





"""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_     :      Optional[Any]								=None

A_     :      Any								=logging.get_logger(__name__)
A_     :      Optional[int]								={"""vocab_file""": """tokenizer.model""", """tokenizer_file""": """tokenizer.json"""}

A_							,	A_     :      Optional[int]								="""[INST]""", """[/INST]"""
A_							,	A_     :      Any								="""<<SYS>>\n""", """\n<</SYS>>\n\n"""

# fmt: off
A_     :      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 	__a   (  lowerCAmelCase_		):
     SCREAMING_SNAKE_CASE__ :      Optional[Any]       		=			VOCAB_FILES_NAMES
     SCREAMING_SNAKE_CASE__ :      List[Any]       		=			LlamaTokenizer
     SCREAMING_SNAKE_CASE__ :      str       		=			'''left'''
     SCREAMING_SNAKE_CASE__ :      Tuple       		=			['''input_ids''', '''attention_mask''']



     def __init__(       self					,     a__=None					,     a__=None					,     a__=False					,     a__="<unk>"					,     a__="<s>"					,     a__="</s>"					,     a__=True					,     a__=False					,     **a__					,     ):
            super().__init__(
                vocab_file=_SCREAMING_SNAKE_CASE					,     tokenizer_file=_SCREAMING_SNAKE_CASE					,     clean_up_tokenization_spaces=_SCREAMING_SNAKE_CASE					,     unk_token=_SCREAMING_SNAKE_CASE					,     bos_token=_SCREAMING_SNAKE_CASE					,     eos_token=_SCREAMING_SNAKE_CASE					,     **_SCREAMING_SNAKE_CASE					,     )
            _lowerCamelCase    	=					add_bos_token
            _lowerCamelCase    	=					add_eos_token
            self.update_post_processor()

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



     def 						snake_case_			(       self   ):
            _lowerCamelCase    	=					self.bos_token
            _lowerCamelCase    	=					self.bos_token_id

            _lowerCamelCase    	=					self.eos_token
            _lowerCamelCase    	=					self.eos_token_id

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

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



     @property
     def 						snake_case_			(       self   ):
            return self._add_eos_token



     @property
     def 						snake_case_			(       self   ):
            return self._add_bos_token



     @add_eos_token.setter
     def 						snake_case_			(       self					,     a__   ):
            _lowerCamelCase    	=					value
            self.update_post_processor()



     @add_bos_token.setter
     def 						snake_case_			(       self					,     a__   ):
            _lowerCamelCase    	=					value
            self.update_post_processor()



     def 						snake_case_			(       self					,     a__					,     a__ = None   ):


            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(_SCREAMING_SNAKE_CASE   ):
                   logger.error(F'Vocabulary path ({save_directory}) should be a directory'   )
                   return
            _lowerCamelCase    	=					os.path.join(
                _SCREAMING_SNAKE_CASE					,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

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

            return (out_vocab_file,)



     def 						snake_case_			(       self					,     a__   ):
            _lowerCamelCase    	=					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...)'   )

            _lowerCamelCase    	=					[]
            if len(conversation.past_user_inputs   ) > 0:
                   if not conversation.past_user_inputs[0].startswith(_SCREAMING_SNAKE_CASE   ) or E_SYS not in conversation.past_user_inputs[0]:
                          _lowerCamelCase    	=					(
                              B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
                          )
            elif not dialogue[0][1].startswith(_SCREAMING_SNAKE_CASE   ) or E_SYS not in dialogue[0][1]:
                   _lowerCamelCase    	=					(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=_SCREAMING_SNAKE_CASE   )
                    + [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=_SCREAMING_SNAKE_CASE   )
            return dialog_tokens













import io
import json
import subprocess


_UpperCAmelCase				       = [
    ['en', 'ru'],
    ['ru', 'en'],
    ['en', 'de'],
    ['de', 'en'],
]

_UpperCAmelCase				       = 8




def        lowerCAmelCase_       (							UpperCamelCase_    ,						UpperCamelCase_     )   ->						Union[str, Any]:
       UpperCamelCase_      				=     {}
       for src, tgt in pairs:
              UpperCamelCase_      				=     F'''{src}-{tgt}'''
              UpperCamelCase_      				=     F'''sacrebleu -t wmt19 -l {pair} --echo src'''.split()
              UpperCamelCase_      				=     subprocess.run(UpperCamelCase_    ,						stdout=subprocess.PIPE     ).stdout.decode("utf-8"     ).splitlines()
              UpperCamelCase_      				=     F'''sacrebleu -t wmt19 -l {pair} --echo ref'''.split()
              UpperCamelCase_      				=     subprocess.run(UpperCamelCase_    ,						stdout=subprocess.PIPE     ).stdout.decode("utf-8"     ).splitlines()
              UpperCamelCase_      				=     {"src": src_lines[:n_objs], "tgt": tgt_lines[:n_objs]}
       return text


_UpperCAmelCase				       = get_all_data(pairs, n_objs)
_UpperCAmelCase				       = './fsmt_val_data.json'
with io.open(filename, 'w', encoding='utf-8') as f:
     _UpperCAmelCase				       = json.dump(text, f, indent=2, ensure_ascii=False)

