"""simple docstring"""




import argparse
import os

from accelerate.utils import ComputeEnvironment

from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file  # noqa: F401
from .config_utils import _ask_field, _ask_options, _convert_compute_environment  # noqa: F401
from .sagemaker import get_sagemaker_input


_a   :	List[str] 					=     'Launches a series of prompts to create and save a `default_config.yaml` configuration file for your training system. Should always be ran first on your machine'





def 							SCREAMING_SNAKE_CASE  (    ) ->   Union[str, Any]:
  _lowerCAmelCase		: Any						    =  _ask_options(
      """In which compute environment are you running?"""    ,["""This machine""", """AWS (Amazon SageMaker)"""]    ,_convert_compute_environment    ,)
  if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
    _lowerCAmelCase		: str						    =  get_sagemaker_input()
  else:
    _lowerCAmelCase		: Union[str, Any]						    =  get_cluster_input()
  return config





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: List[Any]=None			) ->   Optional[Any]:
  if subparsers is not None:
    _lowerCAmelCase		: Union[str, Any]						    =  subparsers.add_parser("""config"""    ,description=_lowerCamelCase			)
  else:
    _lowerCAmelCase		: Tuple						    =  argparse.ArgumentParser("""Accelerate config command"""    ,description=_lowerCamelCase			)

  parser.add_argument(
      """--config_file"""    ,default=_lowerCamelCase    ,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=_lowerCamelCase			)
  return parser





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Optional[int]			) ->   List[Any]:
  _lowerCAmelCase		: Optional[Any]						    =  get_user_input()
  if args.config_file is not None:
    _lowerCAmelCase		: Tuple						    =  args.config_file
  else:
    if not os.path.isdir(_lowerCamelCase			):
      os.makedirs(_lowerCamelCase			)
    _lowerCAmelCase		: List[Any]						    =  default_yaml_config_file

  if config_file.endswith(""".json"""			):
    config.to_json_file(_lowerCamelCase			)
  else:
    config.to_yaml_file(_lowerCamelCase			)
  print(f"accelerate configuration saved at {config_file}"			)





def 							SCREAMING_SNAKE_CASE  (    ) ->   int:
  _lowerCAmelCase		: List[str]						    =  config_command_parser()
  _lowerCAmelCase		: List[Any]						    =  parser.parse_args()
  config_command(_lowerCamelCase			)


if __name__ == "__main__":
     main()







"""simple docstring"""




import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class 		__A							(				SCREAMING_SNAKE_CASE_					,			unittest.TestCase	):
     _UpperCamelCase							:    str	      =	CpmAntTokenizer
     _UpperCamelCase							:    List[Any]	      =	False






     def 					__A						(	self						):
       super().setUp()

       _lowerCAmelCase		: Dict						    =  [
           """<d>""",
           """</d>""",
           """<s>""",
           """</s>""",
           """</_>""",
           """<unk>""",
           """<pad>""",
           """</n>""",
           """我""",
           """是""",
           """C""",
           """P""",
           """M""",
           """A""",
           """n""",
           """t""",
       ]
       _lowerCAmelCase		: int						    =  os.path.join(self.tmpdirname       ,  VOCAB_FILES_NAMES["""vocab_file"""]						)
       with open(self.vocab_file       ,  """w"""       ,  encoding="""utf-8"""						) as vocab_writer:
         vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]						)						)






     @tooslow
     def 					__A						(	self						):
       _lowerCAmelCase		: Tuple						    =  CpmAntTokenizer.from_pretrained("""openbmb/cpm-ant-10b"""						)
       _lowerCAmelCase		: Optional[Any]						    =  """今天天气真好！"""
       _lowerCAmelCase		: Any						    =  ["""今天""", """天气""", """真""", """好""", """！"""]
       _lowerCAmelCase		: str						    =  tokenizer.tokenize(a__						)
       self.assertListEqual(a__       ,  a__						)
       _lowerCAmelCase		: Tuple						    =  """今天天气真好！"""
       _lowerCAmelCase		: Optional[Any]						    =  [tokenizer.bos_token] + tokens

       _lowerCAmelCase		: Optional[int]						    =  [6, 9802, 14962, 2082, 831, 244]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(a__						)       ,  a__						)

       _lowerCAmelCase		: Tuple						    =  tokenizer.decode(a__						)
       self.assertEqual(a__       ,  a__						)




