


lowerCAmelCase__			:      List[Any]								='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

lowerCAmelCase__			:      List[Any]								=[{'type': 'code', 'content': INSTALL_CONTENT}]
lowerCAmelCase__			:      str								={
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}









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 	__lowercase    (__SCREAMING_SNAKE_CASE  ):





							"""simple docstring"""







							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Tuple					=					tempfile.mkdtemp()
										SCREAMING_SNAKE_CASE_		:     Dict					=					5

										# Realm tok
										SCREAMING_SNAKE_CASE_		:     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',
										]
										SCREAMING_SNAKE_CASE_		:     Tuple					=					os.path.join(self.tmpdirname			,						'realm_tokenizer'       )
										os.makedirs(lowerCAmelCase__			,						exist_ok=lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     Tuple					=					os.path.join(lowerCAmelCase__			,						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]       )       )

										SCREAMING_SNAKE_CASE_		:     str					=					os.path.join(self.tmpdirname			,						'realm_block_records'       )
										os.makedirs(lowerCAmelCase__			,						exist_ok=lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




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






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										shutil.rmtree(self.tmpdirname       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					RealmConfig(num_block_records=self.num_block_records       )
										return config






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




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






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     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=lowerCAmelCase__			,						)
										return block_records






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Any					=					RealmRetriever(
										    block_records=self.get_dummy_block_records()			,						tokenizer=self.get_tokenizer()			,						)
										return retriever






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Any					=					self.get_config()
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					self.get_dummy_retriever()
										SCREAMING_SNAKE_CASE_		:     List[str]					=					retriever.tokenizer

										SCREAMING_SNAKE_CASE_		:     Any					=					np.array([0, 3]			,						dtype='long'       )
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					tokenizer(['Test question']       ).input_ids
										SCREAMING_SNAKE_CASE_		:     int					=					tokenizer(
										    ['the fourth']			,						add_special_tokens=lowerCAmelCase__			,						return_token_type_ids=lowerCAmelCase__			,						return_attention_mask=lowerCAmelCase__			,						).input_ids
										SCREAMING_SNAKE_CASE_		:     Any					=					config.reader_seq_len

										SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_		:     str					=					retriever(
										    lowerCAmelCase__			,						lowerCAmelCase__			,						answer_ids=lowerCAmelCase__			,						max_length=lowerCAmelCase__			,						return_tensors='np'       )

										self.assertEqual(len(lowerCAmelCase__       )			,						2       )
										self.assertEqual(len(lowerCAmelCase__       )			,						2       )
										self.assertEqual(len(lowerCAmelCase__       )			,						2       )
										self.assertEqual(concat_inputs.input_ids.shape			,						(2, 1_0)       )
										self.assertEqual(concat_inputs.attention_mask.shape			,						(2, 1_0)       )
										self.assertEqual(concat_inputs.token_type_ids.shape			,						(2, 1_0)       )
										self.assertEqual(concat_inputs.special_tokens_mask.shape			,						(2, 1_0)       )
										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       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Dict					=					self.get_config()
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					self.get_dummy_retriever()
										SCREAMING_SNAKE_CASE_		:     Tuple					=					retriever.tokenizer

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

										SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_		:     Tuple					=					retriever(
										    lowerCAmelCase__			,						lowerCAmelCase__			,						answer_ids=lowerCAmelCase__			,						max_length=lowerCAmelCase__			,						return_tensors='np'       )

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






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Dict					=					self.get_dummy_retriever()
										retriever.save_pretrained(os.path.join(self.tmpdirname			,						'realm_block_records'       )       )

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

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





