






'''simple docstring'''



from __future__ import annotations

from random import random
class UpperCAmelCase_       :




      """simple docstring"""




      def __init__(			self      :		Dict  ,   UpperCAmelCase      :		int | None = None		)	->	Union[str, Any]:


       '''simple docstring'''

       lowercase       : str						=value
       lowercase       : Tuple						=random()
       lowercase       : Node | None						=None
       lowercase       : Node | None						=None






      def __repr__(			self      :		Tuple		)	->	str:


       '''simple docstring'''

       from pprint import pformat

       if self.left is None and self.right is None:
        return f'\'{self.value}: {self.prior:.5}\''
       else:
        return pformat(
            {f'{self.value}: {self.prior:.5}': (self.left, self.right)}  ,   indent=1		)






      def __str__(			self      :		Tuple		)	->	str:


       '''simple docstring'''

       lowercase       : Dict						=str(self.value		) + ''' '''
       lowercase       : Optional[Any]						=str(self.left or ''''''		)
       lowercase       : int						=str(self.right or ''''''		)
       return value + left + right





def 				lowercase_					(     __A			:							Node | None       ,   __A			:							int      )							->   tuple[Node | None, Node | None]:



 """simple docstring"""




 if root is None:  # None tree is split into 2 Nones
  return None, None
 elif root.value is None:
  return None, None
 else:
  if value < root.value:
   lowercase	,		lowercase       : Optional[Any]						=split(root.left       ,   __A      )
   return left, root
  else:
   lowercase	,		lowercase       : List[str]						=split(root.right       ,   __A      )
   return root, right


def 				lowercase_					(     __A			:							Node | None       ,   __A			:							Node | None      )							->   Node | None:



 """simple docstring"""




 if (not left) or (not right):  # If one node is None, return the other
  return left or right
 elif left.prior < right.prior:
  lowercase       : Union[str, Any]						=merge(left.right       ,   __A      )
  return left
 else:
  lowercase       : Union[str, Any]						=merge(__A       ,   right.left      )
  return right


def 				lowercase_					(     __A			:							Node | None       ,   __A			:							int      )							->   Node | None:



 """simple docstring"""




 lowercase       : Union[str, Any]						=Node(__A      )
 lowercase	,		lowercase       : Union[str, Any]						=split(__A       ,   __A      )
 return merge(merge(__A       ,   __A      )       ,   __A      )


def 				lowercase_					(     __A			:							Node | None       ,   __A			:							int      )							->   Node | None:



 """simple docstring"""




 lowercase	,		lowercase       : str						=split(__A       ,   value - 1      )
 lowercase	,		lowercase       : Optional[Any]						=split(__A       ,   __A      )
 return merge(__A       ,   __A      )


def 				lowercase_					(     __A			:							Node | None      )							->   None:



 """simple docstring"""




 if not root:  # None
  return
 else:
  inorder(root.left      )
  print(root.value       ,   end=''','''      )
  inorder(root.right      )


def 				lowercase_					(     __A			:							Node | None       ,   __A			:							str      )							->   Node | None:



 """simple docstring"""




 for arg in args.split():
  if arg[0] == "+":
   lowercase       : Tuple						=insert(__A       ,   int(arg[1:]      )      )

  elif arg[0] == "-":
   lowercase       : Optional[int]						=erase(__A       ,   int(arg[1:]      )      )

  else:
   print('''Unknown command'''      )

 return root


def 				lowercase_					(     )							->   None:



 """simple docstring"""




 lowercase       : List[Any]						=None
 print(
     '''enter numbers to create a tree, + value to add value into treap, '''
     '''- value to erase all nodes with value. \'q\' to quit. '''      )

 lowercase       : Optional[int]						=input()
 while args != "q":
  lowercase       : Tuple						=interact_treap(__A       ,   __A      )
  print(__A      )
  lowercase       : List[str]						=input()

 print('''good by!'''      )


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()







'''simple docstring'''







import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
from datasets import Dataset

from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRetriever
from transformers.models.realm.tokenization_realm import VOCAB_FILES_NAMES, RealmTokenizer
class 						UpperCamelCase__       (			SCREAMING_SNAKE_CASE_						):



     """simple docstring"""






     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Dict       =							tempfile.mkdtemp()
            _lowerCAmelCase     :				List[str]       =							5

            # Realm tok
            _lowerCAmelCase     :				str       =							[
                '[UNK]',
                '[CLS]',
                '[SEP]',
                '[PAD]',
                '[MASK]',
                'test',
                'question',
                'this',
                'is',
                'the',
                'first',
                'second',
                'third',
                'fourth',
                'fifth',
                'record',
                'want',
                '##want',
                '##ed',
                'wa',
                'un',
                'runn',
                '##ing',
                ',',
                'low',
                'lowest',
            ]
            _lowerCAmelCase     :				Union[str, Any]       =							os.path.join(self.tmpdirname   ,						'realm_tokenizer' )
            os.makedirs(snake_case__   ,						exist_ok=snake_case__ )
            _lowerCAmelCase     :				Dict       =							os.path.join(snake_case__   ,						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] ) )

            _lowerCAmelCase     :				List[str]       =							os.path.join(self.tmpdirname   ,						'realm_block_records' )
            os.makedirs(snake_case__   ,						exist_ok=snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            return RealmTokenizer.from_pretrained(os.path.join(self.tmpdirname   ,						'realm_tokenizer' ) )







     def a						(			self ):

            '''simple docstring'''

            shutil.rmtree(self.tmpdirname )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Dict       =							RealmConfig(num_block_records=self.num_block_records )
            return config







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[Any]       =							Dataset.from_dict(
                {
                    'id': ['0', '1'],
                    'question': ['foo', 'bar'],
                    'answers': [['Foo', 'Bar'], ['Bar']],
                } )
            return dataset







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				str       =							np.array(
                [
                    b'This is the first record',
                    b'This is the second record',
                    b'This is the third record',
                    b'This is the fourth record',
                    b'This is the fifth record',
                    b'This is a longer longer longer record',
                ]   ,						dtype=snake_case__   ,						)
            return block_records







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Tuple       =							RealmRetriever(
                block_records=self.get_dummy_block_records()   ,						tokenizer=self.get_tokenizer()   ,						)
            return retriever







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Optional[int]       =							self.get_config()
            _lowerCAmelCase     :				List[Any]       =							self.get_dummy_retriever()
            _lowerCAmelCase     :				Any       =							retriever.tokenizer

            _lowerCAmelCase     :				Tuple       =							np.array([0, 3]   ,						dtype='long' )
            _lowerCAmelCase     :				Dict       =							tokenizer(['Test question'] ).input_ids
            _lowerCAmelCase     :				int       =							tokenizer(
                ['the fourth']   ,						add_special_tokens=snake_case__   ,						return_token_type_ids=snake_case__   ,						return_attention_mask=snake_case__   ,						).input_ids
            _lowerCAmelCase     :				Tuple       =							config.reader_seq_len

            _lowerCAmelCase      ,  _lowerCAmelCase      ,  _lowerCAmelCase      ,  _lowerCAmelCase     :				Union[str, Any]       =							retriever(
                snake_case__   ,						snake_case__   ,						answer_ids=snake_case__   ,						max_length=snake_case__   ,						return_tensors='np' )

            self.assertEqual(len(snake_case__ )   ,						2 )
            self.assertEqual(len(snake_case__ )   ,						2 )
            self.assertEqual(len(snake_case__ )   ,						2 )
            self.assertEqual(concat_inputs.input_ids.shape   ,						(2, 10) )
            self.assertEqual(concat_inputs.attention_mask.shape   ,						(2, 10) )
            self.assertEqual(concat_inputs.token_type_ids.shape   ,						(2, 10) )
            self.assertEqual(concat_inputs.special_tokens_mask.shape   ,						(2, 10) )
            self.assertEqual(
                tokenizer.convert_ids_to_tokens(concat_inputs.input_ids[0] )   ,						['[CLS]', 'test', 'question', '[SEP]', 'this', 'is', 'the', 'first', 'record', '[SEP]']   ,						)
            self.assertEqual(
                tokenizer.convert_ids_to_tokens(concat_inputs.input_ids[1] )   ,						['[CLS]', 'test', 'question', '[SEP]', 'this', 'is', 'the', 'fourth', 'record', '[SEP]']   ,						)







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				int       =							self.get_config()
            _lowerCAmelCase     :				int       =							self.get_dummy_retriever()
            _lowerCAmelCase     :				List[str]       =							retriever.tokenizer

            _lowerCAmelCase     :				List[Any]       =							np.array([0, 3, 5]   ,						dtype='long' )
            _lowerCAmelCase     :				str       =							tokenizer(['Test question'] ).input_ids
            _lowerCAmelCase     :				Union[str, Any]       =							tokenizer(
                ['the fourth', 'longer longer']   ,						add_special_tokens=snake_case__   ,						return_token_type_ids=snake_case__   ,						return_attention_mask=snake_case__   ,						).input_ids
            _lowerCAmelCase     :				Optional[int]       =							config.reader_seq_len

            _lowerCAmelCase      ,  _lowerCAmelCase      ,  _lowerCAmelCase      ,  _lowerCAmelCase     :				List[str]       =							retriever(
                snake_case__   ,						snake_case__   ,						answer_ids=snake_case__   ,						max_length=snake_case__   ,						return_tensors='np' )

            self.assertEqual([False, True, True]   ,						snake_case__ )
            self.assertEqual([[-1, -1, -1], [6, -1, -1], [6, 7, 8]]   ,						snake_case__ )
            self.assertEqual([[-1, -1, -1], [7, -1, -1], [7, 8, 9]]   ,						snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[str]       =							self.get_dummy_retriever()
            retriever.save_pretrained(os.path.join(self.tmpdirname   ,						'realm_block_records' ) )

            # Test local path
            _lowerCAmelCase     :				Union[str, Any]       =							retriever.from_pretrained(os.path.join(self.tmpdirname   ,						'realm_block_records' ) )
            self.assertEqual(retriever.block_records[0]   ,						b'This is the first record' )

            # Test mocked remote path
            with patch('transformers.models.realm.retrieval_realm.hf_hub_download' ) as mock_hf_hub_download:
                   _lowerCAmelCase     :				Any       =							os.path.join(
                       os.path.join(self.tmpdirname   ,						'realm_block_records' )   ,						_REALM_BLOCK_RECORDS_FILENAME )
                   _lowerCAmelCase     :				str       =							RealmRetriever.from_pretrained('google/realm-cc-news-pretrained-openqa' )

            self.assertEqual(retriever.block_records[0]   ,						b'This is the first record' )

