


"""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


if TYPE_CHECKING:
				from transformers.pipelines.conversational import Conversation


__SCREAMING_SNAKE_CASE							:      str						=      logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE							:      int						=      {'tokenizer_file': 'tokenizer.json'}

__SCREAMING_SNAKE_CASE							:      Optional[Any]						=      {
    'tokenizer_file': {
        'bigscience/tokenizer': 'https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json',
        'bigscience/bloom-560m': 'https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json',
        'bigscience/bloom-1b1': 'https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json',
        'bigscience/bloom-1b7': 'https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json',
        'bigscience/bloom-3b': 'https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json',
        'bigscience/bloom-7b1': 'https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json',
        'bigscience/bloom': 'https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json',
    },
}





class        __A       (snake_case__):





							'''simple docstring'''

							__lowercase:						Dict							 =      VOCAB_FILES_NAMES
							__lowercase:						Optional[int]							 =      PRETRAINED_VOCAB_FILES_MAP
							__lowercase:						Optional[Any]							 =      ["""input_ids""", """attention_mask"""]
							__lowercase:						Any							 =      None



							def __init__(			self							: int						,    UpperCAmelCase_							: List[Any]=None						,    UpperCAmelCase_							: Union[str, Any]=None						,    UpperCAmelCase_							: Optional[Any]=None						,    UpperCAmelCase_							: Any="<unk>"						,    UpperCAmelCase_							: Optional[Any]="<s>"						,    UpperCAmelCase_							: List[Any]="</s>"						,    UpperCAmelCase_							: Tuple="<pad>"						,    UpperCAmelCase_							: Optional[int]=False						,    UpperCAmelCase_							: int=False						,    **UpperCAmelCase_							: Any						,    )   ->List[str]:



														"""simple docstring"""



														super().__init__(
														    UpperCAmelCase_						,    UpperCAmelCase_						,    tokenizer_file=UpperCAmelCase_						,    unk_token=UpperCAmelCase_						,    bos_token=UpperCAmelCase_						,    eos_token=UpperCAmelCase_						,    pad_token=UpperCAmelCase_						,    add_prefix_space=UpperCAmelCase_						,    clean_up_tokenization_spaces=UpperCAmelCase_						,    **UpperCAmelCase_						,    )
														snake_case_          =						json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()    )
														if pre_tok_state.get("""add_prefix_space"""						,    UpperCAmelCase_    ) != add_prefix_space:
																					snake_case_          =						getattr(UpperCAmelCase_						,    pre_tok_state.pop("""type"""    )    )
																					snake_case_          =						add_prefix_space
																					snake_case_          =						pre_tok_class(**UpperCAmelCase_    )

														snake_case_          =						add_prefix_space



							def 						lowerCAmelCase    (			self							: List[Any]						,    *UpperCAmelCase_							: Any						,    **UpperCAmelCase_							: Any    )   ->BatchEncoding:



														"""simple docstring"""



														snake_case_          =						kwargs.get("""is_split_into_words"""						,    UpperCAmelCase_    )
														if not (self.add_prefix_space or not is_split_into_words):
																					raise Exception(
																					    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
																					    """ pretokenized inputs."""    )

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



							def 						lowerCAmelCase    (			self							: Any						,    *UpperCAmelCase_							: Optional[Any]						,    **UpperCAmelCase_							: Union[str, Any]    )   ->BatchEncoding:



														"""simple docstring"""



														snake_case_          =						kwargs.get("""is_split_into_words"""						,    UpperCAmelCase_    )

														if not (self.add_prefix_space or not is_split_into_words):
																					raise Exception(
																					    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
																					    """ pretokenized inputs."""    )

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



							def 						lowerCAmelCase    (			self							: int						,    UpperCAmelCase_							: str						,    UpperCAmelCase_							: Optional[str] = None    )   ->Tuple[str]:



														"""simple docstring"""



														snake_case_          =						self._tokenizer.model.save(UpperCAmelCase_						,    name=UpperCAmelCase_    )
														return tuple(UpperCAmelCase_    )



							def 						lowerCAmelCase    (			self							: List[Any]						,    UpperCAmelCase_							: "Conversation"    )   ->List[int]:



														"""simple docstring"""



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

														if len(UpperCAmelCase_    ) > self.model_max_length:
																					snake_case_          =						input_ids[-self.model_max_length :]
														return input_ids








"""simple docstring"""
def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			str:
							return "\n".join(
							    f"""{number} * {i} = {number * i}""" for i in range(1			,	number_of_terms + 1			)			)


if __name__ == "__main__":
				print(multiplication_table(number=5, number_of_terms=10))



