
"""simple docstring"""


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

import sentencepiece as spm

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


SCREAMING_SNAKE_CASE      =     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE      =     {"""vocab_file""": """sentencepiece.bpe.model"""}

SCREAMING_SNAKE_CASE      =     {
    """vocab_file""": {
        """moussaKam/mbarthez""": """https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez""": """https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez-orangesum-title""": (
            """https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model"""
        ),
    },
}

SCREAMING_SNAKE_CASE      =     {
    """moussaKam/mbarthez""": 1_024,
    """moussaKam/barthez""": 1_024,
    """moussaKam/barthez-orangesum-title""": 1_024,
}

SCREAMING_SNAKE_CASE      =     """▁"""



class   __a  (      _lowerCAmelCase	):
       UpperCamelCase_		:					Union[str, Any]   =			VOCAB_FILES_NAMES
       UpperCamelCase_		:					Tuple   =			PRETRAINED_VOCAB_FILES_MAP
       UpperCamelCase_		:					Tuple   =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCamelCase_		:					Any   =			['''input_ids''', '''attention_mask''']






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







              """simple docstring"""
              # Mask token behave like a normal word, i.e. include the space before it
              UpperCamelCase					 =		AddedToken(UpperCAmelCase_       ,      lstrip=UpperCAmelCase_       ,      rstrip=UpperCAmelCase_			) if isinstance(UpperCAmelCase_       ,      UpperCAmelCase_			) else mask_token

              UpperCamelCase					 =		{} if sp_model_kwargs is None else sp_model_kwargs

              super().__init__(
                  bos_token=UpperCAmelCase_       ,      eos_token=UpperCAmelCase_       ,      unk_token=UpperCAmelCase_       ,      sep_token=UpperCAmelCase_       ,      cls_token=UpperCAmelCase_       ,      pad_token=UpperCAmelCase_       ,      mask_token=UpperCAmelCase_       ,      sp_model_kwargs=self.sp_model_kwargs       ,      **UpperCAmelCase_       ,      )

              UpperCamelCase					 =		vocab_file
              UpperCamelCase					 =		spm.SentencePieceProcessor(**self.sp_model_kwargs			)
              self.sp_model.Load(str(UpperCAmelCase_			)			)

              UpperCamelCase					 =		{"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

              UpperCamelCase					 =		len(self.sp_model			) - 1
              UpperCamelCase					 =		{v: k for k, v in self.fairseq_tokens_to_ids.items()}






       def 	_SCREAMING_SNAKE_CASE       (  self :							Union[str, Any]       ,      UpperCAmelCase_ :							List[int]       ,      UpperCAmelCase_ :							Optional[List[int]] = None			)->  List[int]:







              """simple docstring"""

              if token_ids_a is None:
                     return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
              UpperCamelCase					 =		[self.cls_token_id]
              UpperCamelCase					 =		[self.sep_token_id]
              return cls + token_ids_a + sep + sep + token_ids_a + sep






       def 	_SCREAMING_SNAKE_CASE       (  self :							List[str]       ,      UpperCAmelCase_ :							List[int]       ,      UpperCAmelCase_ :							Optional[List[int]] = None       ,      UpperCAmelCase_ :							bool = False			)->  List[int]:







              """simple docstring"""
              if already_has_special_tokens:
                     return super().get_special_tokens_mask(
                         token_ids_a=UpperCAmelCase_       ,      token_ids_a=UpperCAmelCase_       ,      already_has_special_tokens=UpperCAmelCase_			)

              if token_ids_a is None:
                     return [1] + ([0] * len(UpperCAmelCase_			)) + [1]
              return [1] + ([0] * len(UpperCAmelCase_			)) + [1, 1] + ([0] * len(UpperCAmelCase_			)) + [1]






       def 	_SCREAMING_SNAKE_CASE       (  self :							List[Any]       ,      UpperCAmelCase_ :							List[int]       ,      UpperCAmelCase_ :							Optional[List[int]] = None			)->  List[int]:







              """simple docstring"""
              UpperCamelCase					 =		[self.sep_token_id]
              UpperCamelCase					 =		[self.cls_token_id]

              if token_ids_a is None:
                     return len(cls + token_ids_a + sep			) * [0]
              return len(cls + token_ids_a + sep + sep + token_ids_a + sep			) * [0]






       @property
       def 	_SCREAMING_SNAKE_CASE       (  self :							Dict			)->  Dict:







              """simple docstring"""
              return len(self.sp_model			)






       def 	_SCREAMING_SNAKE_CASE       (  self :							Union[str, Any]			)->  Tuple:







              """simple docstring"""
              UpperCamelCase					 =		{self.convert_ids_to_tokens(UpperCAmelCase_			): i for i in range(self.vocab_size			)}
              vocab.update(self.added_tokens_encoder			)
              return vocab






       def 	_SCREAMING_SNAKE_CASE       (  self :							Union[str, Any]       ,      UpperCAmelCase_ :							str			)->  List[str]:







              """simple docstring"""
              return self.sp_model.encode(UpperCAmelCase_       ,      out_type=UpperCAmelCase_			)






       def 	_SCREAMING_SNAKE_CASE       (  self :							List[str]       ,      UpperCAmelCase_ :							int			)->  Optional[Any]:







              """simple docstring"""
              if token in self.fairseq_tokens_to_ids:
                     return self.fairseq_tokens_to_ids[token]
              UpperCamelCase					 =		self.sp_model.PieceToId(UpperCAmelCase_			)

              return spm_id if spm_id else self.unk_token_id






       def 	_SCREAMING_SNAKE_CASE       (  self :							Dict       ,      UpperCAmelCase_ :							List[str]			)->  int:







              """simple docstring"""
              if index in self.fairseq_ids_to_tokens:
                     return self.fairseq_ids_to_tokens[index]
              return self.sp_model.IdToPiece(UpperCAmelCase_			)






       def 	_SCREAMING_SNAKE_CASE       (  self :							List[str]       ,      UpperCAmelCase_ :							List[Any]			)->  str:







              """simple docstring"""
              UpperCamelCase					 =		[]
              UpperCamelCase					 =		""
              UpperCamelCase					 =		False
              for token in tokens:
                     # make sure that special tokens are not decoded using sentencepiece model
                     if token in self.all_special_tokens:
                            if not prev_is_special:
                                   out_string += " "
                            out_string += self.sp_model.decode(UpperCAmelCase_			) + token
                            UpperCamelCase					 =		True
                            UpperCamelCase					 =		[]
                     else:
                            current_sub_tokens.append(UpperCAmelCase_			)
                            UpperCamelCase					 =		False
              out_string += self.sp_model.decode(UpperCAmelCase_			)
              return out_string.strip()






       def __getstate__(  self :							str			)->  Union[str, Any]:







              """simple docstring"""
              UpperCamelCase					 =		self.__dict__.copy()
              UpperCamelCase					 =		None
              return state






       def __setstate__(  self :							List[str]       ,      UpperCAmelCase_ :							int			)->  List[str]:







              """simple docstring"""
              UpperCamelCase					 =		d

              # for backward compatibility
              if not hasattr(self       ,      "sp_model_kwargs"			):
                     UpperCamelCase					 =		{}

              UpperCamelCase					 =		spm.SentencePieceProcessor(**self.sp_model_kwargs			)
              self.sp_model.Load(self.vocab_file			)






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







              """simple docstring"""
              if not os.path.isdir(UpperCAmelCase_			):
                     logger.error(f"Vocabulary path ({save_directory}) should be a directory"			)
                     return
              UpperCamelCase					 =		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_			) and os.path.isfile(self.vocab_file			):
                     copyfile(self.vocab_file       ,      UpperCAmelCase_			)
              elif not os.path.isfile(self.vocab_file			):
                     with open(UpperCAmelCase_       ,      "wb"			) as fi:
                            UpperCamelCase					 =		self.sp_model.serialized_model_proto()
                            fi.write(UpperCAmelCase_			)

              return (out_vocab_file,)







"""simple docstring"""


import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment



@require_huggingface_suite
class   __a  (      unittest.TestCase	):






       def 	_SCREAMING_SNAKE_CASE       (  self :							Optional[int]			)->  Dict:







              """simple docstring"""
              UpperCamelCase					 =		inspect.getfile(accelerate.test_utils			)
              UpperCamelCase					 =		os.path.sep.join(
                  mod_file.split(os.path.sep			)[:-1] + ["scripts", "external_deps", "test_metrics.py"]			)

              from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

              UpperCamelCase					 =		test_metrics






       @require_cpu
       def 	_SCREAMING_SNAKE_CASE       (  self :							Dict			)->  Union[str, Any]:







              """simple docstring"""
              debug_launcher(self.test_metrics.main       ,      num_processes=1			)






       @require_cpu
       def 	_SCREAMING_SNAKE_CASE       (  self :							Tuple			)->  List[str]:







              """simple docstring"""
              debug_launcher(self.test_metrics.main			)






       @require_single_gpu
       def 	_SCREAMING_SNAKE_CASE       (  self :							List[Any]			)->  str:







              """simple docstring"""
              self.test_metrics.main()






       @require_multi_gpu
       def 	_SCREAMING_SNAKE_CASE       (  self :							Optional[Any]			)->  Optional[Any]:







              """simple docstring"""
              print(f"Found {torch.cuda.device_count()} devices."			)
              UpperCamelCase					 =		["torchrun", f"--nproc_per_node={torch.cuda.device_count()}", self.test_file_path]
              with patch_environment(omp_num_threads=1			):
                     execute_subprocess_async(UpperCAmelCase_       ,      env=os.environ.copy()			)





