



"""simple docstring"""
import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
      from transformers.models.rag.configuration_rag import RagConfig
      from transformers.models.rag.tokenization_rag import RagTokenizer



@require_faiss
@require_torch
class       SCREAMING_SNAKE_CASE__  (					lowerCAmelCase__ ):

   def 	SCREAMING_SNAKE_CASE     (   self						)  ->      Dict:





    '''simple docstring'''




    UpperCAmelCase	:					List[Any]	=	tempfile.mkdtemp()
    UpperCAmelCase	:					Tuple	=	8

    # DPR tok
    UpperCAmelCase	:					Tuple	=	[
        '''[UNK]''',
        '''[CLS]''',
        '''[SEP]''',
        '''[PAD]''',
        '''[MASK]''',
        '''want''',
        '''##want''',
        '''##ed''',
        '''wa''',
        '''un''',
        '''runn''',
        '''##ing''',
        ''',''',
        '''low''',
        '''lowest''',
    ]
    UpperCAmelCase	:					Tuple	=	os.path.join(self.tmpdirname      ,     """dpr_tokenizer"""						)
    os.makedirs(lowercase_      ,     exist_ok=lowercase_						)
    UpperCAmelCase	:					List[str]	=	os.path.join(lowercase_      ,     DPR_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]						)						)

    # BART tok
    UpperCAmelCase	:					Tuple	=	[
        '''l''',
        '''o''',
        '''w''',
        '''e''',
        '''r''',
        '''s''',
        '''t''',
        '''i''',
        '''d''',
        '''n''',
        '''\u0120''',
        '''\u0120l''',
        '''\u0120n''',
        '''\u0120lo''',
        '''\u0120low''',
        '''er''',
        '''\u0120lowest''',
        '''\u0120newer''',
        '''\u0120wider''',
        '''<unk>''',
    ]
    UpperCAmelCase	:					Union[str, Any]	=	dict(zip(lowercase_      ,     range(len(lowercase_						)						)						)						)
    UpperCAmelCase	:					Union[str, Any]	=	['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
    UpperCAmelCase	:					List[str]	=	{'''unk_token''': '''<unk>'''}

    UpperCAmelCase	:					Any	=	os.path.join(self.tmpdirname      ,     """bart_tokenizer"""						)
    os.makedirs(lowercase_      ,     exist_ok=lowercase_						)
    UpperCAmelCase	:					Optional[int]	=	os.path.join(lowercase_      ,     BART_VOCAB_FILES_NAMES["""vocab_file"""]						)
    UpperCAmelCase	:					int	=	os.path.join(lowercase_      ,     BART_VOCAB_FILES_NAMES["""merges_file"""]						)
    with open(self.vocab_file      ,     """w"""      ,     encoding="""utf-8"""						) as fp:
     fp.write(json.dumps(lowercase_						) + """\n"""						)
    with open(self.merges_file      ,     """w"""      ,     encoding="""utf-8"""						) as fp:
     fp.write("""\n""".join(lowercase_						)						)

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





    '''simple docstring'''




    return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname      ,     """dpr_tokenizer"""						)						)

   def 	SCREAMING_SNAKE_CASE     (   self						)  ->      Tuple:





    '''simple docstring'''




    return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname      ,     """bart_tokenizer"""						)						)

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





    '''simple docstring'''




    shutil.rmtree(self.tmpdirname						)

   @require_tokenizers
   def 	SCREAMING_SNAKE_CASE     (   self						)  ->      Tuple:





    '''simple docstring'''




    UpperCAmelCase	:					Optional[int]	=	os.path.join(self.tmpdirname      ,     """rag_tokenizer"""						)
    UpperCAmelCase	:					List[str]	=	RagConfig(question_encoder=DPRConfig().to_dict()      ,     generator=BartConfig().to_dict()						)
    UpperCAmelCase	:					Tuple	=	RagTokenizer(question_encoder=self.get_dpr_tokenizer()      ,     generator=self.get_bart_tokenizer()						)
    rag_config.save_pretrained(lowercase_						)
    rag_tokenizer.save_pretrained(lowercase_						)
    UpperCAmelCase	:					Optional[Any]	=	RagTokenizer.from_pretrained(lowercase_      ,     config=lowercase_						)
    self.assertIsInstance(new_rag_tokenizer.question_encoder      ,     lowercase_						)
    self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()      ,     rag_tokenizer.question_encoder.get_vocab()						)
    self.assertIsInstance(new_rag_tokenizer.generator      ,     lowercase_						)
    self.assertEqual(new_rag_tokenizer.generator.get_vocab()      ,     rag_tokenizer.generator.get_vocab()						)

   @slow
   def 	SCREAMING_SNAKE_CASE     (   self						)  ->      Dict:





    '''simple docstring'''




    UpperCAmelCase	:					Tuple	=	RagTokenizer.from_pretrained("""facebook/rag-token-nq"""						)
    UpperCAmelCase	:					List[str]	=	[
        '''who got the first nobel prize in physics''',
        '''when is the next deadpool movie being released''',
        '''which mode is used for short wave broadcast service''',
        '''who is the owner of reading football club''',
        '''when is the next scandal episode coming out''',
        '''when is the last time the philadelphia won the superbowl''',
        '''what is the most current adobe flash player version''',
        '''how many episodes are there in dragon ball z''',
        '''what is the first step in the evolution of the eye''',
        '''where is gall bladder situated in human body''',
        '''what is the main mineral in lithium batteries''',
        '''who is the president of usa right now''',
        '''where do the greasers live in the outsiders''',
        '''panda is a national animal of which country''',
        '''what is the name of manchester united stadium''',
    ]
    UpperCAmelCase	:					Optional[Any]	=	tokenizer(lowercase_						)
    self.assertIsNotNone(lowercase_						)




   @slow
   def 	SCREAMING_SNAKE_CASE     (   self						)  ->      int:





    '''simple docstring'''




    UpperCAmelCase	:					int	=	RagTokenizer.from_pretrained("""facebook/rag-sequence-nq"""						)
    UpperCAmelCase	:					Any	=	[
        '''who got the first nobel prize in physics''',
        '''when is the next deadpool movie being released''',
        '''which mode is used for short wave broadcast service''',
        '''who is the owner of reading football club''',
        '''when is the next scandal episode coming out''',
        '''when is the last time the philadelphia won the superbowl''',
        '''what is the most current adobe flash player version''',
        '''how many episodes are there in dragon ball z''',
        '''what is the first step in the evolution of the eye''',
        '''where is gall bladder situated in human body''',
        '''what is the main mineral in lithium batteries''',
        '''who is the president of usa right now''',
        '''where do the greasers live in the outsiders''',
        '''panda is a national animal of which country''',
        '''what is the name of manchester united stadium''',
    ]
    UpperCAmelCase	:					Optional[int]	=	tokenizer(lowercase_						)
    self.assertIsNotNone(lowercase_						)





"""simple docstring"""

import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
     from .tokenization_pegasus import PegasusTokenizer
else:
     lowercase__    :  int							    =	None


lowercase__    :  Any							    =	logging.get_logger(__name__)


lowercase__    :  List[str]							    =	'''▁'''

lowercase__    :  Optional[int]							    =	{'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase__    :  str							    =	{
    '''vocab_file''': {'''google/pegasus-xsum''': '''https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'''},
    '''tokenizer_file''': {
        '''google/pegasus-xsum''': '''https://huggingface.co/google/pegasus-xsum/resolve/main/tokenizer.json'''
    },
}

lowercase__    :  List[Any]							    =	{
    '''google/pegasus-xsum''': 5_12,
}




class        _UpperCAmelCase       (			lowerCAmelCase__):
 _lowerCAmelCase   :			List[str]							=		VOCAB_FILES_NAMES
 _lowerCAmelCase   :			List[str]							=		PRETRAINED_VOCAB_FILES_MAP
 _lowerCAmelCase   :			Any							=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCAmelCase   :			Tuple							=		PegasusTokenizer
 _lowerCAmelCase   :			str							=		["""input_ids""", """attention_mask"""]

 def __init__(     self		:       Any  ,     lowercase_		:       Optional[Any]=None  ,     lowercase_		:       int=None  ,     lowercase_		:       Tuple="<pad>"  ,     lowercase_		:       int="</s>"  ,     lowercase_		:       Tuple="<unk>"  ,     lowercase_		:       str="<mask_2>"  ,     lowercase_		:       Optional[Any]="<mask_1>"  ,     lowercase_		:       str=None  ,     lowercase_		:       List[str]=103  ,     **lowercase_		:       List[Any]  ,     ):
     snake_case_ :     Dict				=	offset

     if additional_special_tokens is not None:
         if not isinstance(lowercase_  ,     lowercase_				):
             raise TypeError(
                 f"additional_special_tokens should be of type {type(lowercase_				)}, but is"
                 f" {type(lowercase_				)}"				)

         snake_case_ :     str				=	(
             ([mask_token_sent] + additional_special_tokens)
             if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
             else additional_special_tokens
         )
         # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
         additional_special_tokens_extended += [
             f"<unk_{i}>" for i in range(len(lowercase_				)  ,     self.offset - 1				)
         ]

         if len(set(lowercase_				)				) != len(lowercase_				):
             raise ValueError(
                 '''Please make sure that the provided additional_special_tokens do not contain an incorrectly'''
                 f" shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}."				)
         snake_case_ :     Union[str, Any]				=	additional_special_tokens_extended
     else:
         snake_case_ :     Dict				=	[mask_token_sent] if mask_token_sent is not None else []
         additional_special_tokens += [f"<unk_{i}>" for i in range(2  ,     self.offset				)]

     super().__init__(
         lowercase_  ,     tokenizer_file=lowercase_  ,     pad_token=lowercase_  ,     eos_token=lowercase_  ,     unk_token=lowercase_  ,     mask_token=lowercase_  ,     mask_token_sent=lowercase_  ,     offset=lowercase_  ,     additional_special_tokens=lowercase_  ,     **lowercase_  ,     )
     snake_case_ :     List[Any]				=	vocab_file
     snake_case_ :     List[Any]				=	False if not self.vocab_file else True

 def 						_snake_case					(     self		:       str  ,     lowercase_		:       Union[str, Any]				):
     snake_case_ :     Any				=	set(self.all_special_ids				)  # call it once instead of inside list comp
     all_special_ids.remove(self.unk_token_id				)  # <unk> is only sometimes special

     if all_special_ids != set(range(len(self.additional_special_tokens				) + 3				)				):
         raise ValueError(
             '''There should be 3 special tokens: mask_token, pad_token, and eos_token +'''
             f" {len(self.additional_special_tokens				)} additional_special_tokens, but got {all_special_ids}"				)

     return [1 if x in all_special_ids else 0 for x in seq]

 def 						_snake_case					(     self		:       int  ,     lowercase_		:       List  ,     lowercase_		:       Optional[List] = None  ,     lowercase_		:       bool = False				):
     if already_has_special_tokens:
         return self._special_token_mask(lowercase_				)
     elif token_ids_a is None:
         return self._special_token_mask(lowercase_				) + [1]
     else:
         return self._special_token_mask(token_ids_a + token_ids_a				) + [1]

 def 						_snake_case					(     self		:       List[Any]  ,     lowercase_		:       Optional[int]  ,     lowercase_		:       str=None				):
     if token_ids_a is None:
         return token_ids_a + [self.eos_token_id]
     # We don't expect to process pairs, but leave the pair logic for API consistency
     return token_ids_a + token_ids_a + [self.eos_token_id]






 def 						_snake_case					(     self		:       Optional[Any]  ,     lowercase_		:       str  ,     lowercase_		:       Optional[str] = None				):
     if not self.can_save_slow_tokenizer:
         raise ValueError(
             '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
             '''tokenizer.'''				)

     if not os.path.isdir(lowercase_				):
         logger.error(f"Vocabulary path ({save_directory}) should be a directory"				)
         return
     snake_case_ :     Dict				=	os.path.join(
         lowercase_  ,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)

     if os.path.abspath(self.vocab_file				) != os.path.abspath(lowercase_				):
         copyfile(self.vocab_file  ,     lowercase_				)

     return (out_vocab_file,)





