



import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


a__   :					Any 						=      logging.get_logger(__name__)

a__   :					Any 						=      {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

a__   :					Dict 						=      {
    "vocab_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/vocab.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/vocab.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/vocab.json",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/merges.txt",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/merges.txt",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/merges.txt",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/tokenizer.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/tokenizer.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json",
        "roberta-base-openai-detector": (
            "https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json"
        ),
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json"
        ),
    },
}

a__   :					Union[str, Any] 						=      {
    "roberta-base": 5_12,
    "roberta-large": 5_12,
    "roberta-large-mnli": 5_12,
    "distilroberta-base": 5_12,
    "roberta-base-openai-detector": 5_12,
    "roberta-large-openai-detector": 5_12,
}



class    UpperCAmelCase__(				lowerCamelCase						):

   '''simple docstring'''




   A     :	Optional[int]												=     VOCAB_FILES_NAMES
   A     :	Tuple												=     PRETRAINED_VOCAB_FILES_MAP
   A     :	Optional[int]												=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A     :	int												=     ["input_ids", "attention_mask"]
   A     :	Union[str, Any]												=     RobertaTokenizer


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




         """simple docstring"""

         super().__init__(
             lowerCAmelCase      ,					lowerCAmelCase      ,					tokenizer_file=lowerCAmelCase      ,					errors=lowerCAmelCase      ,					bos_token=lowerCAmelCase      ,					eos_token=lowerCAmelCase      ,					sep_token=lowerCAmelCase      ,					cls_token=lowerCAmelCase      ,					unk_token=lowerCAmelCase      ,					pad_token=lowerCAmelCase      ,					mask_token=lowerCAmelCase      ,					add_prefix_space=lowerCAmelCase      ,					trim_offsets=lowerCAmelCase      ,					**lowerCAmelCase      ,					)

         lowercase__  =	json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
         if pre_tok_state.get('add_prefix_space'      ,					lowerCAmelCase) != add_prefix_space:
               lowercase__  =	getattr(lowerCAmelCase      ,					pre_tok_state.pop('type'))
               lowercase__  =	add_prefix_space
               lowercase__  =	pre_tok_class(**lowerCAmelCase)

         lowercase__  =	add_prefix_space

         lowercase__  =	'post_processor'
         lowercase__  =	getattr(self.backend_tokenizer      ,					lowerCAmelCase      ,					lowerCAmelCase)
         if tokenizer_component_instance:
               lowercase__  =	json.loads(tokenizer_component_instance.__getstate__())

               # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
               if "sep" in state:
                     lowercase__  =	tuple(state['sep'])
               if "cls" in state:
                     lowercase__  =	tuple(state['cls'])

               lowercase__  =	False

               if state.get('add_prefix_space'      ,					lowerCAmelCase) != add_prefix_space:
                     lowercase__  =	add_prefix_space
                     lowercase__  =	True

               if state.get('trim_offsets'      ,					lowerCAmelCase) != trim_offsets:
                     lowercase__  =	trim_offsets
                     lowercase__  =	True

               if changes_to_apply:
                     lowercase__  =	getattr(lowerCAmelCase      ,					state.pop('type'))
                     lowercase__  =	component_class(**lowerCAmelCase)
                     setattr(self.backend_tokenizer      ,					lowerCAmelCase      ,					lowerCAmelCase)


   @property
   def       UpperCAmelCase		(    self	:      Optional[Any])						->					str:




         """simple docstring"""

         if self._mask_token is None:
               if self.verbose:
                     logger.error('Using mask_token, but it is not set yet.')
               return None
         return str(self._mask_token)


   @mask_token.setter
   def       UpperCAmelCase		(    self	:      List[str]      ,					lowerCAmelCase	:      Optional[Any])						->					int:




         """simple docstring"""

         lowercase__  =	AddedToken(lowerCAmelCase      ,					lstrip=lowerCAmelCase      ,					rstrip=lowerCAmelCase) if isinstance(lowerCAmelCase      ,					lowerCAmelCase) else value
         lowercase__  =	value


   def       UpperCAmelCase		(    self	:      List[Any]      ,					*lowerCAmelCase	:      str      ,					**lowerCAmelCase	:      Any)						->					BatchEncoding:




         """simple docstring"""

         lowercase__  =	kwargs.get('is_split_into_words'      ,					lowerCAmelCase)
         assert self.add_prefix_space or not is_split_into_words, (
             f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
             "to use it with pretokenized inputs."
         )

         return super()._batch_encode_plus(*lowerCAmelCase      ,					**lowerCAmelCase)


   def       UpperCAmelCase		(    self	:      str      ,					*lowerCAmelCase	:      Optional[Any]      ,					**lowerCAmelCase	:      Optional[Any])						->					BatchEncoding:




         """simple docstring"""

         lowercase__  =	kwargs.get('is_split_into_words'      ,					lowerCAmelCase)

         assert self.add_prefix_space or not is_split_into_words, (
             f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
             "to use it with pretokenized inputs."
         )

         return super()._encode_plus(*lowerCAmelCase      ,					**lowerCAmelCase)


   def       UpperCAmelCase		(    self	:      Optional[Any]      ,					lowerCAmelCase	:      str      ,					lowerCAmelCase	:      Optional[str] = None)						->					Tuple[str]:




         """simple docstring"""

         lowercase__  =	self._tokenizer.model.save(lowerCAmelCase      ,					name=lowerCAmelCase)
         return tuple(lowerCAmelCase)


   def       UpperCAmelCase		(    self	:      List[Any]      ,					lowerCAmelCase	:      List[str]      ,					lowerCAmelCase	:      Any=None)						->					Optional[Any]:




         """simple docstring"""

         lowercase__  =	[self.bos_token_id] + token_ids_a + [self.eos_token_id]
         if token_ids_a is None:
               return output

         return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]



   def       UpperCAmelCase		(    self	:      Any      ,					lowerCAmelCase	:      List[int]      ,					lowerCAmelCase	:      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]





# Copyright 2021 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

from accelerate.test_utils import execute_subprocess_async

def 	_lowerCAmelCase (    A__=None						):
      if subparsers is not None:
            lowercase__  =	subparsers.add_parser('test'						)
      else:
            lowercase__  =	argparse.ArgumentParser('Accelerate test command'						)

      parser.add_argument(
          '--config_file'    ,	default=A__    ,	help=(
              'The path to use to store the config file. Will default to a file named default_config.yaml in the cache '
              'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
              'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
              'with \'huggingface\'.'
          )    ,	)

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

def 	_lowerCAmelCase (    A__						):
      lowercase__  =	os.path.sep.join(__file__.split(os.path.sep						)[:-2] + ['test_utils', 'scripts', 'test_script.py']						)

      if args.config_file is None:
            lowercase__  =	script_name
      else:
            lowercase__  =	F'''--config_file={args.config_file} {script_name}'''

      lowercase__  =	['accelerate-launch'] + test_args.split()
      lowercase__  =	execute_subprocess_async(A__    ,	env=os.environ.copy()						)
      if result.returncode == 0:
            print('Test is a success! You are ready for your distributed training!'						)

def 	_lowerCAmelCase (    ):
      lowercase__  =	test_command_parser()
      lowercase__  =	parser.parse_args()
      test_command(A__						)


if __name__ == "__main__":
       main()
