
import os
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
					from transformers.pipelines.conversational import Conversation

lowerCamelCase__        =						logging.get_logger(__name__)

lowerCamelCase__        =						{"""vocab_file""": """tokenizer.model"""}

lowerCamelCase__        =						{
    """vocab_file""": {
        """hf-internal-testing/llama-tokenizer""": """https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer.model""",
    },
    """tokenizer_file""": {
        """hf-internal-testing/llama-tokenizer""": """https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer_config.json""",
    },
}
lowerCamelCase__        =						{
    """hf-internal-testing/llama-tokenizer""": 2048,
}
lowerCamelCase__        =						"""▁"""

lowerCamelCase__ ,   lowerCamelCase__        =						"""[INST]""", """[/INST]"""
lowerCamelCase__ ,   lowerCamelCase__        =						"""<<SYS>>\n""", """\n<</SYS>>\n\n"""

# fmt: off
lowerCamelCase__        =						"""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__				(	UpperCAmelCase__      ):
				lowercase            =    VOCAB_FILES_NAMES
				lowercase            =    PRETRAINED_VOCAB_FILES_MAP
				lowercase            =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowercase            =    ["input_ids", "attention_mask"]






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






							'''simple docstring'''







							lowerCAmelCase__ : List[str]   =						{} if sp_model_kwargs is None else sp_model_kwargs
							lowerCAmelCase__ : Any   =						AddedToken(lowerCamelCase__       ,	lstrip=lowerCamelCase__       ,	rstrip=lowerCamelCase__  ) if isinstance(lowerCamelCase__       ,	lowerCamelCase__  ) else bos_token
							lowerCAmelCase__ : Any   =						AddedToken(lowerCamelCase__       ,	lstrip=lowerCamelCase__       ,	rstrip=lowerCamelCase__  ) if isinstance(lowerCamelCase__       ,	lowerCamelCase__  ) else eos_token
							lowerCAmelCase__ : List[str]   =						AddedToken(lowerCamelCase__       ,	lstrip=lowerCamelCase__       ,	rstrip=lowerCamelCase__  ) if isinstance(lowerCamelCase__       ,	lowerCamelCase__  ) else unk_token
							lowerCAmelCase__ : Optional[int]   =						AddedToken(lowerCamelCase__       ,	lstrip=lowerCamelCase__       ,	rstrip=lowerCamelCase__  ) if isinstance(lowerCamelCase__       ,	lowerCamelCase__  ) else pad_token
							super().__init__(
							    bos_token=lowerCamelCase__       ,	eos_token=lowerCamelCase__       ,	unk_token=lowerCamelCase__       ,	pad_token=lowerCamelCase__       ,	add_bos_token=lowerCamelCase__       ,	add_eos_token=lowerCamelCase__       ,	sp_model_kwargs=self.sp_model_kwargs       ,	clean_up_tokenization_spaces=lowerCamelCase__       ,	legacy=lowerCamelCase__       ,	**lowerCamelCase__       ,	)
							if legacy:
										logger.warning_once(
										    f'''You are using the legacy behaviour of the {self.__class__}. This means that tokens that come after special tokens will not be properly handled. We recommend you to'''
										    ' read the related pull request available at https://github.com/huggingface/transformers/pull/24565'  )
							lowerCAmelCase__ : int   =						legacy
							lowerCAmelCase__ : Optional[int]   =						vocab_file
							lowerCAmelCase__ : str   =						add_bos_token
							lowerCAmelCase__ : Tuple   =						add_eos_token
							lowerCAmelCase__ : int   =						spm.SentencePieceProcessor(**self.sp_model_kwargs  )
							self.sp_model.Load(lowerCamelCase__  )






				def __getstate__(		self   : Optional[int]  ):






							'''simple docstring'''







							lowerCAmelCase__ : List[str]   =						self.__dict__.copy()
							lowerCAmelCase__ : Dict   =						None
							lowerCAmelCase__ : Any   =						self.sp_model.serialized_model_proto()
							return state






				def __setstate__(		self   : Optional[Any]       ,	a   : Tuple  ):






							'''simple docstring'''







							lowerCAmelCase__ : Optional[int]   =						d
							lowerCAmelCase__ : Any   =						spm.SentencePieceProcessor(**self.sp_model_kwargs  )
							self.sp_model.LoadFromSerializedProto(self.sp_model_proto  )






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






							'''simple docstring'''







							return self.sp_model.get_piece_size()






				def 				_lowerCamelCase						(		self   : Optional[Any]  ):






							'''simple docstring'''







							lowerCAmelCase__ : Dict   =						{self.convert_ids_to_tokens(lowerCamelCase__  ): i for i in range(self.vocab_size  )}
							vocab.update(self.added_tokens_encoder  )
							return vocab






				def 				_lowerCamelCase						(		self   : int       ,	a   : List[Any]       ,	**a   : Any  ):






							'''simple docstring'''







							if not self.legacy:
										lowerCAmelCase__ : List[str]   =						SPIECE_UNDERLINE + text.replace(lowerCamelCase__       ,	' '  )
							return super().tokenize(lowerCamelCase__       ,	**lowerCamelCase__  )






				def 				_lowerCamelCase						(		self   : Any       ,	a   : Optional[Any]  ):






							'''simple docstring'''







							if not self.legacy:
										lowerCAmelCase__ : str   =						text.startswith(lowerCamelCase__  )
										if is_first:
													lowerCAmelCase__ : Dict   =						text[1:]

							lowerCAmelCase__ : Dict   =						self.sp_model.encode(lowerCamelCase__       ,	out_type=lowerCamelCase__  )

							if not self.legacy and not is_first and not text.startswith(' '  ) and tokens[0].startswith(lowerCamelCase__  ):
										lowerCAmelCase__ : Tuple   =						([tokens[0][1:]] if len(tokens[0]  ) > 1 else []) + tokens[1:]
							return tokens






				def 				_lowerCamelCase						(		self   : int       ,	a   : Any  ):






							'''simple docstring'''







							return self.sp_model.piece_to_id(lowerCamelCase__  )






				def 				_lowerCamelCase						(		self   : List[str]       ,	a   : List[Any]  ):






							'''simple docstring'''







							lowerCAmelCase__ : List[Any]   =						self.sp_model.IdToPiece(lowerCamelCase__  )
							return token






				def 				_lowerCamelCase						(		self   : List[str]       ,	a   : int  ):






							'''simple docstring'''







							lowerCAmelCase__ : Any   =						[]
							lowerCAmelCase__ : Dict   =						""
							lowerCAmelCase__ : List[Any]   =						False
							for i, token in enumerate(lowerCamelCase__  ):
										# make sure that special tokens are not decoded using sentencepiece model
										if token in self.all_special_tokens:
													if not prev_is_special and i != 0:
																out_string += " "
													out_string += self.sp_model.decode(lowerCamelCase__  ) + token
													lowerCAmelCase__ : int   =						True
													lowerCAmelCase__ : Any   =						[]
										else:
													current_sub_tokens.append(lowerCamelCase__  )
													lowerCAmelCase__ : Dict   =						False
							out_string += self.sp_model.decode(lowerCamelCase__  )
							return out_string






				def 				_lowerCamelCase						(		self   : List[str]       ,	a   : Any       ,	a   : Optional[str] = None  ):






							'''simple docstring'''







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

							if os.path.abspath(self.vocab_file  ) != os.path.abspath(lowerCamelCase__  ) and os.path.isfile(self.vocab_file  ):
										copyfile(self.vocab_file       ,	lowerCamelCase__  )
							elif not os.path.isfile(self.vocab_file  ):
										with open(lowerCamelCase__       ,	'wb'  ) as fi:
													lowerCAmelCase__ : Union[str, Any]   =						self.sp_model.serialized_model_proto()
													fi.write(lowerCamelCase__  )

							return (out_vocab_file,)






				def 				_lowerCamelCase						(		self   : Tuple       ,	a   : Union[str, Any]       ,	a   : Optional[int]=None  ):






							'''simple docstring'''







							lowerCAmelCase__ : str   =						[self.bos_token_id] if self.add_bos_token else []
							lowerCAmelCase__ : List[str]   =						[self.eos_token_id] if self.add_eos_token else []

							lowerCAmelCase__ : int   =						bos_token_id + token_ids_a + eos_token_id

							if token_ids_a is not None:
										lowerCAmelCase__ : Dict   =						output + bos_token_id + token_ids_a + eos_token_id

							return output






				def 				_lowerCamelCase						(		self   : Dict       ,	a   : List[int]       ,	a   : Optional[List[int]] = None       ,	a   : bool = False  ):






							'''simple docstring'''







							if already_has_special_tokens:
										return super().get_special_tokens_mask(
										    token_ids_a=lowerCamelCase__       ,	token_ids_a=lowerCamelCase__       ,	already_has_special_tokens=lowerCamelCase__  )

							lowerCAmelCase__ : Optional[int]   =						[1] if self.add_bos_token else []
							lowerCAmelCase__ : Dict   =						[1] if self.add_eos_token else []

							if token_ids_a is None:
										return bos_token_id + ([0] * len(lowerCamelCase__  )) + eos_token_id
							return (
							    bos_token_id
							    + ([0] * len(lowerCamelCase__  ))
							    + eos_token_id
							    + bos_token_id
							    + ([0] * len(lowerCamelCase__  ))
							    + eos_token_id
							)






				def 				_lowerCamelCase						(		self   : str       ,	a   : List[int]       ,	a   : Optional[List[int]] = None  ):






							'''simple docstring'''







							lowerCAmelCase__ : List[str]   =						[self.bos_token_id] if self.add_bos_token else []
							lowerCAmelCase__ : int   =						[self.eos_token_id] if self.add_eos_token else []

							lowerCAmelCase__ : Optional[Any]   =						[0] * len(bos_token_id + token_ids_a + eos_token_id  )

							if token_ids_a is not None:
										output += [1] * len(bos_token_id + token_ids_a + eos_token_id  )

							return output






				def 				_lowerCamelCase						(		self   : Union[str, Any]       ,	a   : "Conversation"  ):






							'''simple docstring'''







							lowerCAmelCase__ : str   =						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__ : List[int]   =						[]
							if len(conversation.past_user_inputs  ) > 0:
										if not conversation.past_user_inputs[0].startswith(lowerCamelCase__  ) or E_SYS not in conversation.past_user_inputs[0]:
													lowerCAmelCase__ : List[str]   =						(
													    B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
													)
							elif not dialogue[0][1].startswith(lowerCamelCase__  ) or E_SYS not in dialogue[0][1]:
										lowerCAmelCase__ : Tuple   =						(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=lowerCamelCase__  )
							        + [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=lowerCamelCase__  )
							return dialog_tokens



'''simple docstring'''


import io
import json
import subprocess


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

lowerCamelCase__     						=  8






def 			__lowerCAmelCase			(__lowerCAmelCase   ,			__lowerCAmelCase ):
		_UpperCAmelCase		:							List[str]             =   {}
		for src, tgt in pairs:
				_UpperCAmelCase		:							Tuple             =   F"""{src}-{tgt}"""
				_UpperCAmelCase		:							Tuple             =   F"""sacrebleu -t wmt19 -l {pair} --echo src""".split()
				_UpperCAmelCase		:							List[Any]             =   subprocess.run(__lowerCAmelCase   ,			stdout=subprocess.PIPE ).stdout.decode("utf-8" ).splitlines()
				_UpperCAmelCase		:							Tuple             =   F"""sacrebleu -t wmt19 -l {pair} --echo ref""".split()
				_UpperCAmelCase		:							List[str]             =   subprocess.run(__lowerCAmelCase   ,			stdout=subprocess.PIPE ).stdout.decode("utf-8" ).splitlines()
				_UpperCAmelCase		:							Tuple             =   {"src": src_lines[:n_objs], "tgt": tgt_lines[:n_objs]}
		return text


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



