



import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation


__snake_case						:str						=					logging.get_logger(__name__)

__snake_case						:Optional[Any]						=					{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

__snake_case						:Optional[int]						=					{
    '''tokenizer_file''': {
        '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json''',
    },
}

__snake_case						:Optional[int]						=					{
    '''gpt-neox-20b''': 2048,
}

class    _A	(     __UpperCAmelCase   ):
       UpperCamelCase__  :   Union[str, Any]						 =						VOCAB_FILES_NAMES
       UpperCamelCase__  :   Tuple						 =						PRETRAINED_VOCAB_FILES_MAP
       UpperCamelCase__  :   List[Any]						 =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCamelCase__  :   str						 =						['''input_ids''', '''attention_mask''']



       def __init__(		self							:					List[Any]					,		__SCREAMING_SNAKE_CASE							:					Any=None					,		__SCREAMING_SNAKE_CASE							:					List[Any]=None					,		__SCREAMING_SNAKE_CASE							:					str=None					,		__SCREAMING_SNAKE_CASE							:					int="<|endoftext|>"					,		__SCREAMING_SNAKE_CASE							:					Optional[int]="<|endoftext|>"					,		__SCREAMING_SNAKE_CASE							:					Dict="<|endoftext|>"					,		__SCREAMING_SNAKE_CASE							:					Optional[int]=False					,		**__SCREAMING_SNAKE_CASE							:					List[str]					,		):


           '''simple docstring'''

           super().__init__(
               __SCREAMING_SNAKE_CASE					,		__SCREAMING_SNAKE_CASE					,		tokenizer_file=__SCREAMING_SNAKE_CASE					,		unk_token=__SCREAMING_SNAKE_CASE					,		bos_token=__SCREAMING_SNAKE_CASE					,		eos_token=__SCREAMING_SNAKE_CASE					,		add_prefix_space=__SCREAMING_SNAKE_CASE					,		**__SCREAMING_SNAKE_CASE					,		)

           __a							=    json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
           if pre_tok_state.get('''add_prefix_space'''					,		__SCREAMING_SNAKE_CASE) != add_prefix_space:
               __a							=    getattr(__SCREAMING_SNAKE_CASE					,		pre_tok_state.pop('''type'''))
               __a							=    add_prefix_space
               __a							=    pre_tok_class(**__SCREAMING_SNAKE_CASE)

           __a							=    add_prefix_space



       def 		_lowerCamelCase      (		self							:					Tuple					,		__SCREAMING_SNAKE_CASE							:					str					,		__SCREAMING_SNAKE_CASE							:					Optional[str] = None):


           '''simple docstring'''

           __a							=    self._tokenizer.model.save(__SCREAMING_SNAKE_CASE					,		name=__SCREAMING_SNAKE_CASE)
           return tuple(__SCREAMING_SNAKE_CASE)





       def 		_lowerCamelCase      (		self							:					Union[str, Any]					,		__SCREAMING_SNAKE_CASE							:					"Conversation"):


           '''simple docstring'''

           __a							=    []
           for is_user, text in conversation.iter_texts():
               input_ids.extend(self.encode(__SCREAMING_SNAKE_CASE					,		add_special_tokens=__SCREAMING_SNAKE_CASE) + [self.eos_token_id])

           if len(__SCREAMING_SNAKE_CASE) > self.model_max_length:
               __a							=    input_ids[-self.model_max_length :]
           return input_ids










import unittest

from transformers import DonutProcessor


__snake_case						:List[str]						=					'''naver-clova-ix/donut-base'''

class    _A	(     unittest.TestCase   ):



       def 		_lowerCamelCase      (		self							:					List[str]):


           '''simple docstring'''

           __a							=    DonutProcessor.from_pretrained(__SCREAMING_SNAKE_CASE)





       def 		_lowerCamelCase      (		self							:					Tuple):


           '''simple docstring'''

           __a							=    {
               '''name''': '''John Doe''',
               '''age''': '''99''',
               '''city''': '''Atlanta''',
               '''state''': '''GA''',
               '''zip''': '''30301''',
               '''phone''': '''123-4567''',
               '''nicknames''': [{'''nickname''': '''Johnny'''}, {'''nickname''': '''JD'''}],
           }

           __a							=    (
               '''<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>'''
               '''<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>'''
               '''<s_nicknames><s_nickname>Johnny</s_nickname>'''
               '''<sep/><s_nickname>JD</s_nickname></s_nicknames>'''
           )
           __a							=    self.processor.tokenajson(__SCREAMING_SNAKE_CASE)

           self.assertDictEqual(__SCREAMING_SNAKE_CASE					,		__SCREAMING_SNAKE_CASE)





