


"""simple docstring"""


import heapq as hq
import math
from collections.abc import Iterator
class   _UpperCamelCase  :
							'''simple docstring'''







							def __init__(     self    ,   __a	):
										__lowerCAmelCase				    =			str(id_	)
										__lowerCAmelCase				    =			None
										__lowerCAmelCase				    =			None
										__lowerCAmelCase				    =			[]
										__lowerCAmelCase				    =			{}  # {vertex:distance}

							def __lt__(     self    ,   __a	):
										return self.key < other.key

							def __repr__(     self	):
										return self.id

							def 			snake_case				(     self    ,   __a	):
										self.neighbors.append(__a	)



							def 			snake_case				(     self    ,   __a    ,   __a	):
										__lowerCAmelCase				    =			weight


def _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase      ):

			'''simple docstring'''




			graph[a - 1].add_neighbor(graph[b - 1]      )
			graph[b - 1].add_neighbor(graph[a - 1]      )
			# add the edges:
			graph[a - 1].add_edge(graph[b - 1]    , _UpperCamelCase      )
			graph[b - 1].add_edge(graph[a - 1]    , _UpperCamelCase      )


def _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			[]
			for u in graph:
						__lowerCAmelCase				    =			math.inf
						__lowerCAmelCase				    =			None
			__lowerCAmelCase				    =			0
			__lowerCAmelCase				    =			graph[:]
			while q:
						__lowerCAmelCase				    =			min(_UpperCamelCase      )
						q.remove(_UpperCamelCase      )
						for v in u.neighbors:
									if (v in q) and (u.edges[v.id] < v.key):
												__lowerCAmelCase				    =			u
												__lowerCAmelCase				    =			u.edges[v.id]
			for i in range(1    , len(_UpperCamelCase      )      ):
						a.append((int(graph[i].id      ) + 1, int(graph[i].pi.id      ) + 1)      )
			return a


def _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase      ):

			'''simple docstring'''




			for u in graph:
						__lowerCAmelCase				    =			math.inf
						__lowerCAmelCase				    =			None
			__lowerCAmelCase				    =			0

			__lowerCAmelCase				    =			list(_UpperCamelCase      )
			hq.heapify(_UpperCamelCase      )

			while h:
						__lowerCAmelCase				    =			hq.heappop(_UpperCamelCase      )
						for v in u.neighbors:
									if (v in h) and (u.edges[v.id] < v.key):
												__lowerCAmelCase				    =			u
												__lowerCAmelCase				    =			u.edges[v.id]
												hq.heapify(_UpperCamelCase      )

			for i in range(1    , len(_UpperCamelCase      )      ):
						yield (int(graph[i].id      ) + 1, int(graph[i].pi.id      ) + 1)


def _lowerCamelCase	(		):

			'''simple docstring'''






if __name__ == "__main__":
	import doctest

	doctest.testmod()








"""simple docstring"""


import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


A     :   Dict			    =			logging.getLogger(__name__)
@dataclass
class   _UpperCamelCase  (   lowerCAmelCase__		):
							'''simple docstring'''







							__UpperCAmelCase						:    Optional[float]				      =field(
							    default=0.0       ,metadata={"""help""": """The label smoothing epsilon to apply (if not zero)."""}		)
							__UpperCAmelCase						:    bool				      =field(default=lowerCAmelCase__       ,metadata={"""help""": """Whether to SortishSamler or not."""}		)
							__UpperCAmelCase						:    bool				      =field(
							    default=lowerCAmelCase__       ,metadata={"""help""": """Whether to use generate to calculate generative metrics (ROUGE, BLEU)."""}		)
							__UpperCAmelCase						:    bool				      =field(default=lowerCAmelCase__       ,metadata={"""help""": """whether to use adafactor"""}		)
							__UpperCAmelCase						:    Optional[float]				      =field(
							    default=lowerCAmelCase__       ,metadata={"""help""": """Encoder layer dropout probability. Goes into model.config."""}		)
							__UpperCAmelCase						:    Optional[float]				      =field(
							    default=lowerCAmelCase__       ,metadata={"""help""": """Decoder layer dropout probability. Goes into model.config."""}		)
							__UpperCAmelCase						:    Optional[float]				      =field(default=lowerCAmelCase__       ,metadata={"""help""": """Dropout probability. Goes into model.config."""}		)
							__UpperCAmelCase						:    Optional[float]				      =field(
							    default=lowerCAmelCase__       ,metadata={"""help""": """Attention dropout probability. Goes into model.config."""}		)
							__UpperCAmelCase						:    Optional[str]				      =field(
							    default="""linear"""       ,metadata={"""help""": F'''Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()		)}'''}       ,)




