


'''simple docstring'''

import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
							from transformers.models.rag.configuration_rag import RagConfig
							from transformers.models.rag.tokenization_rag import RagTokenizer
@require_faiss
@require_torch
class _lowerCamelCase	(						lowercase__							):



		'''simple docstring'''







		def        __lowerCAmelCase		( self		:						Tuple      )  ->			Any:
			__magic_name__	:   Dict					     =					tempfile.mkdtemp()
			__magic_name__	:   Any					     =					8

			# DPR tok
			__magic_name__	:   str					     =					[
			    '[UNK]',
			    '[CLS]',
			    '[SEP]',
			    '[PAD]',
			    '[MASK]',
			    'want',
			    '##want',
			    '##ed',
			    'wa',
			    'un',
			    'runn',
			    '##ing',
			    ',',
			    'low',
			    'lowest',
			]
			__magic_name__	:   List[Any]					     =					os.path.join(self.tmpdirname  ,					'dpr_tokenizer'      )
			os.makedirs(_A  ,					exist_ok=_A      )
			__magic_name__	:   Any					     =					os.path.join(_A  ,					DPR_VOCAB_FILES_NAMES['vocab_file']      )
			with open(self.vocab_file  ,					'w'  ,					encoding='utf-8'      ) as vocab_writer:
				vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]      )      )

			# BART tok
			__magic_name__	:   List[Any]					     =					[
			    'l',
			    'o',
			    'w',
			    'e',
			    'r',
			    's',
			    't',
			    'i',
			    'd',
			    'n',
			    '\u0120',
			    '\u0120l',
			    '\u0120n',
			    '\u0120lo',
			    '\u0120low',
			    'er',
			    '\u0120lowest',
			    '\u0120newer',
			    '\u0120wider',
			    '<unk>',
			]
			__magic_name__	:   Union[str, Any]					     =					dict(zip(_A  ,					range(len(_A      )      )      )      )
			__magic_name__	:   Tuple					     =					['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
			__magic_name__	:   Optional[int]					     =					{'unk_token': '<unk>'}

			__magic_name__	:   List[Any]					     =					os.path.join(self.tmpdirname  ,					'bart_tokenizer'      )
			os.makedirs(_A  ,					exist_ok=_A      )
			__magic_name__	:   List[Any]					     =					os.path.join(_A  ,					BART_VOCAB_FILES_NAMES['vocab_file']      )
			__magic_name__	:   Union[str, Any]					     =					os.path.join(_A  ,					BART_VOCAB_FILES_NAMES['merges_file']      )
			with open(self.vocab_file  ,					'w'  ,					encoding='utf-8'      ) as fp:
				fp.write(json.dumps(_A      ) + '\n'      )
			with open(self.merges_file  ,					'w'  ,					encoding='utf-8'      ) as fp:
				fp.write('\n'.join(_A      )      )







		def        __lowerCAmelCase		( self		:						Union[str, Any]      )  ->			DPRQuestionEncoderTokenizer:
			return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname  ,					'dpr_tokenizer'      )      )







		def        __lowerCAmelCase		( self		:						Optional[int]      )  ->			BartTokenizer:
			return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname  ,					'bart_tokenizer'      )      )







		def        __lowerCAmelCase		( self		:						str      )  ->			Union[str, Any]:
			shutil.rmtree(self.tmpdirname      )







		@require_tokenizers
		def        __lowerCAmelCase		( self		:						Union[str, Any]      )  ->			str:
			__magic_name__	:   Optional[Any]					     =					os.path.join(self.tmpdirname  ,					'rag_tokenizer'      )
			__magic_name__	:   List[str]					     =					RagConfig(question_encoder=DPRConfig().to_dict()  ,					generator=BartConfig().to_dict()      )
			__magic_name__	:   Union[str, Any]					     =					RagTokenizer(question_encoder=self.get_dpr_tokenizer()  ,					generator=self.get_bart_tokenizer()      )
			rag_config.save_pretrained(_A      )
			rag_tokenizer.save_pretrained(_A      )
			__magic_name__	:   List[Any]					     =					RagTokenizer.from_pretrained(_A  ,					config=_A      )
			self.assertIsInstance(new_rag_tokenizer.question_encoder  ,					_A      )
			self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()  ,					rag_tokenizer.question_encoder.get_vocab()      )
			self.assertIsInstance(new_rag_tokenizer.generator  ,					_A      )
			self.assertEqual(new_rag_tokenizer.generator.get_vocab()  ,					rag_tokenizer.generator.get_vocab()      )







		@slow
		def        __lowerCAmelCase		( self		:						Optional[Any]      )  ->			int:
			__magic_name__	:   int					     =					RagTokenizer.from_pretrained('facebook/rag-token-nq'      )
			__magic_name__	:   Union[str, Any]					     =					[
			    'who got the first nobel prize in physics',
			    'when is the next deadpool movie being released',
			    'which mode is used for short wave broadcast service',
			    'who is the owner of reading football club',
			    'when is the next scandal episode coming out',
			    'when is the last time the philadelphia won the superbowl',
			    'what is the most current adobe flash player version',
			    'how many episodes are there in dragon ball z',
			    'what is the first step in the evolution of the eye',
			    'where is gall bladder situated in human body',
			    'what is the main mineral in lithium batteries',
			    'who is the president of usa right now',
			    'where do the greasers live in the outsiders',
			    'panda is a national animal of which country',
			    'what is the name of manchester united stadium',
			]
			__magic_name__	:   Optional[int]					     =					tokenizer(_A      )
			self.assertIsNotNone(_A      )







		@slow
		def        __lowerCAmelCase		( self		:						str      )  ->			List[Any]:
			__magic_name__	:   Any					     =					RagTokenizer.from_pretrained('facebook/rag-sequence-nq'      )
			__magic_name__	:   Tuple					     =					[
			    'who got the first nobel prize in physics',
			    'when is the next deadpool movie being released',
			    'which mode is used for short wave broadcast service',
			    'who is the owner of reading football club',
			    'when is the next scandal episode coming out',
			    'when is the last time the philadelphia won the superbowl',
			    'what is the most current adobe flash player version',
			    'how many episodes are there in dragon ball z',
			    'what is the first step in the evolution of the eye',
			    'where is gall bladder situated in human body',
			    'what is the main mineral in lithium batteries',
			    'who is the president of usa right now',
			    'where do the greasers live in the outsiders',
			    'panda is a national animal of which country',
			    'what is the name of manchester united stadium',
			]
			__magic_name__	:   Union[str, Any]					     =					tokenizer(_A      )
			self.assertIsNotNone(_A      )



'''simple docstring'''

from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

lowerCAmelCase				:Any        =      TypeVar('''T''')





def lowerCamelCase      (      lowerCAmelCase    :     int		):





	"""simple docstring"""







	return (position - 1) // 2





def lowerCamelCase      (      lowerCAmelCase    :     int		):





	"""simple docstring"""







	return (2 * position) + 1





def lowerCamelCase      (      lowerCAmelCase    :     int		):





	"""simple docstring"""







	return (2 * position) + 2
class _lowerCamelCase	(						Generic[T]							):



		'''simple docstring'''







		def __init__( self		:						Union[str, Any]      )  ->			None:
			__magic_name__	:   list[tuple[T, int]]					     =					[]
			__magic_name__	:   dict[T, int]					     =					{}
			__magic_name__	:   int					     =					0







		def __len__( self		:						Optional[int]      )  ->			int:
			return self.elements







		def __repr__( self		:						Optional[Any]      )  ->			str:
			return str(self.heap      )







		def        __lowerCAmelCase		( self		:						List[Any]      )  ->			bool:
			# Check if the priority queue is empty
			return self.elements == 0







		def        __lowerCAmelCase		( self		:						Dict  ,					_A		:						T  ,					_A		:						int      )  ->			None:
			# Add an element with given priority to the queue
			self.heap.append((elem, weight)      )
			__magic_name__	:   List[str]					     =					self.elements
			self.elements += 1
			self._bubble_up(_A      )







		def        __lowerCAmelCase		( self		:						List[Any]      )  ->			T:
			# Remove and return the element with lowest weight (highest priority)
			if self.elements > 1:
				self._swap_nodes(0  ,					self.elements - 1      )
			__magic_name__     ,    __magic_name__	:   Optional[Any]					     =					self.heap.pop()
			del self.position_map[elem]
			self.elements -= 1
			if self.elements > 0:
				__magic_name__     ,    __magic_name__	:   Tuple					     =					self.heap[0]
				self._bubble_down(_A      )
			return elem







		def        __lowerCAmelCase		( self		:						Dict  ,					_A		:						T  ,					_A		:						int      )  ->			None:
			# Update the weight of the given key
			__magic_name__	:   Optional[Any]					     =					self.position_map[elem]
			__magic_name__	:   Any					     =					(elem, weight)
			if position > 0:
				__magic_name__	:   Optional[int]					     =					get_parent_position(_A      )
				__magic_name__     ,    __magic_name__	:   Any					     =					self.heap[parent_position]
				if parent_weight > weight:
					self._bubble_up(_A      )
				else:
					self._bubble_down(_A      )
			else:
				self._bubble_down(_A      )







		def        __lowerCAmelCase		( self		:						Optional[int]  ,					_A		:						T      )  ->			None:
			# Place a node at the proper position (upward movement) [to be used internally
			# only]
			__magic_name__	:   Union[str, Any]					     =					self.position_map[elem]
			if curr_pos == 0:
				return None
			__magic_name__	:   Optional[Any]					     =					get_parent_position(_A      )
			__magic_name__     ,    __magic_name__	:   Any					     =					self.heap[curr_pos]
			__magic_name__     ,    __magic_name__	:   int					     =					self.heap[parent_position]
			if parent_weight > weight:
				self._swap_nodes(_A  ,					_A      )
				return self._bubble_up(_A      )
			return None







		def        __lowerCAmelCase		( self		:						int  ,					_A		:						T      )  ->			None:
			# Place a node at the proper position (downward movement) [to be used
			# internally only]
			__magic_name__	:   Dict					     =					self.position_map[elem]
			__magic_name__     ,    __magic_name__	:   List[str]					     =					self.heap[curr_pos]
			__magic_name__	:   str					     =					get_child_left_position(_A      )
			__magic_name__	:   List[str]					     =					get_child_right_position(_A      )
			if child_left_position < self.elements and child_right_position < self.elements:
				__magic_name__     ,    __magic_name__	:   int					     =					self.heap[child_left_position]
				__magic_name__     ,    __magic_name__	:   int					     =					self.heap[child_right_position]
				if child_right_weight < child_left_weight and child_right_weight < weight:
					self._swap_nodes(_A  ,					_A      )
					return self._bubble_down(_A      )
			if child_left_position < self.elements:
				__magic_name__     ,    __magic_name__	:   Any					     =					self.heap[child_left_position]
				if child_left_weight < weight:
					self._swap_nodes(_A  ,					_A      )
					return self._bubble_down(_A      )
			else:
				return None
			if child_right_position < self.elements:
				__magic_name__     ,    __magic_name__	:   str					     =					self.heap[child_right_position]
				if child_right_weight < weight:
					self._swap_nodes(_A  ,					_A      )
					return self._bubble_down(_A      )
			return None







		def        __lowerCAmelCase		( self		:						int  ,					_A		:						int  ,					_A		:						int      )  ->			None:
			# Swap the nodes at the given positions
			__magic_name__	:   List[Any]					     =					self.heap[nodea_pos][0]
			__magic_name__	:   Union[str, Any]					     =					self.heap[nodea_pos][0]
			__magic_name__     ,    __magic_name__	:   Optional[Any]					     =					(
			    self.heap[nodea_pos],
			    self.heap[nodea_pos],
			)
			__magic_name__	:   Optional[Any]					     =					nodea_pos
			__magic_name__	:   Optional[Any]					     =					nodea_pos







class _lowerCamelCase	(						Generic[T]							):



		'''simple docstring'''







		def __init__( self		:						Union[str, Any]      )  ->			None:
			__magic_name__	:   dict[T, dict[T, int]]					     =					{}
			__magic_name__	:   int					     =					0







		def __repr__( self		:						str      )  ->			str:
			return str(self.connections      )







		def __len__( self		:						Union[str, Any]      )  ->			int:
			return self.nodes







		def        __lowerCAmelCase		( self		:						Dict  ,					_A		:						T      )  ->			None:
			# Add a node in the graph if it is not in the graph
			if node not in self.connections:
				__magic_name__	:   str					     =					{}
				self.nodes += 1







		def        __lowerCAmelCase		( self		:						List[str]  ,					_A		:						T  ,					_A		:						T  ,					_A		:						int      )  ->			None:
			# Add an edge between 2 nodes in the graph
			self.add_node(_A      )
			self.add_node(_A      )
			__magic_name__	:   Any					     =					weight
			__magic_name__	:   Dict					     =					weight







def lowerCamelCase      (      lowerCAmelCase    :     GraphUndirectedWeighted[T]		,		):





	"""simple docstring"""







	__magic_name__	:   dict[T, int]					     =					{node: maxsize for node in graph.connections}
	__magic_name__	:   dict[T, T | None]					     =					{node: None for node in graph.connections}

	__magic_name__	:   MinPriorityQueue[T]					     =					MinPriorityQueue()
	for node, weight in dist.items():
		priority_queue.push(lowerCAmelCase		,		lowerCAmelCase		)

	if priority_queue.is_empty():
		return dist, parent

	# initialization
	__magic_name__	:   Any					     =					priority_queue.extract_min()
	__magic_name__	:   List[str]					     =					0
	for neighbour in graph.connections[node]:
		if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
			__magic_name__	:   Any					     =					dist[node] + graph.connections[node][neighbour]
			priority_queue.update_key(lowerCAmelCase		,		dist[neighbour]		)
			__magic_name__	:   Tuple					     =					node

    # running prim's algorithm
	while not priority_queue.is_empty():
		__magic_name__	:   Tuple					     =					priority_queue.extract_min()
		for neighbour in graph.connections[node]:
			if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
				__magic_name__	:   int					     =					dist[node] + graph.connections[node][neighbour]
				priority_queue.update_key(lowerCAmelCase		,		dist[neighbour]		)
				__magic_name__	:   Union[str, Any]					     =					node
	return dist, parent