"""simple docstring"""


import os
import shutil
import unittest
from unittest.mock import patch

from transformers.testing_utils import CaptureStd, is_pt_tf_cross_test, require_torch
class   UpperCAmelCase_	(				unittest.TestCase   ):
    @patch("sys.argv"   ,						["fakeprogrampath", "env"]		)
    def 		_lowerCamelCase      (	self			:       Optional[int]		)						->    List[Any]:
       # test transformers-cli env
       import transformers.commands.transformers_cli

       with CaptureStd() as cs:
          transformers.commands.transformers_cli.main()
       self.assertIn("Python version"   ,						cs.out		)
       self.assertIn("Platform"   ,						cs.out		)
       self.assertIn("Using distributed or parallel set-up in script?"   ,						cs.out		)
    @is_pt_tf_cross_test
    @patch(
        "sys.argv"   ,						["fakeprogrampath", "pt-to-tf", "--model-name", "hf-internal-testing/tiny-random-gptj", "--no-pr"]		)
    def 		_lowerCamelCase      (	self			:       Union[str, Any]		)						->    Optional[int]:
       import transformers.commands.transformers_cli

       shutil.rmtree("/tmp/hf-internal-testing/tiny-random-gptj"   ,						ignore_errors=_lowercase		)  # cleans potential past runs
       transformers.commands.transformers_cli.main()

       # The original repo has no TF weights -- if they exist, they were created by the CLI
       self.assertTrue(os.path.exists("/tmp/hf-internal-testing/tiny-random-gptj/tf_model.h5"		)		)
    @require_torch
    @patch("sys.argv"   ,						["fakeprogrampath", "download", "hf-internal-testing/tiny-random-gptj", "--cache-dir", "/tmp"]		)
    def 		_lowerCamelCase      (	self			:       int		)						->    int:
       import transformers.commands.transformers_cli

       # # remove any previously downloaded model to start clean
       shutil.rmtree("/tmp/models--hf-internal-testing--tiny-random-gptj"   ,						ignore_errors=_lowercase		)

       # run the command
       transformers.commands.transformers_cli.main()

       # check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--tiny-random-gptj
       self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/blobs"		)		)
       self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/refs"		)		)
       self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/snapshots"		)		)




    @require_torch
    @patch(
        "sys.argv"   ,						[
            "fakeprogrampath",
            "download",
            "hf-internal-testing/test_dynamic_model_with_tokenizer",
            "--trust-remote-code",
            "--cache-dir",
            "/tmp",
        ]   ,						)
    def 		_lowerCamelCase      (	self			:       Dict		)						->    List[str]:
       import transformers.commands.transformers_cli

       # # remove any previously downloaded model to start clean
       shutil.rmtree("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer"   ,						ignore_errors=_lowercase		)

       # run the command
       transformers.commands.transformers_cli.main()

       # check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer
       self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/blobs"		)		)
       self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/refs"		)		)
       self.assertTrue(
           os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/snapshots"		)		)
"""simple docstring"""


from typing import Literal

__UpperCamelCase       :    int         =		"ABCDEFGHIJKLMNOPQRSTUVWXYZ"


def   __UpperCAmelCase     (	_snake_case		:       str,				_snake_case		:       str,				_snake_case		:       Literal["encrypt", "decrypt"]       ):
   _lowercase							     =       LETTERS if mode == "decrypt" else key
   _lowercase							     =       key if mode == "decrypt" else LETTERS
   _lowercase							     =       ""
   # loop through each symbol in the message
   for symbol in message:
      if symbol.upper() in chars_a:
         # encrypt/decrypt the symbol
         _lowercase							     =       chars_a.find(symbol.upper()       )
         if symbol.isupper():
            translated += chars_b[sym_index].upper()
         else:
            translated += chars_b[sym_index].lower()
      else:
         # symbol is not in LETTERS, just add it
         translated += symbol
   return translated


def   __UpperCAmelCase     (	_snake_case		:       str,				_snake_case		:       str       ):
   return translate_message(_snake_case,				_snake_case,				"encrypt"       )


def   __UpperCAmelCase     (	_snake_case		:       str,				_snake_case		:       str       ):
   return translate_message(_snake_case,				_snake_case,				"decrypt"       )


def   __UpperCAmelCase     (	):
   _lowercase							     =       "Hello World"
   _lowercase							     =       "QWERTYUIOPASDFGHJKLZXCVBNM"
   _lowercase							     =       "decrypt"  # set to 'encrypt' or 'decrypt'

   if mode == "encrypt":
      _lowercase							     =       encrypt_message(_snake_case,				_snake_case       )
   elif mode == "decrypt":
      _lowercase							     =       decrypt_message(_snake_case,				_snake_case       )
   print(f"""Using the key {key}, the {mode}ed message is: {translated}"""       )


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()