





import os
import sys

import transformers


lowercase_          =		'3'

print("""Python version:""", sys.version)
print("""transformers version:""", transformers.__version__)

try:
      import torch

      print("""Torch version:""", torch.__version__)
      print("""Cuda available:""", torch.cuda.is_available())
      print("""Cuda version:""", torch.version.cuda)
      print("""CuDNN version:""", torch.backends.cudnn.version())
      print("""Number of GPUs available:""", torch.cuda.device_count())
      print("""NCCL version:""", torch.cuda.nccl.version())
except ImportError:
      print("""Torch version:""", None)

try:
      import deepspeed

      print("""DeepSpeed version:""", deepspeed.__version__)
except ImportError:
      print("""DeepSpeed version:""", None)

try:
      import tensorflow as tf

      print("""TensorFlow version:""", tf.__version__)
      print("""TF GPUs available:""", bool(tf.config.list_physical_devices("""GPU""")))
      print("""Number of TF GPUs available:""", len(tf.config.list_physical_devices("""GPU""")))
except ImportError:
      print("""TensorFlow version:""", None)









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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_camembert import CamembertTokenizer
else:
      lowercase_          =		None


lowercase_          =		logging.get_logger(__name__)

lowercase_          =		{"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

lowercase_          =		{
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    },
    """tokenizer_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/tokenizer.json""",
    },
}

lowercase_          =		{
    """camembert-base""": 512,
}

lowercase_          =		"""▁"""
class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   _UpperCamelCase   :		int			 =	VOCAB_FILES_NAMES
   _UpperCamelCase   :		Dict			 =	PRETRAINED_VOCAB_FILES_MAP
   _UpperCamelCase   :		Dict			 =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _UpperCamelCase   :		Dict			 =	['input_ids', 'attention_mask']
   _UpperCamelCase   :		Optional[int]			 =	CamembertTokenizer


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





     """simple docstring"""







     lowercase__           =  AddedToken(a      ,					lstrip=a      ,					rstrip=a	) if isinstance(a      ,					a	) else mask_token

     super().__init__(
         a      ,					tokenizer_file=a      ,					bos_token=a      ,					eos_token=a      ,					sep_token=a      ,					cls_token=a      ,					unk_token=a      ,					pad_token=a      ,					mask_token=a      ,					additional_special_tokens=a      ,					**a      ,					)

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


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    List[int]      ,					a      :    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]
     lowercase__           =  [self.cls_token_id]
     lowercase__           =  [self.sep_token_id]
     return cls + token_ids_a + sep + sep + token_ids_a + sep


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





     """simple docstring"""







     lowercase__           =  [self.sep_token_id]
     lowercase__           =  [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]


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[int]      ,					a      :    str      ,					a      :    Optional[str] = None	)->       Tuple[str]:





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

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

     return (out_vocab_file,)


