


'''simple docstring'''

def _SCREAMING_SNAKE_CASE   (A						,				A ) -> list:






       """simple docstring"""







       lowercase__       =				sorted(A						,				key=lambda A : value[2]						,				reverse=A )

       # Create a list of size equal to the maximum deadline
       # and initialize it with -1
       lowercase__       =				max(A						,				key=lambda A : value[1] )[1]
       lowercase__       =				[-1] * max_deadline

       # Finding the maximum profit and the count of jobs
       lowercase__       =				0
       lowercase__       =				0
       for job in jobs:
              # Find a free time slot for this job
              # (Note that we start from the last possible slot)
              for i in range(job[1] - 1						,				-1						,				-1 ):
                     if time_slots[i] == -1:
                            lowercase__       =				job[0]
                            count += 1
                            max_profit += job[2]
                            break
       return [count, max_profit]


if __name__ == "__main__":
 import doctest

 doctest.testmod()








'''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:
 lowerCamelCase							:     Optional[int]								=			None

lowerCamelCase							:     List[Any]								=			logging.get_logger(__name__)
lowerCamelCase							:     Dict								=			{'vocab_file': 'tokenizer.model', 'tokenizer_file': 'tokenizer.json'}

lowerCamelCase		,						lowerCamelCase							:     str								=			'[INST]', '[/INST]'
lowerCamelCase		,						lowerCamelCase							:     Optional[Any]								=			'<<SYS>>\n', '\n<</SYS>>\n\n'

# fmt: off
lowerCamelCase							:     Optional[int]								=			'You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\\nanswers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\\nthat your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not\\ncorrect. If you don\'t know the answer to a question, please don\'t share false information.'
class 						__lowerCAmelCase		(lowercase_  ):





      '''simple docstring'''






      lowerCAmelCase__      :  int						      =							VOCAB_FILES_NAMES
      lowerCAmelCase__      :  List[str]						      =							LlamaTokenizer
      lowerCAmelCase__      :  Tuple						      =							"""left"""
      lowerCAmelCase__      :  int						      =							["""input_ids""", """attention_mask"""]



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

             '''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     ,		)
             lowercase__       =				add_bos_token
             lowercase__       =				add_eos_token
             self.update_post_processor()

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



      def    UpperCamelCase__	(self					:					Tuple				):

             '''simple docstring'''







             lowercase__       =				self.bos_token
             lowercase__       =				self.bos_token_id

             lowercase__       =				self.eos_token
             lowercase__       =				self.eos_token_id

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

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



      @property
      def    UpperCamelCase__	(self					:					Union[str, Any]				):

             '''simple docstring'''







             return self._add_eos_token



      @property
      def    UpperCamelCase__	(self					:					Tuple				):

             '''simple docstring'''







             return self._add_bos_token



      @add_eos_token.setter
      def    UpperCamelCase__	(self					:					Union[str, Any]     ,		UpperCamelCase					:					int				):

             '''simple docstring'''







             lowercase__       =				value
             self.update_post_processor()



      @add_bos_token.setter
      def    UpperCamelCase__	(self					:					Optional[Any]     ,		UpperCamelCase					:					Optional[int]				):

             '''simple docstring'''







             lowercase__       =				value
             self.update_post_processor()



      def    UpperCamelCase__	(self					:					Optional[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
             lowercase__       =				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    UpperCamelCase__	(self					:					str     ,		UpperCamelCase					:					"Conversation"				):

             '''simple docstring'''







             lowercase__       =				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...)'''				)

             lowercase__       =				[]
             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]:
                           lowercase__       =				(
                               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]:
                    lowercase__       =				(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




