





"""simple docstring"""
import subprocess
import sys

from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase__	(     __UpperCamelCase					):



   @require_torch
   def  _UpperCAmelCase						(							self						)			->     Optional[int]:







      """simple docstring"""
      lowercase     :      str	=							"""\nfrom transformers import BertConfig, BertModel, BertTokenizer, pipeline\n        """

      lowercase     :      Tuple	=							"""\nmname = \"hf-internal-testing/tiny-random-bert\"\nBertConfig.from_pretrained(mname)\nBertModel.from_pretrained(mname)\nBertTokenizer.from_pretrained(mname)\npipe = pipeline(task=\"fill-mask\", model=mname)\nprint(\"success\")\n        """

      lowercase     :      List[Any]	=							"""\nimport socket\ndef offline_socket(*args, **kwargs): raise RuntimeError(\"Offline mode is enabled, we shouldn\'t access internet\")\nsocket.socket = offline_socket\n        """

      # Force fetching the files so that we can use the cache
      lowercase     :      List[str]	=							"""hf-internal-testing/tiny-random-bert"""
      BertConfig.from_pretrained(snake_case__						)
      BertModel.from_pretrained(snake_case__						)
      BertTokenizer.from_pretrained(snake_case__						)
      pipeline(task="""fill-mask"""   , model=snake_case__						)

      # baseline - just load from_pretrained with normal network
      lowercase     :      List[Any]	=							[sys.executable, """-c""", """\n""".join([load, run, mock]						)]

      # should succeed
      lowercase     :      Union[str, Any]	=							self.get_env()
      # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
      lowercase     :      Union[str, Any]	=							"""1"""
      lowercase     :      List[Any]	=							subprocess.run(snake_case__   , env=snake_case__   , check=snake_case__   , capture_output=snake_case__						)
      self.assertEqual(result.returncode   , 0   , result.stderr						)
      self.assertIn("""success"""   , result.stdout.decode()						)



   @require_torch
   def  _UpperCAmelCase						(							self						)			->     int:







      """simple docstring"""
      lowercase     :      str	=							"""\nfrom transformers import BertConfig, BertModel, BertTokenizer, pipeline\n        """

      lowercase     :      int	=							"""\nmname = \"hf-internal-testing/tiny-random-bert\"\nBertConfig.from_pretrained(mname)\nBertModel.from_pretrained(mname)\nBertTokenizer.from_pretrained(mname)\npipe = pipeline(task=\"fill-mask\", model=mname)\nprint(\"success\")\n        """

      lowercase     :      Union[str, Any]	=							"""\nimport socket\ndef offline_socket(*args, **kwargs): raise socket.error(\"Faking flaky internet\")\nsocket.socket = offline_socket\n        """

      # Force fetching the files so that we can use the cache
      lowercase     :      Tuple	=							"""hf-internal-testing/tiny-random-bert"""
      BertConfig.from_pretrained(snake_case__						)
      BertModel.from_pretrained(snake_case__						)
      BertTokenizer.from_pretrained(snake_case__						)
      pipeline(task="""fill-mask"""   , model=snake_case__						)

      # baseline - just load from_pretrained with normal network
      lowercase     :      Optional[int]	=							[sys.executable, """-c""", """\n""".join([load, run, mock]						)]

      # should succeed
      lowercase     :      List[Any]	=							self.get_env()
      lowercase     :      Optional[Any]	=							subprocess.run(snake_case__   , env=snake_case__   , check=snake_case__   , capture_output=snake_case__						)
      self.assertEqual(result.returncode   , 0   , result.stderr						)
      self.assertIn("""success"""   , result.stdout.decode()						)



   @require_torch
   def  _UpperCAmelCase						(							self						)			->     Dict:







      """simple docstring"""
      lowercase     :      Dict	=							"""\nfrom transformers import BertConfig, BertModel, BertTokenizer\n        """

      lowercase     :      Union[str, Any]	=							"""\nmname = \"hf-internal-testing/tiny-random-bert-sharded\"\nBertConfig.from_pretrained(mname)\nBertModel.from_pretrained(mname)\nprint(\"success\")\n        """

      lowercase     :      Tuple	=							"""\nimport socket\ndef offline_socket(*args, **kwargs): raise ValueError(\"Offline mode is enabled\")\nsocket.socket = offline_socket\n        """

      # baseline - just load from_pretrained with normal network
      lowercase     :      Dict	=							[sys.executable, """-c""", """\n""".join([load, run]						)]

      # should succeed
      lowercase     :      List[Any]	=							self.get_env()
      lowercase     :      str	=							subprocess.run(snake_case__   , env=snake_case__   , check=snake_case__   , capture_output=snake_case__						)
      self.assertEqual(result.returncode   , 0   , result.stderr						)
      self.assertIn("""success"""   , result.stdout.decode()						)

      # next emulate no network
      lowercase     :      Optional[Any]	=							[sys.executable, """-c""", """\n""".join([load, mock, run]						)]

      # Doesn't fail anymore since the model is in the cache due to other tests, so commenting this.
      # env["TRANSFORMERS_OFFLINE"] = "0"
      # result = subprocess.run(cmd, env=env, check=False, capture_output=True)
      # self.assertEqual(result.returncode, 1, result.stderr)

      # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
      lowercase     :      Any	=							"""1"""
      lowercase     :      List[Any]	=							subprocess.run(snake_case__   , env=snake_case__   , check=snake_case__   , capture_output=snake_case__						)
      self.assertEqual(result.returncode   , 0   , result.stderr						)
      self.assertIn("""success"""   , result.stdout.decode()						)



   @require_torch
   def  _UpperCAmelCase						(							self						)			->     Any:







      """simple docstring"""
      lowercase     :      str	=							"""\nfrom transformers import pipeline\n        """
      lowercase     :      Optional[Any]	=							"""\nmname = \"hf-internal-testing/tiny-random-bert\"\npipe = pipeline(model=mname)\n        """

      lowercase     :      str	=							"""\nimport socket\ndef offline_socket(*args, **kwargs): raise socket.error(\"Offline mode is enabled\")\nsocket.socket = offline_socket\n        """
      lowercase     :      Optional[Any]	=							self.get_env()
      lowercase     :      Optional[int]	=							"""1"""
      lowercase     :      Dict	=							[sys.executable, """-c""", """\n""".join([load, mock, run]						)]
      lowercase     :      List[Any]	=							subprocess.run(snake_case__   , env=snake_case__   , check=snake_case__   , capture_output=snake_case__						)
      self.assertEqual(result.returncode   , 1   , result.stderr						)
      self.assertIn(
          """You cannot infer task automatically within `pipeline` when using offline mode"""   , result.stderr.decode().replace("""\n"""   , """"""						)   , )





   @require_torch
   def  _UpperCAmelCase						(							self						)			->     Dict:







      """simple docstring"""
      lowercase     :      Optional[Any]	=							"""\nfrom transformers import AutoModel\n        """
      lowercase     :      str	=							"""\nmname = \"hf-internal-testing/test_dynamic_model\"\nAutoModel.from_pretrained(mname, trust_remote_code=True)\nprint(\"success\")\n        """

      # baseline - just load from_pretrained with normal network
      lowercase     :      List[str]	=							[sys.executable, """-c""", """\n""".join([load, run]						)]

      # should succeed
      lowercase     :      Optional[int]	=							self.get_env()
      lowercase     :      List[str]	=							subprocess.run(snake_case__   , env=snake_case__   , check=snake_case__   , capture_output=snake_case__						)
      self.assertEqual(result.returncode   , 0   , result.stderr						)
      self.assertIn("""success"""   , result.stdout.decode()						)

      # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
      lowercase     :      Optional[int]	=							"""1"""
      lowercase     :      List[str]	=							subprocess.run(snake_case__   , env=snake_case__   , check=snake_case__   , capture_output=snake_case__						)
      self.assertEqual(result.returncode   , 0   , result.stderr						)
      self.assertIn("""success"""   , result.stdout.decode()						)





import string


def 							__lowerCAmelCase     (							_UpperCamelCase		:	str						)		->				str:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE		    =      ''
 for i in sequence:
  SCREAMING_SNAKE_CASE		    =      ord(_UpperCamelCase						)
  if 65 <= extract <= 90:
   output += chr(1_55 - extract						)
  elif 97 <= extract <= 1_22:
   output += chr(2_19 - extract						)
  else:
   output += i
 return output


def 							__lowerCAmelCase     (							_UpperCamelCase		:	str						)		->				str:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE		    =      string.ascii_letters
 SCREAMING_SNAKE_CASE		    =      string.ascii_lowercase[::-1] + string.ascii_uppercase[::-1]
 return "".join(
     letters_reversed[letters.index(_UpperCamelCase						)] if c in letters else c for c in sequence						)


def 							__lowerCAmelCase     (							)		->				None:
 '''simple docstring'''


 from timeit import timeit

 print('Running performance benchmarks...'						)
 SCREAMING_SNAKE_CASE		    =      'from string import printable ; from __main__ import atbash, atbash_slow'
 print(f"""> atbash_slow(): {timeit('atbash_slow(printable)'		,				setup=_UpperCamelCase						)} seconds"""						)
 print(f""">      atbash(): {timeit('atbash(printable)'		,				setup=_UpperCamelCase						)} seconds"""						)


if __name__ == "__main__":
      for example in ("ABCDEFGH", "123GGjj", "testStringtest", "with space"):
            print(F"""{example} encrypted in atbash: {atbash(example)}""")
      benchmark()

