




'''simple docstring'''

import os
from shutil import copyfile
from typing import TYPE_CHECKING, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
from ...utils.versions import require_version


if TYPE_CHECKING:
		from transformers.pipelines.conversational import Conversation

require_version('''tokenizers>=0.13.3''')

if is_sentencepiece_available():
		from .tokenization_llama import LlamaTokenizer
else:
		a__         =     None

a__         =     logging.get_logger(__name__)
a__         =     {'''vocab_file''': '''tokenizer.model''', '''tokenizer_file''': '''tokenizer.json'''}

a__    , a__         =     '''[INST]''', '''[/INST]'''
a__    , a__         =     '''<<SYS>>\n''', '''\n<</SYS>>\n\n'''

# fmt: off
a__         =     '''You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\
answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\
that your responses are socially unbiased and positive in nature.

If a question does not make any sense, or is not factually coherent, explain why instead of answering something not\
correct. If you don\'t know the answer to a question, please don\'t share false information.'''





class __magic_name__(						__lowerCAmelCase      ):
						UpperCAmelCase_		:					str    =  VOCAB_FILES_NAMES
						UpperCAmelCase_		:					List[Any]    =  LlamaTokenizer
						UpperCAmelCase_		:					Any    =  """left"""
						UpperCAmelCase_		:					Optional[int]    =  ["""input_ids""", """attention_mask"""]






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



									'''simple docstring'''






									super().__init__(
									    vocab_file=__UpperCamelCase					,   tokenizer_file=__UpperCamelCase					,   clean_up_tokenization_spaces=__UpperCamelCase					,   unk_token=__UpperCamelCase					,   bos_token=__UpperCamelCase					,   eos_token=__UpperCamelCase					,   **__UpperCamelCase					,   )
									snake_case__          =						add_bos_token
									snake_case__          =						add_eos_token
									self.update_post_processor()

									snake_case__          =						vocab_file
									snake_case__          =						False if not self.vocab_file else True






						def       __lowerCAmelCase(   self						:						List[Any]       ):



									'''simple docstring'''






									snake_case__          =						self.bos_token
									snake_case__          =						self.bos_token_id

									snake_case__          =						self.eos_token
									snake_case__          =						self.eos_token_id

									snake_case__          =						f"""{(bos+":0 ") * self.add_bos_token}$A:0{(" "+eos+":0") * self.add_eos_token}"""
									snake_case__          =						f"""{single}{(" "+bos+":1") * self.add_bos_token} $B:1{(" "+eos+":1") * self.add_eos_token}"""

									snake_case__          =						[]
									if self.add_bos_token:
												special_tokens.append((bos, bos_token_id)       )
									if self.add_eos_token:
												special_tokens.append((eos, eos_token_id)       )
									snake_case__          =						processors.TemplateProcessing(
									    single=__UpperCamelCase					,   pair=__UpperCamelCase					,   special_tokens=__UpperCamelCase       )






						@property
						def       __lowerCAmelCase(   self						:						int       ):



									'''simple docstring'''






									return self._add_eos_token






						@property
						def       __lowerCAmelCase(   self						:						str       ):



									'''simple docstring'''






									return self._add_bos_token






						@add_eos_token.setter
						def       __lowerCAmelCase(   self						:						Union[str, Any]					,   __UpperCamelCase						:						Any       ):



									'''simple docstring'''






									snake_case__          =						value
									self.update_post_processor()






						@add_bos_token.setter
						def       __lowerCAmelCase(   self						:						int					,   __UpperCamelCase						:						Any       ):



									'''simple docstring'''






									snake_case__          =						value
									self.update_post_processor()






						def       __lowerCAmelCase(   self						:						Any					,   __UpperCamelCase						:						str					,   __UpperCamelCase						:						Optional[str] = None       ):



									'''simple docstring'''






									if not self.can_save_slow_tokenizer:
												raise ValueError(
												    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
												    """tokenizer."""       )

									if not os.path.isdir(__UpperCamelCase       ):
												logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""       )
												return
									snake_case__          =						os.path.join(
									    __UpperCamelCase					,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )

									if os.path.abspath(self.vocab_file       ) != os.path.abspath(__UpperCamelCase       ):
												copyfile(self.vocab_file					,   __UpperCamelCase       )

									return (out_vocab_file,)







						def       __lowerCAmelCase(   self						:						Optional[int]					,   __UpperCamelCase						:						"Conversation"       ):



									'''simple docstring'''






									snake_case__          =						list(conversation.iter_texts()       )
									if not all([is_user for is_user, msg in dialogue[::2]]       ) or not all(
									    [not is_user for is_user, msg in dialogue[1::2]]       ):
												raise ValueError(
												    """The model only supports 'user' and 'assistant' roles, starting with user and alternating (u/a/u/a/u...)"""       )

									snake_case__          =						[]
									if len(conversation.past_user_inputs       ) > 0:
												if not conversation.past_user_inputs[0].startswith(__UpperCamelCase       ) or E_SYS not in conversation.past_user_inputs[0]:
															snake_case__          =						(
															    B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
															)
									elif not dialogue[0][1].startswith(__UpperCamelCase       ) or E_SYS not in dialogue[0][1]:
												snake_case__          =						(dialogue[0][0], B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + dialogue[0][1])

									dialog_tokens += sum(
									    [
									        [self.bos_token_id]
									        + self.encode(
									            f"""{B_INST} {(prompt[1]).strip()} {E_INST} {(answer[1]).strip()} """					,   add_special_tokens=__UpperCamelCase       )
									        + [self.eos_token_id]
									        for prompt, answer in zip(dialogue[::2]					,   dialogue[1::2]       )
									    ]					,   []					,   )
									if not (dialogue[-1][0]):
												raise ValueError(f"""Last message must be from user, got {dialogue[-1]["role"]}"""       )
									dialog_tokens += [self.bos_token_id] + self.encode(
									    f"""{B_INST} {(dialogue[-1][1]).strip()} {E_INST}"""					,   add_special_tokens=__UpperCamelCase       )
									return dialog_tokens



"""simple docstring"""
SCREAMING_SNAKE_CASE					:       List[Any]							   =							1000






def 						lowercase				(	_snake_case		: float	)	->float:
	"""simple docstring"""





	return x * x






def 						lowercase				(	_snake_case		: Union[str, Any]	,  _snake_case		: float	,  _snake_case		: float	,  _snake_case		: int = 4	)	->float:
	"""simple docstring"""





	assert callable(
	    _snake_case	), f"""the function(object) passed should be callable your input : {function}"""
	assert isinstance(_snake_case	,  (float, int)	), f"""a should be float or integer your input : {a}"""
	assert isinstance(function(_snake_case	)	,  (float, int)	), (
	    "the function should return integer or float return type of your function, "
	    f"""{type(_snake_case	)}"""
	)
	assert isinstance(_snake_case	,  (float, int)	), f"""b should be float or integer your input : {b}"""
	assert (
	    isinstance(_snake_case	,  _snake_case	) and precision > 0
	), f"""precision should be positive integer your input : {precision}"""

	# just applying the formula of simpson for approximate integration written in
	# mentioned article in first comment of this file and above this function

	__snake_case      :		Tuple         =							(b - a) / N_STEPS
	__snake_case      :		Union[str, Any]         =							function(_snake_case	) + function(_snake_case	)

	for i in range(1	,  _snake_case	):
		__snake_case      :		List[str]         =							a + h * i
		result += function(_snake_case	) * (4 if i % 2 else 2)

	result *= h / 3
	return round(_snake_case	,  _snake_case	)


if __name__ == "__main__":
			import doctest

			doctest.testmod()





