

'''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


lowerCAmelCase__											=	logging.get_logger(__name__)

lowerCAmelCase__											=	{'''vocab_file''': '''sentencepiece.bpe.model'''}

lowerCAmelCase__											=	{
    '''vocab_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model''',
    }
}

lowerCAmelCase__											=	{
    '''camembert-base''': 512,
}

lowerCAmelCase__											=	'''▁'''






class 			lowercase_	(lowerCamelCase__      ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE    :  Optional[Any]							=			VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE    :  str							=			PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE    :  Dict							=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE    :  Union[str, Any]							=			['input_ids', 'attention_mask']






  def __init__(      self   :     Dict					,lowercase__   :     Optional[Any]					,lowercase__   :     Optional[int]="<s>"					,lowercase__   :     Any="</s>"					,lowercase__   :     Any="</s>"					,lowercase__   :     Any="<s>"					,lowercase__   :     List[str]="<unk>"					,lowercase__   :     List[Any]="<pad>"					,lowercase__   :     Optional[int]="<mask>"					,lowercase__   :     Optional[Any]=["<s>NOTUSED", "</s>NOTUSED"]					,lowercase__   :     Optional[Dict[str, Any]] = None					,**lowercase__   :     Optional[int]					,):
   # Mask token behave like a normal word, i.e. include the space before it
   __lowercase							  = AddedToken(lowercase__					,lstrip=lowercase__					,rstrip=lowercase__			) if isinstance(lowercase__					,lowercase__			) else mask_token

   __lowercase							  = {} if sp_model_kwargs is None else sp_model_kwargs

   super().__init__(
       bos_token=lowercase__					,eos_token=lowercase__					,unk_token=lowercase__					,sep_token=lowercase__					,cls_token=lowercase__					,pad_token=lowercase__					,mask_token=lowercase__					,additional_special_tokens=lowercase__					,sp_model_kwargs=self.sp_model_kwargs					,**lowercase__					,)
   __lowercase							  = spm.SentencePieceProcessor(**self.sp_model_kwargs			)
   self.sp_model.Load(str(lowercase__			)			)
   __lowercase							  = vocab_file
   # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
   # sentencepiece vocabulary (this is the case for <s> and </s>
   __lowercase							  = {'''<s>NOTUSED''': 0, '''<pad>''': 1, '''</s>NOTUSED''': 2, '''<unk>''': 3}
   __lowercase							  = len(self.fairseq_tokens_to_ids			)
   __lowercase							  = len(self.sp_model			) + len(self.fairseq_tokens_to_ids			)
   __lowercase							  = {v: k for k, v in self.fairseq_tokens_to_ids.items()}






  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]					,lowercase__   :     List[int]					,lowercase__   :     Optional[List[int]] = None			):

   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   :     List[Any]					,lowercase__   :     List[int]					,lowercase__   :     Optional[List[int]] = None					,lowercase__   :     bool = False			):
   if already_has_special_tokens:
    return super().get_special_tokens_mask(
        token_ids_a=lowercase__					,token_ids_a=lowercase__					,already_has_special_tokens=lowercase__			)

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






  def 					SCREAMING_SNAKE_CASE      (      self   :     Tuple					,lowercase__   :     List[int]					,lowercase__   :     Optional[List[int]] = None			):
   __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]






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     Dict			):
   return len(self.fairseq_tokens_to_ids			) + len(self.sp_model			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Tuple			):
   __lowercase							  = {self.convert_ids_to_tokens(lowercase__			): i for i in range(self.vocab_size			)}
   vocab.update(self.added_tokens_encoder			)
   return vocab






  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]					,lowercase__   :     str			):
   return self.sp_model.encode(lowercase__					,out_type=lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]					,lowercase__   :     Tuple			):
   if token in self.fairseq_tokens_to_ids:
    return self.fairseq_tokens_to_ids[token]
   elif self.sp_model.PieceToId(lowercase__			) == 0:
    # Convert sentence piece unk token to fairseq unk token index
    return self.unk_token_id
   return self.fairseq_offset + self.sp_model.PieceToId(lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]					,lowercase__   :     Optional[Any]			):
   if index in self.fairseq_ids_to_tokens:
    return self.fairseq_ids_to_tokens[index]
   return self.sp_model.IdToPiece(index - self.fairseq_offset			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     int					,lowercase__   :     Dict			):
   __lowercase							  = []
   __lowercase							  = ''''''
   __lowercase							  = 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(lowercase__			) + token
     __lowercase							  = True
     __lowercase							  = []
    else:
     current_sub_tokens.append(lowercase__			)
     __lowercase							  = False
   out_string += self.sp_model.decode(lowercase__			)
   return out_string.strip()






  def __getstate__(      self   :     Optional[Any]			):
   __lowercase							  = self.__dict__.copy()
   __lowercase							  = None
   return state






  def __setstate__(      self   :     Union[str, Any]					,lowercase__   :     Dict			):
   __lowercase							  = d

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

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






  def 					SCREAMING_SNAKE_CASE      (      self   :     Any					,lowercase__   :     str					,lowercase__   :     Optional[str] = None			):
   if not os.path.isdir(lowercase__			):
    logger.error(F"Vocabulary path ({save_directory}) should be a directory"			)
    return
   __lowercase							  = os.path.join(
       lowercase__					,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']			)

   if os.path.abspath(self.vocab_file			) != os.path.abspath(lowercase__			) and os.path.isfile(self.vocab_file			):
    copyfile(self.vocab_file					,lowercase__			)
   elif not os.path.isfile(self.vocab_file			):
    with open(lowercase__					,'''wb'''			) as fi:
     __lowercase							  = self.sp_model.serialized_model_proto()
     fi.write(lowercase__			)

   return (out_vocab_file,)




'''simple docstring'''






# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os
import subprocess

from packaging.version import Version, parse

from accelerate.commands.config.config_args import default_config_file, load_config_from_file


lowerCAmelCase__											=	'''Run commands across TPU VMs for initial setup before running `accelerate launch`.'''


def 		_A     (    A__=None      ):






 """simple docstring"""



 if subparsers is not None:
  __lowercase							  = subparsers.add_parser('''tpu-config'''     ,				description=_description      )
 else:
  __lowercase							  = argparse.ArgumentParser('''Accelerate tpu-config command'''     ,				description=_description      )
 # Core arguments
 __lowercase							  = parser.add_argument_group(
     '''Config Arguments'''     ,				'''Arguments that can be configured through `accelerate config`.'''      )
 config_args.add_argument(
     '''--config_file'''     ,				type=A__     ,				default=A__     ,				help='''Path to the config file to use for accelerate.'''     ,				)
 config_args.add_argument(
     '''--tpu_name'''     ,				default=A__     ,				help='''The name of the TPU to use. If not specified, will use the TPU specified in the config file.'''     ,				)
 config_args.add_argument(
     '''--tpu_zone'''     ,				default=A__     ,				help='''The zone of the TPU to use. If not specified, will use the zone specified in the config file.'''     ,				)
 __lowercase							  = parser.add_argument_group('''TPU Arguments'''     ,				'''Arguments for options ran inside the TPU.'''      )
 pod_args.add_argument(
     '''--use_alpha'''     ,				action='''store_true'''     ,				help='''Whether to use `gcloud alpha` when running the TPU training script instead of `gcloud`.'''     ,				)
 pod_args.add_argument(
     '''--command_file'''     ,				default=A__     ,				help='''The path to the file containing the commands to run on the pod on startup.'''     ,				)
 pod_args.add_argument(
     '''--command'''     ,				action='''append'''     ,				nargs='''+'''     ,				help='''A command to run on the pod. Can be passed multiple times.'''     ,				)
 pod_args.add_argument(
     '''--install_accelerate'''     ,				action='''store_true'''     ,				help='''Whether to install accelerate on the pod. Defaults to False.'''     ,				)
 pod_args.add_argument(
     '''--accelerate_version'''     ,				default='''latest'''     ,				help='''The version of accelerate to install on the pod. If not specified, will use the latest pypi version. Specify \'dev\' to install from GitHub.'''     ,				)
 pod_args.add_argument(
     '''--debug'''     ,				action='''store_true'''     ,				help='''If set, will print the command that would be run instead of running it.'''      )

 if subparsers is not None:
  parser.set_defaults(func=A__      )
 return parser


def 		_A     (    A__      ):






 """simple docstring"""



 __lowercase							  = None

 # Get the default from the config file if it exists.
 if args.config_file is not None or os.path.isfile(A__      ):
  __lowercase							  = load_config_from_file(args.config_file      )
  if not args.command_file and defaults.command_file is not None and not args.command:
   __lowercase							  = defaults.command_file
  if not args.command and defaults.commands is not None:
   __lowercase							  = defaults.commands
  if not args.tpu_name:
   __lowercase							  = defaults.tpu_name
  if not args.tpu_zone:
   __lowercase							  = defaults.tpu_zone
 if args.accelerate_version == "dev":
  __lowercase							  = '''git+https://github.com/huggingface/accelerate.git'''
 elif args.accelerate_version == "latest":
  __lowercase							  = '''accelerate -U'''
 elif isinstance(parse(args.accelerate_version      )     ,				A__      ):
  __lowercase							  = F"accelerate=={args.accelerate_version}"

 if not args.command_file and not args.command:
  raise ValueError('''You must specify either a command file or a command to run on the pod.'''      )

 if args.command_file:
  with open(args.command_file     ,				'''r'''      ) as f:
   __lowercase							  = [f.read().splitlines()]

    # To turn list of lists into list of strings
 if isinstance(args.command[0]     ,				A__      ):
  __lowercase							  = [line for cmd in args.command for line in cmd]
 # Default to the shared folder and install accelerate
 __lowercase							  = ['''cd /usr/share''']
 if args.install_accelerate:
  new_cmd += [F"pip install {args.accelerate_version}"]
 new_cmd += args.command
 __lowercase							  = '''; '''.join(A__      )

 # Then send it to gcloud
 # Eventually try to use google-api-core to do this instead of subprocess
 __lowercase							  = ['''gcloud''']
 if args.use_alpha:
  cmd += ["alpha"]
 cmd += [
     "compute",
     "tpus",
     "tpu-vm",
     "ssh",
     args.tpu_name,
     "--zone",
     args.tpu_zone,
     "--command",
     args.command,
     "--worker",
     "all",
 ]
 if args.debug:
  print(F"Running {' '.join(A__      )}"      )
  return
 subprocess.run(A__      )
 print('''Successfully setup pod.'''      )






def 		_A     (    ):






 """simple docstring"""



 __lowercase							  = tpu_command_parser()
 __lowercase							  = parser.parse_args()

 tpu_command_launcher(A__      )

