





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 						snake_case__				(							self  )       -> Optional[Any]:






									"""simple docstring"""
									lowercase_	:   Optional[int]  				=     tempfile.mkdtemp()
									lowercase_	:   Union[str, Any]  				=     5

									# Realm tok
									lowercase_	:   Dict  				=     [
									    '''[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''',
									]
									lowercase_	:   List[Any]  				=     os.path.join(self.tmpdirname,   """realm_tokenizer"""  )
									os.makedirs(UpperCamelCase__,   exist_ok=UpperCamelCase__  )
									lowercase_	:   int  				=     os.path.join(UpperCamelCase__,   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]  )  )

									lowercase_	:   List[Any]  				=     os.path.join(self.tmpdirname,   """realm_block_records"""  )
									os.makedirs(UpperCamelCase__,   exist_ok=UpperCamelCase__  )






		def 						snake_case__				(							self  )       -> RealmTokenizer:






									"""simple docstring"""
									return RealmTokenizer.from_pretrained(os.path.join(self.tmpdirname,   """realm_tokenizer"""  )  )






		def 						snake_case__				(							self  )       -> Optional[int]:






									"""simple docstring"""
									shutil.rmtree(self.tmpdirname  )






		def 						snake_case__				(							self  )       -> List[str]:






									"""simple docstring"""
									lowercase_	:   Dict  				=     RealmConfig(num_block_records=self.num_block_records  )
									return config






		def 						snake_case__				(							self  )       -> List[Any]:






									"""simple docstring"""
									lowercase_	:   Optional[int]  				=     Dataset.from_dict(
									    {
									        """id""": ["""0""", """1"""],
									        """question""": ["""foo""", """bar"""],
									        """answers""": [["""Foo""", """Bar"""], ["""Bar"""]],
									    }  )
									return dataset






		def 						snake_case__				(							self  )       -> Tuple:






									"""simple docstring"""
									lowercase_	:   Dict  				=     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=UpperCamelCase__,   )
									return block_records






		def 						snake_case__				(							self  )       -> Optional[Any]:






									"""simple docstring"""
									lowercase_	:   List[Any]  				=     RealmRetriever(
									    block_records=self.get_dummy_block_records(),   tokenizer=self.get_tokenizer(),   )
									return retriever






		def 						snake_case__				(							self  )       -> Any:






									"""simple docstring"""
									lowercase_	:   Tuple  				=     self.get_config()
									lowercase_	:   Union[str, Any]  				=     self.get_dummy_retriever()
									lowercase_	:   int  				=     retriever.tokenizer

									lowercase_	:   List[str]  				=     np.array([0, 3],   dtype="""long"""  )
									lowercase_	:   Optional[int]  				=     tokenizer(["""Test question"""]  ).input_ids
									lowercase_	:   Dict  				=     tokenizer(
									    ["""the fourth"""],   add_special_tokens=UpperCamelCase__,   return_token_type_ids=UpperCamelCase__,   return_attention_mask=UpperCamelCase__,   ).input_ids
									lowercase_	:   int  				=     config.reader_seq_len

									lowercase_	:   List[Any]  				=     retriever(
									    UpperCamelCase__,   UpperCamelCase__,   answer_ids=UpperCamelCase__,   max_length=UpperCamelCase__,   return_tensors="""np"""  )

									self.assertEqual(len(UpperCamelCase__  ),   2  )
									self.assertEqual(len(UpperCamelCase__  ),   2  )
									self.assertEqual(len(UpperCamelCase__  ),   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 						snake_case__				(							self  )       -> Optional[Any]:






									"""simple docstring"""
									lowercase_	:   List[str]  				=     self.get_config()
									lowercase_	:   Any  				=     self.get_dummy_retriever()
									lowercase_	:   Union[str, Any]  				=     retriever.tokenizer

									lowercase_	:   Tuple  				=     np.array([0, 3, 5],   dtype="""long"""  )
									lowercase_	:   Union[str, Any]  				=     tokenizer(["""Test question"""]  ).input_ids
									lowercase_	:   Tuple  				=     tokenizer(
									    ["""the fourth""", """longer longer"""],   add_special_tokens=UpperCamelCase__,   return_token_type_ids=UpperCamelCase__,   return_attention_mask=UpperCamelCase__,   ).input_ids
									lowercase_	:   int  				=     config.reader_seq_len

									lowercase_	:   Optional[Any]  				=     retriever(
									    UpperCamelCase__,   UpperCamelCase__,   answer_ids=UpperCamelCase__,   max_length=UpperCamelCase__,   return_tensors="""np"""  )

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






		def 						snake_case__				(							self  )       -> Tuple:






									"""simple docstring"""
									lowercase_	:   Dict  				=     self.get_dummy_retriever()
									retriever.save_pretrained(os.path.join(self.tmpdirname,   """realm_block_records"""  )  )

									# Test local path
									lowercase_	:   int  				=     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:
																lowercase_	:   str  				=     os.path.join(
																    os.path.join(self.tmpdirname,   """realm_block_records"""  ),   _REALM_BLOCK_RECORDS_FILENAME  )
																lowercase_	:   Union[str, Any]  				=     RealmRetriever.from_pretrained("""google/realm-cc-news-pretrained-openqa"""  )

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

'''simple docstring'''
from __future__ import annotations

from collections.abc import Callable
from typing import Any, Generic, TypeVar

lowercase__						       =      TypeVar("T")






class 	snake_case__       (      Generic[T]					):







		"""simple docstring"""

		def __init__(      self				:			str  ,	UpperCamelCase__				:			list[T]  ,	UpperCamelCase__				:			Callable[[T, T], T]      )						->			None:






				"""simple docstring"""







				snake_case  :       Any | T     			=						None

				snake_case  :       int     			=						len(UpperCamelCase__      )
				snake_case  :       list[T]     			=						[any_type for _ in range(self.N      )] + arr
				snake_case  :       Optional[int]     			=						fnc
				self.build()



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






				"""simple docstring"""







				for p in range(self.N - 1  ,	0  ,	-1      ):
						snake_case  :       List[Any]     			=						self.fn(self.st[p * 2]  ,	self.st[p * 2 + 1]      )



		def       lowerCAmelCase				(      self				:			List[Any]  ,	UpperCamelCase__				:			int  ,	UpperCamelCase__				:			T      )						->			None:






				"""simple docstring"""







				p += self.N
				snake_case  :       int     			=						v
				while p > 1:
						snake_case  :       List[Any]     			=						p // 2
						snake_case  :       List[Any]     			=						self.fn(self.st[p * 2]  ,	self.st[p * 2 + 1]      )



		def       lowerCAmelCase				(      self				:			Union[str, Any]  ,	UpperCamelCase__				:			int  ,	UpperCamelCase__				:			int      )						->			T | None:  # noqa: E741






				"""simple docstring"""







				snake_case			,snake_case  :       Union[str, Any]     			=						l + self.N, r + self.N

				snake_case  :       T | None     			=						None
				while l <= r:
						if l % 2 == 1:
								snake_case  :       str     			=						self.st[l] if res is None else self.fn(UpperCamelCase__  ,	self.st[l]      )
						if r % 2 == 0:
								snake_case  :       Tuple     			=						self.st[r] if res is None else self.fn(UpperCamelCase__  ,	self.st[r]      )
						snake_case			,snake_case  :       Dict     			=						(l + 1) // 2, (r - 1) // 2
				return res


if __name__ == "__main__":
						from functools import reduce

						lowercase__						       =      [1, 1_0, -2, 9, -3, 8, 4, -7, 5, 6, 1_1, -1_2]

						lowercase__						       =      {
						    0: 7,
						    1: 2,
						    2: 6,
						    3: -1_4,
						    4: 5,
						    5: 4,
						    6: 7,
						    7: -1_0,
						    8: 9,
						    9: 1_0,
						    1_0: 1_2,
						    1_1: 1,
						}

						lowercase__						       =      SegmentTree(test_array, min)
						lowercase__						       =      SegmentTree(test_array, max)
						lowercase__						       =      SegmentTree(test_array, lambda a, b: a + b)




						def    _UpperCamelCase						(       )  ->							None:


								'''simple docstring'''


								for i in range(len(SCREAMING_SNAKE_CASE__			)			):
										for j in range(SCREAMING_SNAKE_CASE__ ,       len(SCREAMING_SNAKE_CASE__			)			):
												snake_case  :       int     			=						reduce(SCREAMING_SNAKE_CASE__ ,       test_array[i : j + 1]			)
												snake_case  :       List[str]     			=						reduce(SCREAMING_SNAKE_CASE__ ,       test_array[i : j + 1]			)
												snake_case  :       Tuple     			=						reduce(lambda SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__			: a + b ,       test_array[i : j + 1]			)
												assert min_range == min_segment_tree.query(SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__			)
												assert max_range == max_segment_tree.query(SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__			)
												assert sum_range == sum_segment_tree.query(SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__			)

						test_all_segments()

						for index, value in test_updates.items():
												lowercase__						       =      value
												min_segment_tree.update(index, value)
												max_segment_tree.update(index, value)
												sum_segment_tree.update(index, value)
												test_all_segments()


