





'''simple docstring'''



def    _lowerCAmelCase						(				lowerCamelCase_			:  str		,       lowerCamelCase_			:  int				):
			__lowercase										=							[[] for _ in range(lowerCamelCase_				)]
			__lowercase										=							key - 1

			if key <= 0:
						raise ValueError('''Height of grid can\'t be 0 or negative'''				)
			if key == 1 or len(lowerCamelCase_				) <= key:
						return input_string

			for position, character in enumerate(lowerCamelCase_				):
						__lowercase										=							position % (lowest * 2)  # puts it in bounds
						__lowercase										=							min(lowerCamelCase_		,       lowest * 2 - num				)  # creates zigzag pattern
						temp_grid[num].append(lowerCamelCase_				)
			__lowercase										=							[''''''.join(lowerCamelCase_				) for row in temp_grid]
			__lowercase										=							''''''.join(lowerCamelCase_				)

			return output_string




def    _lowerCAmelCase						(				lowerCamelCase_			:  str		,       lowerCamelCase_			:  int				):
			__lowercase										=							[]
			__lowercase										=							key - 1

			if key <= 0:
						raise ValueError('''Height of grid can\'t be 0 or negative'''				)
			if key == 1:
						return input_string

			__lowercase										=							[[] for _ in range(lowerCamelCase_				)]  # generates template
			for position in range(len(lowerCamelCase_				)				):
						__lowercase										=							position % (lowest * 2)  # puts it in bounds
						__lowercase										=							min(lowerCamelCase_		,       lowest * 2 - num				)  # creates zigzag pattern
						temp_grid[num].append('''*'''				)

			__lowercase										=							0
			for row in temp_grid:  # fills in the characters
						__lowercase										=							input_string[counter : counter + len(lowerCamelCase_				)]
						grid.append(list(lowerCamelCase_				)				)
						counter += len(lowerCamelCase_				)

			__lowercase										=							''''''  # reads as zigzag
			for position in range(len(lowerCamelCase_				)				):
						__lowercase										=							position % (lowest * 2)  # puts it in bounds
						__lowercase										=							min(lowerCamelCase_		,       lowest * 2 - num				)  # creates zigzag pattern
						output_string += grid[num][0]
						grid[num].pop(0				)
			return output_string




def    _lowerCAmelCase						(				lowerCamelCase_			:  str				):
			__lowercase										=							{}
			for key_guess in range(1		,       len(lowerCamelCase_				)				):  # tries every key
						__lowercase										=							decrypt(lowerCamelCase_		,       lowerCamelCase_				)
			return results


if __name__ == "__main__":
	import doctest

	doctest.testmod()












'''simple docstring'''



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


_SCREAMING_SNAKE_CASE					=    logging.get_logger(__name__)

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

_SCREAMING_SNAKE_CASE					=    {
    '''tokenizer_file''': {
        '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json''',
    },
}

_SCREAMING_SNAKE_CASE					=    {
    '''gpt-neox-20b''': 2_0_4_8,
}






class 							__lowercase       (      lowerCAmelCase__						):







	'''simple docstring'''

	a    :				List[Any]											=       VOCAB_FILES_NAMES
	a    :				Optional[Any]											=       PRETRAINED_VOCAB_FILES_MAP
	a    :				Optional[int]											=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	a    :				List[str]											=       ["input_ids", "attention_mask"]


	def __init__(self     ,_lowerCamelCase=None     ,_lowerCamelCase=None     ,_lowerCamelCase=None     ,_lowerCamelCase="<|endoftext|>"     ,_lowerCamelCase="<|endoftext|>"     ,_lowerCamelCase="<|endoftext|>"     ,_lowerCamelCase=False     ,**_lowerCamelCase     ,)							->							Optional[Any]:







				'''simple docstring'''





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

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

				__lowercase										=							add_prefix_space


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase     ,_lowerCamelCase = None )							->							Tuple[str]:







				'''simple docstring'''





				__lowercase										=							self._tokenizer.model.save(_lowerCamelCase     ,name=_lowerCamelCase )
				return tuple(_lowerCamelCase )


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase )							->							List[int]:







				'''simple docstring'''





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





