






import json
import os
import unittest

from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES, FSMTTokenizer
from transformers.testing_utils import slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


# using a different tiny model than the one used for default params defined in init to ensure proper testing
__lowerCamelCase						= 'stas/tiny-wmt19-en-ru'

class      UpperCamelCase_							(				UpperCamelCase ,       unittest.TestCase       ):
						lowercase									=  FSMTTokenizer
						lowercase									=  False




						def      snake_case__(    self       )			->						Optional[int]:
													super().setUp()

													# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
													_a  :    Optional[int]			=						[
													    'l',
													    'o',
													    'w',
													    'e',
													    'r',
													    's',
													    't',
													    'i',
													    'd',
													    'n',
													    'w</w>',
													    'r</w>',
													    't</w>',
													    'lo',
													    'low',
													    'er</w>',
													    'low</w>',
													    'lowest</w>',
													    'newer</w>',
													    'wider</w>',
													    '<unk>',
													]
													_a  :    List[Any]			=						dict(zip(__SCREAMING_SNAKE_CASE		,	range(len(__SCREAMING_SNAKE_CASE       )       )       )       )
													_a  :    int			=						['l o 123', 'lo w 1456', 'e r</w> 1789', '']

													_a  :    str			=						['en', 'ru']
													_a  :    Any			=						{
													    'langs': self.langs,
													    'src_vocab_size': 10,
													    'tgt_vocab_size': 20,
													}

													_a  :    Dict			=						os.path.join(self.tmpdirname		,	VOCAB_FILES_NAMES['''src_vocab_file''']       )
													_a  :    Union[str, Any]			=						os.path.join(self.tmpdirname		,	VOCAB_FILES_NAMES['''tgt_vocab_file''']       )
													_a  :    Any			=						os.path.join(self.tmpdirname		,	'''tokenizer_config.json'''       )
													_a  :    int			=						os.path.join(self.tmpdirname		,	VOCAB_FILES_NAMES['''merges_file''']       )
													with open(self.src_vocab_file		,	'''w'''       ) as fp:
																				fp.write(json.dumps(__SCREAMING_SNAKE_CASE       )       )
													with open(self.tgt_vocab_file		,	'''w'''       ) as fp:
																				fp.write(json.dumps(__SCREAMING_SNAKE_CASE       )       )
													with open(self.merges_file		,	'''w'''       ) as fp:
																				fp.write('''\n'''.join(__SCREAMING_SNAKE_CASE       )       )
													with open(__SCREAMING_SNAKE_CASE		,	'''w'''       ) as fp:
																				fp.write(json.dumps(__SCREAMING_SNAKE_CASE       )       )




						@cached_property
						def      snake_case__(    self       )			->						Dict:
													return FSMTTokenizer.from_pretrained('''facebook/wmt19-ru-en'''       )




						@cached_property
						def      snake_case__(    self       )			->						Optional[int]:
													return FSMTTokenizer.from_pretrained('''facebook/wmt19-en-ru'''       )




						def      snake_case__(    self       )			->						Union[str, Any]:
													_a  :    List[str]			=						FSMTTokenizer.from_pretrained(__SCREAMING_SNAKE_CASE       )
													self.assertListEqual([tokenizer.src_lang, tokenizer.tgt_lang]		,	['''en''', '''ru''']       )
													self.assertEqual(tokenizer.src_vocab_size		,	21       )
													self.assertEqual(tokenizer.tgt_vocab_size		,	21       )




						def      snake_case__(    self       )			->						Optional[int]:
													_a  :    Tuple			=						FSMTTokenizer(self.langs		,	self.src_vocab_file		,	self.tgt_vocab_file		,	self.merges_file       )

													_a  :    List[str]			=						'lower'
													_a  :    str			=						['low', 'er</w>']
													_a  :    List[str]			=						tokenizer.tokenize(__SCREAMING_SNAKE_CASE       )
													self.assertListEqual(__SCREAMING_SNAKE_CASE		,	__SCREAMING_SNAKE_CASE       )

													_a  :    int			=						tokens + ['<unk>']
													_a  :    Union[str, Any]			=						[14, 15, 20]
													self.assertListEqual(tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE       )		,	__SCREAMING_SNAKE_CASE       )




						@slow
						def      snake_case__(    self       )			->						Optional[Any]:
													_a  :    Any			=						self.tokenizer_ru_en

													_a  :    Union[str, Any]			=						tokenizer.encode('''sequence builders'''		,	add_special_tokens=__SCREAMING_SNAKE_CASE       )
													_a  :    Tuple			=						tokenizer.encode('''multi-sequence build'''		,	add_special_tokens=__SCREAMING_SNAKE_CASE       )

													_a  :    Optional[Any]			=						tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE       )
													_a  :    Optional[Any]			=						tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE		,	__SCREAMING_SNAKE_CASE       )

													assert encoded_sentence == text + [2]
													assert encoded_pair == text + [2] + text_a + [2]




						@slow
						def      snake_case__(    self       )			->						List[str]:
													_a  :    Any			=						self.tokenizer_en_ru
													_a  :    int			=						self.tokenizer_ru_en

													_a  :    Optional[Any]			=						[
													    [
													        'Here\'s a little song I wrote. Don\'t worry, be happy.',
													        [2_470, 39, 11, 2_349, 7_222, 70, 5_979, 7, 8_450, 1_050, 13_160, 5, 26, 6_445, 7, 2],
													    ],
													    ['This is it. No more. I\'m done!', [132, 21, 37, 7, 1_434, 86, 7, 70, 6_476, 1_305, 427, 2]],
													]

													# if data needs to be recreated or added, run:
													# import torch
													# model = torch.hub.load("pytorch/fairseq", "transformer.wmt19.en-ru", checkpoint_file="model4.pt", tokenizer="moses", bpe="fastbpe")
													# for src_text, _ in targets: print(f"""[\n"{src_text}",\n {model.encode(src_text).tolist()}\n],""")

													for src_text, tgt_input_ids in targets:
																				_a  :    Any			=						tokenizer_enc.encode(__SCREAMING_SNAKE_CASE		,	return_tensors=__SCREAMING_SNAKE_CASE       )
																				self.assertListEqual(__SCREAMING_SNAKE_CASE		,	__SCREAMING_SNAKE_CASE       )

																				# and decode backward, using the reversed languages model
																				_a  :    List[Any]			=						tokenizer_dec.decode(__SCREAMING_SNAKE_CASE		,	skip_special_tokens=__SCREAMING_SNAKE_CASE       )
																				self.assertEqual(__SCREAMING_SNAKE_CASE		,	__SCREAMING_SNAKE_CASE       )




						@slow
						def      snake_case__(    self       )			->						List[str]:
													_a  :    Optional[Any]			=						FSMTTokenizer.from_pretrained('''facebook/wmt19-ru-en'''		,	do_lower_case=__SCREAMING_SNAKE_CASE       )
													_a  :    Dict			=						tokenizer.tokenize('''USA is United States of America'''       )
													_a  :    Optional[int]			=						['us', 'a</w>', 'is</w>', 'un', 'i', 'ted</w>', 'st', 'ates</w>', 'of</w>', 'am', 'er', 'ica</w>']
													self.assertListEqual(__SCREAMING_SNAKE_CASE		,	__SCREAMING_SNAKE_CASE       )




						@unittest.skip('''FSMTConfig.__init__  requires non-optional args'''       )
						def      snake_case__(    self       )			->						Union[str, Any]:
													pass







						@unittest.skip('''FSMTConfig.__init__  requires non-optional args'''       )
						def      snake_case__(    self       )			->						List[Any]:
													pass

'''simple docstring'''

import random
import sys

__UpperCAmelCase												=   'ABCDEFGHIJKLMNOPQRSTUVWXYZ'



def        SCREAMING_SNAKE_CASE_  (	)       ->	None:
 SCREAMING_SNAKE_CASE  :  Dict								=		input('Enter message: '							)
 SCREAMING_SNAKE_CASE  :  Dict								=		'LFWOAYUISVKMNXPBDCRJTQEGHZ'
 SCREAMING_SNAKE_CASE  :  Tuple								=		input('Encrypt/Decrypt [e/d]: '							)

 check_valid_key(snake_case_							)

 if resp.lower().startswith('e'							):
  SCREAMING_SNAKE_CASE  :  str								=		'encrypt'
  SCREAMING_SNAKE_CASE  :  Optional[Any]								=		encrypt_message(snake_case_   ,     snake_case_							)
 elif resp.lower().startswith('d'							):
  SCREAMING_SNAKE_CASE  :  List[Any]								=		'decrypt'
  SCREAMING_SNAKE_CASE  :  List[str]								=		decrypt_message(snake_case_   ,     snake_case_							)

 print(f"""\n{mode.title()}ion: \n{translated}"""							)



def        SCREAMING_SNAKE_CASE_  (	snake_case_				:	str							)       ->	None:
 SCREAMING_SNAKE_CASE  :  int								=		list(snake_case_							)
 SCREAMING_SNAKE_CASE  :  Optional[Any]								=		list(snake_case_							)
 key_list.sort()
 letters_list.sort()

 if key_list != letters_list:
  sys.exit('Error in the key or symbol set.'							)



def        SCREAMING_SNAKE_CASE_  (	snake_case_				:	str   ,     snake_case_				:	str							)       ->	str:
 return translate_message(snake_case_   ,     snake_case_   ,     'encrypt'							)



def        SCREAMING_SNAKE_CASE_  (	snake_case_				:	str   ,     snake_case_				:	str							)       ->	str:
 return translate_message(snake_case_   ,     snake_case_   ,     'decrypt'							)



def        SCREAMING_SNAKE_CASE_  (	snake_case_				:	str   ,     snake_case_				:	str   ,     snake_case_				:	str							)       ->	str:
 SCREAMING_SNAKE_CASE  :  Any								=		''
 SCREAMING_SNAKE_CASE  :  Optional[Any]								=		LETTERS
 SCREAMING_SNAKE_CASE  :  List[Any]								=		key

 if mode == "decrypt":
  SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE  :  List[Any]								=		chars_b, chars_a

 for symbol in message:
  if symbol.upper() in chars_a:
   SCREAMING_SNAKE_CASE  :  Optional[Any]								=		chars_a.find(symbol.upper()							)
   if symbol.isupper():
    translated += chars_b[sym_index].upper()
   else:
    translated += chars_b[sym_index].lower()
  else:
   translated += symbol

 return translated



def        SCREAMING_SNAKE_CASE_  (	)       ->	str:
 SCREAMING_SNAKE_CASE  :  Dict								=		list(snake_case_							)
 random.shuffle(snake_case_							)
 return "".join(snake_case_							)


if __name__ == "__main__":
   main()


