



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    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):





							def 						UpperCamelCase_					(   self		:		Any	):

											'''simple docstring'''
											__a       =		tempfile.mkdtemp()
											__a       =		5

											# Realm tok
											__a       =		[
											    """[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""",
											]
											__a       =		os.path.join(self.tmpdirname      ,				"""realm_tokenizer"""	)
											os.makedirs(__lowercase      ,				exist_ok=__lowercase	)
											__a       =		os.path.join(__lowercase      ,				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]	)	)

											__a       =		os.path.join(self.tmpdirname      ,				"""realm_block_records"""	)
											os.makedirs(__lowercase      ,				exist_ok=__lowercase	)





							def 						UpperCamelCase_					(   self		:		Any	):

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





							def 						UpperCamelCase_					(   self		:		Tuple	):

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





							def 						UpperCamelCase_					(   self		:		Union[str, Any]	):

											'''simple docstring'''
											__a       =		RealmConfig(num_block_records=self.num_block_records	)
											return config





							def 						UpperCamelCase_					(   self		:		int	):

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





							def 						UpperCamelCase_					(   self		:		Tuple	):

											'''simple docstring'''
											__a       =		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=__lowercase      ,				)
											return block_records





							def 						UpperCamelCase_					(   self		:		str	):

											'''simple docstring'''
											__a       =		RealmRetriever(
											    block_records=self.get_dummy_block_records()      ,				tokenizer=self.get_tokenizer()      ,				)
											return retriever





							def 						UpperCamelCase_					(   self		:		str	):

											'''simple docstring'''
											__a       =		self.get_config()
											__a       =		self.get_dummy_retriever()
											__a       =		retriever.tokenizer

											__a       =		np.array([0, 3]      ,				dtype="""long"""	)
											__a       =		tokenizer(["""Test question"""]	).input_ids
											__a       =		tokenizer(
											    ["""the fourth"""]      ,				add_special_tokens=__lowercase      ,				return_token_type_ids=__lowercase      ,				return_attention_mask=__lowercase      ,				).input_ids
											__a       =		config.reader_seq_len

											__a     ,					__a     ,					__a     ,					__a       =		retriever(
											    __lowercase      ,				__lowercase      ,				answer_ids=__lowercase      ,				max_length=__lowercase      ,				return_tensors="""np"""	)

											self.assertEqual(len(__lowercase	)      ,				2	)
											self.assertEqual(len(__lowercase	)      ,				2	)
											self.assertEqual(len(__lowercase	)      ,				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 						UpperCamelCase_					(   self		:		Optional[int]	):

											'''simple docstring'''
											__a       =		self.get_config()
											__a       =		self.get_dummy_retriever()
											__a       =		retriever.tokenizer

											__a       =		np.array([0, 3, 5]      ,				dtype="""long"""	)
											__a       =		tokenizer(["""Test question"""]	).input_ids
											__a       =		tokenizer(
											    ["""the fourth""", """longer longer"""]      ,				add_special_tokens=__lowercase      ,				return_token_type_ids=__lowercase      ,				return_attention_mask=__lowercase      ,				).input_ids
											__a       =		config.reader_seq_len

											__a     ,					__a     ,					__a     ,					__a       =		retriever(
											    __lowercase      ,				__lowercase      ,				answer_ids=__lowercase      ,				max_length=__lowercase      ,				return_tensors="""np"""	)

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







							def 						UpperCamelCase_					(   self		:		str	):

											'''simple docstring'''
											__a       =		self.get_dummy_retriever()
											retriever.save_pretrained(os.path.join(self.tmpdirname      ,				"""realm_block_records"""	)	)

											# Test local path
											__a       =		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:
															__a       =		os.path.join(
															    os.path.join(self.tmpdirname      ,				"""realm_block_records"""	)      ,				_REALM_BLOCK_RECORDS_FILENAME	)
															__a       =		RealmRetriever.from_pretrained("""google/realm-cc-news-pretrained-openqa"""	)

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





def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			list				,     _SCREAMING_SNAKE_CASE       :			list				,     _SCREAMING_SNAKE_CASE       :			int				,     _SCREAMING_SNAKE_CASE       :			int				,     _SCREAMING_SNAKE_CASE       :			int    ):
				"""simple docstring"""







				if index == number_of_items:
								return 0
				__a       =		0
				__a       =		0
				__a       =		knapsack(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     index + 1    )
				if weights[index] <= max_weight:
								__a       =		values[index] + knapsack(
								    _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     max_weight - weights[index]				,     index + 1    )
				return max(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE    )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
