__      =roota
																						return roota

															if self.rank[roota] < self.rank[roota]:
																						a__      =roota
																						return roota

															if self.rank[roota] == self.rank[roota]:
																						self.rank[roota] += 1
																						a__      =roota
																						return roota
															return None







				@staticmethod
				def 						__UpperCamelCase    (				lowercase_)  -> Optional[Any]:
											a__      =graph.num_vertices

											a__      =Graph.UnionFind()
											a__      =[]
											while num_components > 1:
																		a__      ={}
																		for vertex in graph.get_vertices():
																									a__      =-1

																		a__      =graph.get_edges()
																		for edge in edges:
																									a__    ,     a__    ,     a__      =edge
																									edges.remove((tail, head, weight))
																		for edge in edges:
																									a__    ,     a__    ,     a__      =edge
																									a__      =union_find.find(lowercase_)
																									a__      =union_find.find(lowercase_)
																									if seta != seta:
																																if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
																																							a__      =[head, tail, weight]

																																if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
																																							a__      =[head, tail, weight]
																		for vertex in cheap_edge:
																									if cheap_edge[vertex] != -1:
																																a__    ,     a__    ,     a__      =cheap_edge[vertex]
																																if union_find.find(lowercase_) != union_find.find(lowercase_):
																																							union_find.union(lowercase_       ,  lowercase_)
																																							mst_edges.append(cheap_edge[vertex])
																																							a__      =num_components - 1
											a__      =Graph.build(edges=lowercase_)
											return mst






"""simple docstring"""






import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin



class      A__  (    __SCREAMING_SNAKE_CASE    ,						__SCREAMING_SNAKE_CASE    ,						__SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	@register_to_config
	def __init__(	self:						List[str]			,     _SCREAMING_SNAKE_CASE:						int			,     _SCREAMING_SNAKE_CASE:						int			,     _SCREAMING_SNAKE_CASE:						int			,     _SCREAMING_SNAKE_CASE:						float			,     _SCREAMING_SNAKE_CASE:						int			,     _SCREAMING_SNAKE_CASE:						int			,     _SCREAMING_SNAKE_CASE:						int			,     _SCREAMING_SNAKE_CASE:						int			,     _SCREAMING_SNAKE_CASE:						str			,     _SCREAMING_SNAKE_CASE:						bool = False			,     )							->			Any:

				"""simple docstring"""

				super().__init__()

				__lowerCAmelCase :    str				=			nn.Embedding(_SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    Dict				=			nn.Embedding(_SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE)
				__lowerCAmelCase :    str				=			False

				__lowerCAmelCase :    Optional[Any]				=			nn.Dropout(p=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    Dict				=			TaConfig(
				    vocab_size=_SCREAMING_SNAKE_CASE			,     d_model=_SCREAMING_SNAKE_CASE			,     num_heads=_SCREAMING_SNAKE_CASE			,     d_kv=_SCREAMING_SNAKE_CASE			,     d_ff=_SCREAMING_SNAKE_CASE			,     dropout_rate=_SCREAMING_SNAKE_CASE			,     feed_forward_proj=_SCREAMING_SNAKE_CASE			,     is_decoder=_SCREAMING_SNAKE_CASE			,     is_encoder_decoder=_SCREAMING_SNAKE_CASE			,     )

				__lowerCAmelCase :    str				=			nn.ModuleList()
				for lyr_num in range(_SCREAMING_SNAKE_CASE):
							__lowerCAmelCase :    int				=			TaBlock(_SCREAMING_SNAKE_CASE)
							self.encoders.append(_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    Dict				=			TaLayerNorm(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase :    Any				=			nn.Dropout(p=_SCREAMING_SNAKE_CASE)







	def 				_SCREAMING_SNAKE_CASE  (	self:						Any			,     _SCREAMING_SNAKE_CASE:						Tuple			,     _SCREAMING_SNAKE_CASE:						str)							->			List[str]:

				"""simple docstring"""

				__lowerCAmelCase :    Union[str, Any]				=			self.token_embedder(_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    Optional[Any]				=			encoder_input_tokens.shape[1]
				__lowerCAmelCase :    List[Any]				=			torch.arange(_SCREAMING_SNAKE_CASE			,     device=encoder_input_tokens.device)
				x += self.position_encoding(_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    List[Any]				=			self.dropout_pre(_SCREAMING_SNAKE_CASE)

				# inverted the attention mask
				__lowerCAmelCase :    List[Any]				=			encoder_input_tokens.size()
				__lowerCAmelCase :    Any				=			self.get_extended_attention_mask(_SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE)

				for lyr in self.encoders:
							__lowerCAmelCase :    Union[str, Any]				=			lyr(_SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE)[0]
				__lowerCAmelCase :    int				=			self.layer_norm(_SCREAMING_SNAKE_CASE)

				return self.dropout_post(_SCREAMING_SNAKE_CASE), encoder_inputs_mask