






import concurrent.futures
import json
import os
import shutil
import tempfile
import unittest

from transformers import AutoTokenizer, PreTrainedTokenizerFast
from transformers.testing_utils import require_tokenizers

from ..test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 							a_				(		lowerCamelCase__			,			unittest.TestCase	):


							'''simple docstring'''






							__a:			Optional[Any]									=					PreTrainedTokenizerFast
							__a:			Optional[int]									=					False
							__a:			Optional[Any]									=					True
							__a:			List[Any]									=					'''tokenizer_file'''

							def   _lowercase (	self     )      ->      int:
														'''simple docstring'''

														lowerCAmelCase_       		=  False  # because we don't have pretrained_vocab_files_map
														super().setUp()
														lowerCAmelCase_       		=  True

														lowerCAmelCase_       		=  ['robot-test/dummy-tokenizer-fast', 'robot-test/dummy-tokenizer-wordlevel']
														lowerCAmelCase_       		=  'SaulLu/dummy-tokenizer-bytelevel-bpe'

														# Inclusion of 2 tokenizers to test different types of models (Unigram and WordLevel for the moment)
														lowerCAmelCase_       		=  [(PreTrainedTokenizerFast, model_path, {}) for model_path in model_paths]

														lowerCAmelCase_       		=  PreTrainedTokenizerFast.from_pretrained(model_paths[0]     )
														tokenizer.save_pretrained(self.tmpdirname     )

							def   _lowercase (	self     )      ->      List[str]:
														'''simple docstring'''

														pass

							def   _lowercase (	self     )      ->      Tuple:
														'''simple docstring'''

														pass

							def   _lowercase (	self     )      ->      List[Any]:
														'''simple docstring'''

														pass

							def   _lowercase (	self     )      ->      Optional[Any]:
														'''simple docstring'''

														pass

							def   _lowercase (	self     )      ->      Optional[int]:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.tmpdirname
														# Here we want to test the 2 available tokenizers that use 2 different types of models: Unigram and WordLevel.
														for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																					with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''     ):
																												try:
																																			lowerCAmelCase_       		=  tempfile.mkdtemp()
																																			lowerCAmelCase_       		=  self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_    ,    **SCREAMING_SNAKE_CASE_     )

																																			tokenizer.save_pretrained(self.tmpdirname     )
																																			super().test_training_new_tokenizer()
																												finally:
																																			# Even if the test fails, we must be sure that the folder is deleted and that the default tokenizer
																																			# is restored
																																			shutil.rmtree(self.tmpdirname     )
																																			lowerCAmelCase_       		=  tmpdirname_orig

							def   _lowercase (	self     )      ->      List[Any]:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.tmpdirname
														# Here we want to test the 2 available tokenizers that use 2 different types of models: Unigram and WordLevel.
														for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																					with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''     ):
																												try:
																																			lowerCAmelCase_       		=  tempfile.mkdtemp()
																																			lowerCAmelCase_       		=  self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_    ,    **SCREAMING_SNAKE_CASE_     )

																																			tokenizer.save_pretrained(self.tmpdirname     )
																																			super().test_training_new_tokenizer_with_special_tokens_change()
																												finally:
																																			# Even if the test fails, we must be sure that the folder is deleted and that the default tokenizer
																																			# is restored
																																			shutil.rmtree(self.tmpdirname     )
																																			lowerCAmelCase_       		=  tmpdirname_orig






							def   _lowercase (	self     )      ->      str:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.rust_tokenizer_class.from_pretrained(self.bytelevel_bpe_model_name     )

														lowerCAmelCase_       		=  ('a' for _ in range(1_0_0_0     ))
														lowerCAmelCase_       		=  tokenizer.train_new_from_iterator(text_iterator=SCREAMING_SNAKE_CASE_    ,    length=1_0_0_0    ,    vocab_size=5_0     )

														lowerCAmelCase_       		=  new_tokenizer.encode('a🤗'     )
														self.assertEqual(SCREAMING_SNAKE_CASE_    ,    [6_4, 1_7_2, 2_5_3, 9_7, 2_4_5]     )




@require_tokenizers
class 							a_				(		unittest.TestCase	):


							'''simple docstring'''






							def   _lowercase (	self     )      ->      Union[str, Any]:
														'''simple docstring'''

														lowerCAmelCase_       		=  AutoTokenizer.from_pretrained('bert-base-cased'     )
														lowerCAmelCase_       		=  json.loads(tokenizer._tokenizer.to_str()     )
														lowerCAmelCase_       		=  len(SCREAMING_SNAKE_CASE_     )

														with tempfile.TemporaryDirectory() as tmp_dir:
																					# Hack to save this in the tokenizer_config.json
																					lowerCAmelCase_       		=  ['tokenizer.4.0.0.json']
																					tokenizer.save_pretrained(SCREAMING_SNAKE_CASE_     )
																					json.dump(SCREAMING_SNAKE_CASE_    ,    open(os.path.join(SCREAMING_SNAKE_CASE_    ,    'tokenizer.4.0.0.json'     )    ,    'w'     )     )

																					# This should pick the new tokenizer file as the version of Transformers is > 4.0.0
																					lowerCAmelCase_       		=  AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_     )
																					self.assertEqual(len(SCREAMING_SNAKE_CASE_     )    ,    len(SCREAMING_SNAKE_CASE_     ) + 1     )
																					lowerCAmelCase_       		=  json.loads(new_tokenizer._tokenizer.to_str()     )
																					self.assertIn('huggingface'    ,    json_tokenizer['model']['vocab']     )

																					# Will need to be adjusted if we reach v42 and this test is still here.
																					# Should pick the old tokenizer file as the version of Transformers is < 4.0.0
																					shutil.move(os.path.join(SCREAMING_SNAKE_CASE_    ,    'tokenizer.4.0.0.json'     )    ,    os.path.join(SCREAMING_SNAKE_CASE_    ,    'tokenizer.42.0.0.json'     )     )
																					lowerCAmelCase_       		=  ['tokenizer.42.0.0.json']
																					tokenizer.save_pretrained(SCREAMING_SNAKE_CASE_     )
																					lowerCAmelCase_       		=  AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_     )
																					self.assertEqual(len(SCREAMING_SNAKE_CASE_     )    ,    len(SCREAMING_SNAKE_CASE_     )     )
																					lowerCAmelCase_       		=  json.loads(new_tokenizer._tokenizer.to_str()     )
																					self.assertNotIn('huggingface'    ,    json_tokenizer['model']['vocab']     )






							def   _lowercase (	self     )      ->      Optional[int]:
														'''simple docstring'''

														lowerCAmelCase_       		=  'hf-internal-testing/test-two-tokenizers'

														# This should pick the new tokenizer file as the version of Transformers is > 4.0.0
														lowerCAmelCase_       		=  AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_     )
														self.assertEqual(len(SCREAMING_SNAKE_CASE_     )    ,    2_8_9_9_7     )
														lowerCAmelCase_       		=  json.loads(tokenizer._tokenizer.to_str()     )
														self.assertIn('huggingface'    ,    json_tokenizer['model']['vocab']     )

														# Testing an older version by monkey-patching the version in the module it's used.
														import transformers as old_transformers

														lowerCAmelCase_       		=  '3.0.0'
														lowerCAmelCase_       		=  old_transformers.models.auto.AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_     )
														self.assertEqual(len(SCREAMING_SNAKE_CASE_     )    ,    2_8_9_9_6     )
														lowerCAmelCase_       		=  json.loads(old_tokenizer._tokenizer.to_str()     )
														self.assertNotIn('huggingface'    ,    json_tokenizer['model']['vocab']     )




@require_tokenizers
class 							a_				(		unittest.TestCase	):


							'''simple docstring'''






							def   _lowercase (	self     )      ->      Optional[Any]:
														'''simple docstring'''

														lowerCAmelCase_       		=  PreTrainedTokenizerFast.from_pretrained('robot-test/dummy-tokenizer-wordlevel'     )
														lowerCAmelCase_       		=  'The Matrix is a 1999 science fiction action film.'

														with concurrent.futures.ThreadPoolExecutor() as executor:
																					lowerCAmelCase_       		=  [executor.submit(self.fetch    ,    SCREAMING_SNAKE_CASE_    ,    SCREAMING_SNAKE_CASE_     ) for i in range(1_0     )]
																					lowerCAmelCase_       		=  [future.result() for future in futures]
																					self.assertEqual(SCREAMING_SNAKE_CASE_    ,    [[1, 1_0, 0, 8, 0, 1_8, 0, 0, 0, 2] for i in range(1_0     )]     )






							def   _lowercase (	self    ,    lowercase_    ,    lowercase_     )      ->      Any:
														'''simple docstring'''

														return tokenizer.encode(SCREAMING_SNAKE_CASE_    ,    truncation='longest_first'    ,    padding='longest'     )











from __future__ import annotations

from string import ascii_letters
def   lowerCamelCase      (		a_				,		a_				,		a_ = None			)			->    str:
							lowerCAmelCase_       		=  alphabet or ascii_letters

							# The final result string
							lowerCAmelCase_       		=  ''

							for character in input_string:
														if character not in alpha:
																					# Append without encryption if character is not in the alphabet
																					result += character
														else:
																					# Get the index of the new key and make sure it isn't too large
																					lowerCAmelCase_       		=  (alpha.index(a_			) + key) % len(a_			)

																					# Append the encoded character to the alphabet
																					result += alpha[new_key]

							return result
def   lowerCamelCase      (		a_				,		a_				,		a_ = None			)			->    str:
							key *= -1

							return encrypt(a_				,		a_				,		a_			)
def   lowerCamelCase      (		a_				,		a_ = None			)			->    dict[int, str]:
							lowerCAmelCase_       		=  alphabet or ascii_letters

							# To store data on all the combinations
							lowerCAmelCase_       		=  {}

							# Cycle through each combination
							for key in range(1				,		len(a_			) + 1			):
														# Decrypt the message and store the result in the data
														lowerCAmelCase_       		=  decrypt(a_				,		a_				,		a_			)

							return brute_force_data


if __name__ == "__main__":
		while True:
				print(f'''\n{"-" * 1_0}\n Menu\n{"-" * 1_0}''')
				print(*["""1.Encrypt""", """2.Decrypt""", """3.BruteForce""", """4.Quit"""], sep="""\n""")

				# get user input
				lowerCamelCase_		  =						input("""\nWhat would you like to do?: """).strip() or """4"""

				# run functions based on what the user chose
				if choice not in ("1", "2", "3", "4"):
						print("""Invalid choice, please enter a valid choice""")
				elif choice == "1":
						lowerCamelCase_		  =						input("""Please enter the string to be encrypted: """)
						lowerCamelCase_		  =						int(input("""Please enter off-set: """).strip())

						print(encrypt(input_string, key))
				elif choice == "2":
						lowerCamelCase_		  =						input("""Please enter the string to be decrypted: """)
						lowerCamelCase_		  =						int(input("""Please enter off-set: """).strip())

						print(decrypt(input_string, key))
				elif choice == "3":
						lowerCamelCase_		  =						input("""Please enter the string to be decrypted: """)
						lowerCamelCase_		  =						brute_force(input_string)

						for key, value in brute_force_data.items():
								print(f'''Key: {key} | Message: {value}''')

				elif choice == "4":
						print("""Goodbye.""")
						break



