


'''simple docstring'''

import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional

import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset

from transformers import DPRContextEncoder, DPRContextEncoderTokenizerFast, HfArgumentParser


lowerCamelCase							:   Dict  						=	logging.getLogger(__name__)
torch.set_grad_enabled(False)
lowerCamelCase							:   List[Any]  						=	'cuda' if torch.cuda.is_available() else 'cpu'

def _SCREAMING_SNAKE_CASE      (A  , A=100  , A=" "       )       ->       List[str]:






       """simple docstring"""







       lowercase__      			= text.split(A       )
       return [character.join(text[i : i + n]       ).strip() for i in range(0  , len(A       )  , A       )]

def _SCREAMING_SNAKE_CASE      (A       )       ->       dict:






       """simple docstring"""







       lowercase__			,lowercase__      			= [], []
       for title, text in zip(documents['''title''']  , documents['''text''']       ):
              if text is not None:
                     for passage in split_text(A       ):
                            titles.append(title if title is not None else ''''''       )
                            texts.append(A       )
       return {"title": titles, "text": texts}

def _SCREAMING_SNAKE_CASE      (A  , A  , A       )       ->       dict:






       """simple docstring"""







       lowercase__      			= ctx_tokenizer(
           documents['''title''']  , documents['''text''']  , truncation=A  , padding='''longest'''  , return_tensors='''pt'''       )['''input_ids''']
       lowercase__      			= ctx_encoder(input_ids.to(device=A       )  , return_dict=A       ).pooler_output
       return {"embeddings": embeddings.detach().cpu().numpy()}

def _SCREAMING_SNAKE_CASE      (A  , A  , A  , )       ->       List[str]:






       """simple docstring"""







       logger.info('''Step 1 - Create the dataset'''       )
       ######################################

       # The dataset needed for RAG must have three columns:
       # - title (string): title of the document
       # - text (string): text of a passage of the document
       # - embeddings (array of dimension d): DPR representation of the passage
       # Let's say you have documents in tab-separated csv files with columns "title" and "text"
       assert os.path.isfile(rag_example_args.csv_path       ), "Please provide a valid path to a csv file"

       # You can load a Dataset object this way
       lowercase__      			= load_dataset(
           '''csv'''  , data_files=[rag_example_args.csv_path]  , split='''train'''  , delimiter='''\t'''  , column_names=['''title''', '''text''']       )

       # More info about loading csv files in the documentation: https://huggingface.co/docs/datasets/loading_datasets.html?highlight=csv#csv-files

       # Then split the documents into passages of 100 words
       lowercase__      			= dataset.map(A  , batched=A  , num_proc=processing_args.num_proc       )

       # And compute the embeddings
       lowercase__      			= DPRContextEncoder.from_pretrained(rag_example_args.dpr_ctx_encoder_model_name       ).to(device=A       )
       lowercase__      			= DPRContextEncoderTokenizerFast.from_pretrained(rag_example_args.dpr_ctx_encoder_model_name       )
       lowercase__      			= Features(
           {'''text''': Value('''string'''       ), '''title''': Value('''string'''       ), '''embeddings''': Sequence(Value('''float32'''       )       )}       )  # optional, save as float32 instead of float64 to save space
       lowercase__      			= dataset.map(
           partial(A  , ctx_encoder=A  , ctx_tokenizer=A       )  , batched=A  , batch_size=processing_args.batch_size  , features=A  , )

       # And finally save your dataset
       lowercase__      			= os.path.join(rag_example_args.output_dir  , '''my_knowledge_dataset'''       )
       dataset.save_to_disk(A       )
       # from datasets import load_from_disk
       # dataset = load_from_disk(passages_path)  # to reload the dataset

       ######################################
       logger.info('''Step 2 - Index the dataset'''       )
       ######################################

       # Let's use the Faiss implementation of HNSW for fast approximate nearest neighbor search
       lowercase__      			= faiss.IndexHNSWFlat(index_hnsw_args.d  , index_hnsw_args.m  , faiss.METRIC_INNER_PRODUCT       )
       dataset.add_faiss_index('''embeddings'''  , custom_index=A       )

       # And save the index
       lowercase__      			= os.path.join(rag_example_args.output_dir  , '''my_knowledge_dataset_hnsw_index.faiss'''       )
       dataset.get_index('''embeddings'''       ).save(A       )
       # dataset.load_faiss_index("embeddings", index_path)  # to reload the index
@dataclass
class   __lowerCAmelCase						:





      '''simple docstring'''






      lowerCAmelCase__					:     str  					=							field(
          default=str(Path(lowercase_     ).parent / """test_run""" / """dummy-kb""" / """my_knowledge_dataset.csv"""     )  ,     metadata={"""help""": """Path to a tab-separated csv file with columns 'title' and 'text'"""}  ,     )
      lowerCAmelCase__					:     Optional[str]  					=							field(
          default=lowercase_  ,     metadata={"""help""": """Question that is passed as input to RAG. Default is 'What does Moses' rod turn into ?'."""}  ,     )
      lowerCAmelCase__					:     str  					=							field(
          default="""facebook/rag-sequence-nq"""  ,     metadata={"""help""": """The RAG model to use. Either 'facebook/rag-sequence-nq' or 'facebook/rag-token-nq'"""}  ,     )
      lowerCAmelCase__					:     str  					=							field(
          default="""facebook/dpr-ctx_encoder-multiset-base"""  ,     metadata={
              """help""": (
                  """The DPR context encoder model to use. Either 'facebook/dpr-ctx_encoder-single-nq-base' or"""
                  """ 'facebook/dpr-ctx_encoder-multiset-base'"""
              )
          }  ,     )
      lowerCAmelCase__					:     Optional[str]  					=							field(
          default=str(Path(lowercase_     ).parent / """test_run""" / """dummy-kb"""     )  ,     metadata={"""help""": """Path to a directory where the dataset passages and the index will be saved"""}  ,     )






@dataclass
class   __lowerCAmelCase						:





      '''simple docstring'''






      lowerCAmelCase__					:     Optional[int]  					=							field(
          default=lowercase_  ,     metadata={
              """help""": """The number of processes to use to split the documents into passages. Default is single process."""
          }  ,     )
      lowerCAmelCase__					:     int  					=							field(
          default=16  ,     metadata={
              """help""": """The batch size to use when computing the passages embeddings using the DPR context encoder."""
          }  ,     )






@dataclass
class   __lowerCAmelCase						:





      '''simple docstring'''






      lowerCAmelCase__					:     int  					=							field(
          default=768  ,     metadata={"""help""": """The dimension of the embeddings to pass to the HNSW Faiss index."""}  ,     )
      lowerCAmelCase__					:     int  					=							field(
          default=128  ,     metadata={
              """help""": (
                  """The number of bi-directional links created for every new element during the HNSW index construction."""
              )
          }  ,     )


if __name__ == "__main__":
 logging.basicConfig(level=logging.WARNING)
 logger.setLevel(logging.INFO)

 lowerCamelCase							:   Optional[Any]  						=	HfArgumentParser((RagExampleArguments, ProcessingArguments, IndexHnswArguments))
 lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase							:   Union[str, Any]  						=	parser.parse_args_into_dataclasses()
 with TemporaryDirectory() as tmp_dir:
  lowerCamelCase							:   Optional[int]  						=	rag_example_args.output_dir or tmp_dir
  main(rag_example_args, processing_args, index_hnsw_args)








'''simple docstring'''

import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase							:   List[str]  						=	get_tests_dir('fixtures/spiece.model')
@require_sentencepiece
@require_tokenizers
class   __lowerCAmelCase						(lowercase_  ,     unittest.TestCase     ):





      '''simple docstring'''






      lowerCAmelCase__					:     int  					=							DebertaVaTokenizer
      lowerCAmelCase__					:     List[Any]  					=							DebertaVaTokenizerFast
      lowerCAmelCase__					:     str  					=							True
      lowerCAmelCase__					:     Tuple  					=							True



      def       UpperCamelCase__		(self    :    Tuple ):

             '''simple docstring'''







             super().setUp()

             # We have a SentencePiece fixture for testing
             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						unk_token='''<unk>''' )
             tokenizer.save_pretrained(self.tmpdirname )



      def       UpperCamelCase__		(self    :    Union[str, Any]   ,						UpperCamelCase    :    str ):

             '''simple docstring'''







             lowercase__      			= '''this is a test'''
             lowercase__      			= '''this is a test'''
             return input_text, output_text



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             lowercase__      			= '''<pad>'''
             lowercase__      			= 0

             self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCamelCase )   ,						UpperCamelCase )
             self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCamelCase )   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    Dict ):

             '''simple docstring'''







             lowercase__      			= list(self.get_tokenizer().get_vocab().keys() )
             self.assertEqual(vocab_keys[0]   ,						'''<pad>''' )
             self.assertEqual(vocab_keys[1]   ,						'''<unk>''' )
             self.assertEqual(vocab_keys[-1]   ,						'''[PAD]''' )
             self.assertEqual(len(UpperCamelCase )   ,						30001 )



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             self.assertEqual(self.get_tokenizer().vocab_size   ,						30000 )



      def       UpperCamelCase__		(self    :    Optional[Any] ):

             '''simple docstring'''







             lowercase__      			= ''' \tHeLLo!how  \n Are yoU?  '''
             lowercase__      			= ['''▁hello''', '''!''', '''how''', '''▁are''', '''▁you''', '''?''']
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						do_lower_case=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						do_lower_case=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      @unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.''' )
      def       UpperCamelCase__		(self    :    List[Any] ):

             '''simple docstring'''







             pass



      @unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.''' )
      def       UpperCamelCase__		(self    :    List[str] ):

             '''simple docstring'''







             pass



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             lowercase__      			= '''I was born in 92000, and this is falsé.'''
             lowercase__      			= ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             lowercase__      			= '''I was born in 92000, and this is falsé.'''
             lowercase__      			= ['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    Optional[Any] ):

             '''simple docstring'''







             lowercase__      			= '''I was born in 92000, and this is falsé.'''
             lowercase__      			= ['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



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

             '''simple docstring'''







             lowercase__      			= '''I was born in 92000, and this is falsé.'''
             lowercase__      			= ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



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

             '''simple docstring'''







             lowercase__      			= ''' \tHeLLo!how  \n Are yoU?  '''
             lowercase__      			= ['''▁''', '''<unk>''', '''e''', '''<unk>''', '''o''', '''!''', '''how''', '''▁''', '''<unk>''', '''re''', '''▁yo''', '''<unk>''', '''?''']
             # fmt: on

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						do_lower_case=UpperCamelCase   ,						split_by_punct=UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



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

             '''simple docstring'''







             lowercase__      			= self.get_tokenizer()
             lowercase__      			= self.get_rust_tokenizer()

             lowercase__      			= '''I was born in 92000, and this is falsé.'''

             lowercase__      			= tokenizer.convert_ids_to_tokens(tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase ) )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             lowercase__      			= rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= self.get_rust_tokenizer()
             lowercase__      			= tokenizer.encode(UpperCamelCase )
             lowercase__      			= rust_tokenizer.encode(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             lowercase__      			= '''This is a test'''
             lowercase__      			= [13, 1, 4398, 25, 21, 1289]
             lowercase__      			= ['''▁''', '''T''', '''his''', '''▁is''', '''▁a''', '''▁test''']
             lowercase__      			= ['''▁''', '''<unk>''', '''his''', '''▁is''', '''▁a''', '''▁test''']

             lowercase__      			= DebertaVaTokenizer(UpperCamelCase   ,						keep_accents=UpperCamelCase )
             lowercase__      			= DebertaVaTokenizerFast(UpperCamelCase   ,						keep_accents=UpperCamelCase )

             lowercase__      			= tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= tokenizer.tokenize(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= rust_tokenizer.tokenize(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             # fmt: off
             lowercase__      			= '''I was born in 92000, and this is falsé.'''
             lowercase__      			= [13, 1, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]
             lowercase__      			= ['''▁''', '''I''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''', ]
             lowercase__      			= ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
             # fmt: on

             lowercase__      			= tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= tokenizer.tokenize(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= tokenizer.convert_ids_to_tokens(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )

             lowercase__      			= rust_tokenizer.encode(UpperCamelCase   ,						add_special_tokens=UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= rust_tokenizer.tokenize(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= rust_tokenizer.convert_ids_to_tokens(UpperCamelCase )
             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             lowercase__      			= DebertaVaTokenizer(UpperCamelCase )

             lowercase__      			= tokenizer.encode('''sequence builders''' )
             lowercase__      			= tokenizer.encode('''multi-sequence build''' )

             lowercase__      			= tokenizer.build_inputs_with_special_tokens(UpperCamelCase )
             lowercase__      			= tokenizer.build_inputs_with_special_tokens(UpperCamelCase   ,						UpperCamelCase )

             self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]   ,						UpperCamelCase )
             self.assertEqual(
                 [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]   ,						UpperCamelCase   ,						)






      @slow
      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             lowercase__      			= {'''input_ids''': [[1, 39867, 36, 19390, 486, 27, 35052, 81436, 18, 60685, 1225, 7, 35052, 81436, 18, 9367, 16899, 18, 15937, 53, 594, 773, 18, 16287, 30465, 36, 15937, 6, 41139, 38, 36979, 60763, 191, 6, 34132, 99, 6, 50538, 390, 43230, 6, 34132, 2779, 20850, 14, 699, 1072, 1194, 36, 382, 10901, 53, 7, 699, 1072, 2084, 36, 20422, 630, 53, 19, 105, 3049, 1896, 1053, 16899, 1506, 11, 37978, 4243, 7, 1237, 31869, 200, 16566, 654, 6, 35052, 81436, 7, 55630, 13593, 4, 2], [1, 26, 15011, 13, 667, 8, 1053, 18, 23611, 1237, 72356, 12820, 34, 104134, 1209, 35, 13313, 6627, 21, 202, 347, 7, 164, 2399, 11, 46, 4485, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 5, 1232, 2864, 15785, 14951, 105, 5, 8581, 1250, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
             # fmt: on

             self.tokenizer_integration_test_util(
                 expected_encoding=UpperCamelCase   ,						model_name='''microsoft/deberta-v2-xlarge'''   ,						revision='''ad6e42c1532ddf3a15c39246b63f5559d558b670'''   ,						)




