


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

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer


if TYPE_CHECKING:
     from transformers.pipelines.conversational import Conversation


snake_case    :   Union[str, Any]	    =					logging.get_logger(__name__)

snake_case    :   Any	    =					{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

snake_case    :   Optional[int]	    =					{
    '''vocab_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/vocab.json''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/vocab.json''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/vocab.json''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/vocab.json''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/merges.txt''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/merges.txt''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/merges.txt''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/merges.txt''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/tokenizer.json''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/tokenizer.json''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/tokenizer.json''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/tokenizer.json''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/tokenizer.json''',
    },
}

snake_case    :   Any	    =					{
    '''gpt2''': 10_24,
    '''gpt2-medium''': 10_24,
    '''gpt2-large''': 10_24,
    '''gpt2-xl''': 10_24,
    '''distilgpt2''': 10_24,
}







class 		_snake_case  (				_snake_case							):
 SCREAMING_SNAKE_CASE__				=	VOCAB_FILES_NAMES
 SCREAMING_SNAKE_CASE__				=	PRETRAINED_VOCAB_FILES_MAP
 SCREAMING_SNAKE_CASE__				=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 SCREAMING_SNAKE_CASE__				=	['input_ids', 'attention_mask']
 SCREAMING_SNAKE_CASE__				=	GPTaTokenizer




 def __init__(		self ,  _lowerCamelCase=None ,  _lowerCamelCase=None ,  _lowerCamelCase=None ,  _lowerCamelCase="<|endoftext|>" ,  _lowerCamelCase="<|endoftext|>" ,  _lowerCamelCase="<|endoftext|>" ,  _lowerCamelCase=False ,  **_lowerCamelCase ,  ):
       super().__init__(
           _lowerCamelCase ,  _lowerCamelCase ,  tokenizer_file=_lowerCamelCase ,  unk_token=_lowerCamelCase ,  bos_token=_lowerCamelCase ,  eos_token=_lowerCamelCase ,  add_prefix_space=_lowerCamelCase ,  **_lowerCamelCase ,  )

       a						:Union[str, Any]										=	kwargs.pop('''add_bos_token''' ,  _lowerCamelCase   )

       a						:Tuple										=	json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
       if pre_tok_state.get('''add_prefix_space''' ,  _lowerCamelCase   ) != add_prefix_space:
             a						:int										=	getattr(_lowerCamelCase ,  pre_tok_state.pop('''type'''   )   )
             a						:Union[str, Any]										=	add_prefix_space
             a						:Optional[int]										=	pre_tok_class(**_lowerCamelCase   )

       a						:Optional[int]										=	add_prefix_space




 def 	SCREAMING_SNAKE_CASE__    (		self ,  *_lowerCamelCase ,  **_lowerCamelCase   ):
       a						:Optional[int]										=	kwargs.get('''is_split_into_words''' ,  _lowerCamelCase   )
       assert self.add_prefix_space or not is_split_into_words, (
           F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
           "to use it with pretokenized inputs."
       )

       return super()._batch_encode_plus(*_lowerCamelCase ,  **_lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  *_lowerCamelCase ,  **_lowerCamelCase   ):
       a						:Any										=	kwargs.get('''is_split_into_words''' ,  _lowerCamelCase   )

       assert self.add_prefix_space or not is_split_into_words, (
           F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
           "to use it with pretokenized inputs."
       )

       return super()._encode_plus(*_lowerCamelCase ,  **_lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase ,  _lowerCamelCase = None   ):
       a						:Union[str, Any]										=	self._tokenizer.model.save(_lowerCamelCase ,  name=_lowerCamelCase   )
       return tuple(_lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       a						:List[str]										=	[]
       for is_user, text in conversation.iter_texts():
             input_ids.extend(self.encode(_lowerCamelCase ,  add_special_tokens=_lowerCamelCase   ) + [self.eos_token_id]   )

       if len(_lowerCamelCase   ) > self.model_max_length:
             a						:List[str]										=	input_ids[-self.model_max_length :]
       return input_ids









import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


snake_case    :   Any	    =					pytest.mark.integration
@pytest.mark.parametrize('''path'''			,  ['''paws''', '''csv''']						)
def     __lowerCamelCase						(			UpperCAmelCase_						:		Optional[int]			,  UpperCAmelCase_						:		Optional[Any]						):




      """simple docstring"""





      inspect_dataset(UpperCAmelCase_			,  UpperCAmelCase_						)
      a						:List[Any]										=	path + '''.py'''
      assert script_name in os.listdir(UpperCAmelCase_						)
      assert "__pycache__" not in os.listdir(UpperCAmelCase_						)
@pytest.mark.filterwarnings('''ignore:inspect_metric is deprecated:FutureWarning'''						)
@pytest.mark.filterwarnings('''ignore:metric_module_factory is deprecated:FutureWarning'''						)
@pytest.mark.parametrize('''path'''			,  ['''accuracy''']						)
def     __lowerCamelCase						(			UpperCAmelCase_						:		List[Any]			,  UpperCAmelCase_						:		Any						):




      """simple docstring"""





      inspect_metric(UpperCAmelCase_			,  UpperCAmelCase_						)
      a						:Dict										=	path + '''.py'''
      assert script_name in os.listdir(UpperCAmelCase_						)
      assert "__pycache__" not in os.listdir(UpperCAmelCase_						)
@pytest.mark.parametrize(
    '''path, config_name, expected_splits'''			,  [
        ('''squad''', '''plain_text''', ['''train''', '''validation''']),
        ('''dalle-mini/wit''', '''dalle-mini--wit''', ['''train''']),
        ('''paws''', '''labeled_final''', ['''train''', '''test''', '''validation''']),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		Optional[int]			,  UpperCAmelCase_						:		List[Any]			,  UpperCAmelCase_						:		str						):




      """simple docstring"""





      a						:List[str]										=	get_dataset_config_info(UpperCAmelCase_			,  config_name=UpperCAmelCase_						)
      assert info.config_name == config_name
      assert list(info.splits.keys()						) == expected_splits
@pytest.mark.parametrize(
    '''path, config_name, expected_exception'''			,  [
        ('''paws''', None, ValueError),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		List[Any]			,  UpperCAmelCase_						:		str			,  UpperCAmelCase_						:		Tuple						):




      """simple docstring"""





      with pytest.raises(UpperCAmelCase_						):
            get_dataset_config_info(UpperCAmelCase_			,  config_name=UpperCAmelCase_						)
@pytest.mark.parametrize(
    '''path, expected'''			,  [
        ('''squad''', '''plain_text'''),
        ('''acronym_identification''', '''default'''),
        ('''lhoestq/squad''', '''plain_text'''),
        ('''lhoestq/test''', '''default'''),
        ('''lhoestq/demo1''', '''lhoestq--demo1'''),
        ('''dalle-mini/wit''', '''dalle-mini--wit'''),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		Tuple			,  UpperCAmelCase_						:		int						):




      """simple docstring"""





      a						:List[str]										=	get_dataset_config_names(UpperCAmelCase_						)
      assert expected in config_names
@pytest.mark.parametrize(
    '''path, expected_configs, expected_splits_in_first_config'''			,  [
        ('''squad''', ['''plain_text'''], ['''train''', '''validation''']),
        ('''dalle-mini/wit''', ['''dalle-mini--wit'''], ['''train''']),
        ('''paws''', ['''labeled_final''', '''labeled_swap''', '''unlabeled_final'''], ['''train''', '''test''', '''validation''']),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		Tuple			,  UpperCAmelCase_						:		Tuple			,  UpperCAmelCase_						:		Optional[int]						):




      """simple docstring"""





      a						:Optional[int]										=	get_dataset_infos(UpperCAmelCase_						)
      assert list(infos.keys()						) == expected_configs
      a						:Union[str, Any]										=	expected_configs[0]
      assert expected_config in infos
      a						:List[Any]										=	infos[expected_config]
      assert info.config_name == expected_config
      assert list(info.splits.keys()						) == expected_splits_in_first_config
@pytest.mark.parametrize(
    '''path, expected_config, expected_splits'''			,  [
        ('''squad''', '''plain_text''', ['''train''', '''validation''']),
        ('''dalle-mini/wit''', '''dalle-mini--wit''', ['''train''']),
        ('''paws''', '''labeled_final''', ['''train''', '''test''', '''validation''']),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		Optional[int]			,  UpperCAmelCase_						:		Any			,  UpperCAmelCase_						:		Optional[int]						):




      """simple docstring"""





      a						:Union[str, Any]										=	get_dataset_infos(UpperCAmelCase_						)
      assert expected_config in infos
      a						:int										=	infos[expected_config]
      assert info.config_name == expected_config
      assert list(info.splits.keys()						) == expected_splits






@pytest.mark.parametrize(
    '''path, config_name, expected_exception'''			,  [
        ('''paws''', None, ValueError),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		Union[str, Any]			,  UpperCAmelCase_						:		Optional[int]			,  UpperCAmelCase_						:		str						):




      """simple docstring"""





      with pytest.raises(UpperCAmelCase_						):
            get_dataset_split_names(UpperCAmelCase_			,  config_name=UpperCAmelCase_						)





