





'''simple docstring'''

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


lowercase__		:     int			=							logging.get_logger(__name__)

lowercase__		:     str			=							{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

lowercase__		:     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',
    },
}

lowercase__		:     List[str]			=							{
    'gpt2': 10_24,
    'gpt2-medium': 10_24,
    'gpt2-large': 10_24,
    'gpt2-xl': 10_24,
    'distilgpt2': 10_24,
}
class 							__lowerCAmelCase	(       __magic_name__					):






       """simple docstring"""
       _snake_case      :	Any									=       VOCAB_FILES_NAMES
       _snake_case      :	str									=       PRETRAINED_VOCAB_FILES_MAP
       _snake_case      :	Dict									=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       _snake_case      :	str									=       ['input_ids', 'attention_mask']
       _snake_case      :	Dict									=       GPTaTokenizer





       def __init__(				self  :						Any			,					lowerCAmelCase__  :						Tuple=None			,					lowerCAmelCase__  :						Union[str, Any]=None			,					lowerCAmelCase__  :						Union[str, Any]=None			,					lowerCAmelCase__  :						Union[str, Any]="<|endoftext|>"			,					lowerCAmelCase__  :						Optional[Any]="<|endoftext|>"			,					lowerCAmelCase__  :						Tuple="<|endoftext|>"			,					lowerCAmelCase__  :						str=False			,					**lowerCAmelCase__  :						List[Any]			,					)       ->	Union[str, Any]:

            '''simple docstring'''




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

            _UpperCamelCase							       =			kwargs.pop('''add_bos_token'''			,					lowerCAmelCase__	)

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

            _UpperCamelCase							       =			add_prefix_space





       def snake_case__		(				self  :						Union[str, Any]			,					*lowerCAmelCase__  :						Any			,					**lowerCAmelCase__  :						Any	)       ->	BatchEncoding:

            '''simple docstring'''




            _UpperCamelCase							       =			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 snake_case__		(				self  :						Optional[int]			,					*lowerCAmelCase__  :						int			,					**lowerCAmelCase__  :						List[Any]	)       ->	BatchEncoding:

            '''simple docstring'''




            _UpperCamelCase							       =			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 snake_case__		(				self  :						Any			,					lowerCAmelCase__  :						str			,					lowerCAmelCase__  :						Optional[str] = None	)       ->	Tuple[str]:

            '''simple docstring'''




            _UpperCamelCase							       =			self._tokenizer.model.save(lowerCAmelCase__			,					name=lowerCAmelCase__	)
            return tuple(lowerCAmelCase__	)







       def snake_case__		(				self  :						Optional[Any]			,					lowerCAmelCase__  :						"Conversation"	)       ->	List[int]:

            '''simple docstring'''




            _UpperCamelCase							       =			[]
            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:
                 _UpperCamelCase							       =			input_ids[-self.model_max_length :]
            return input_ids










'''simple docstring'''

def    a__							(							lowercase   :	str )						->						int:





     """simple docstring"""

     assert column_title.isupper()
     _UpperCamelCase							       =			0
     _UpperCamelCase							       =			len(lowercase ) - 1
     _UpperCamelCase							       =			0

     while index >= 0:
          _UpperCamelCase							       =			(ord(column_title[index] ) - 64) * pow(26,   lowercase )
          answer += value
          power += 1
          index -= 1

     return answer


if __name__ == "__main__":
   from doctest import testmod

   testmod()



