





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
SCREAMING_SNAKE_CASE_      :			str		  =      '''stas/tiny-wmt19-en-ru'''

class 		snake_case_      (       UpperCAmelCase_    ,    unittest.TestCase	):







	'''simple docstring'''
	__UpperCamelCase        =		FSMTTokenizer
	__UpperCamelCase        =		False




	def       UpperCAmelCase (	self       :    Tuple      )					->   int:

			'''simple docstring'''




			super().setUp()

			# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
			__lowercase					=    [
			    '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>',
			]
			__lowercase					=    dict(zip(__lowerCamelCase				,			range(len(__lowerCamelCase      )      )      )      )
			__lowercase					=    ['l o 123', 'lo w 1456', 'e r</w> 1789', '']

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

			__lowercase					=    os.path.join(self.tmpdirname				,			VOCAB_FILES_NAMES['src_vocab_file']      )
			__lowercase					=    os.path.join(self.tmpdirname				,			VOCAB_FILES_NAMES['tgt_vocab_file']      )
			__lowercase					=    os.path.join(self.tmpdirname				,			'tokenizer_config.json'      )
			__lowercase					=    os.path.join(self.tmpdirname				,			VOCAB_FILES_NAMES['merges_file']      )
			with open(self.src_vocab_file				,			'w'      ) as fp:
					fp.write(json.dumps(__lowerCamelCase      )      )
			with open(self.tgt_vocab_file				,			'w'      ) as fp:
					fp.write(json.dumps(__lowerCamelCase      )      )
			with open(self.merges_file				,			'w'      ) as fp:
					fp.write('\n'.join(__lowerCamelCase      )      )
			with open(__lowerCamelCase				,			'w'      ) as fp:
					fp.write(json.dumps(__lowerCamelCase      )      )




	@cached_property
	def       UpperCAmelCase (	self       :    Union[str, Any]      )					->   str:

			'''simple docstring'''




			return FSMTTokenizer.from_pretrained('facebook/wmt19-ru-en'      )




	@cached_property
	def       UpperCAmelCase (	self       :    Union[str, Any]      )					->   str:

			'''simple docstring'''




			return FSMTTokenizer.from_pretrained('facebook/wmt19-en-ru'      )




	def       UpperCAmelCase (	self       :    Optional[int]      )					->   Tuple:

			'''simple docstring'''




			__lowercase					=    FSMTTokenizer.from_pretrained(__lowerCamelCase      )
			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       UpperCAmelCase (	self       :    List[Any]      )					->   Dict:

			'''simple docstring'''




			__lowercase					=    FSMTTokenizer(self.langs				,			self.src_vocab_file				,			self.tgt_vocab_file				,			self.merges_file      )

			__lowercase					=    'lower'
			__lowercase					=    ['low', 'er</w>']
			__lowercase					=    tokenizer.tokenize(__lowerCamelCase      )
			self.assertListEqual(__lowerCamelCase				,			__lowerCamelCase      )

			__lowercase					=    tokens + ['<unk>']
			__lowercase					=    [14, 15, 20]
			self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase      )				,			__lowerCamelCase      )




	@slow
	def       UpperCAmelCase (	self       :    Dict      )					->   Dict:

			'''simple docstring'''




			__lowercase					=    self.tokenizer_ru_en

			__lowercase					=    tokenizer.encode('sequence builders'				,			add_special_tokens=__lowerCamelCase      )
			__lowercase					=    tokenizer.encode('multi-sequence build'				,			add_special_tokens=__lowerCamelCase      )

			__lowercase					=    tokenizer.build_inputs_with_special_tokens(__lowerCamelCase      )
			__lowercase					=    tokenizer.build_inputs_with_special_tokens(__lowerCamelCase				,			__lowerCamelCase      )

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




	@slow
	def       UpperCAmelCase (	self       :    str      )					->   Optional[int]:

			'''simple docstring'''




			__lowercase					=    self.tokenizer_en_ru
			__lowercase					=    self.tokenizer_ru_en

			__lowercase					=    [
			    [
			        '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:
					__lowercase					=    tokenizer_enc.encode(__lowerCamelCase				,			return_tensors=__lowerCamelCase      )
					self.assertListEqual(__lowerCamelCase				,			__lowerCamelCase      )

					# and decode backward, using the reversed languages model
					__lowercase					=    tokenizer_dec.decode(__lowerCamelCase				,			skip_special_tokens=__lowerCamelCase      )
					self.assertEqual(__lowerCamelCase				,			__lowerCamelCase      )




	@slow
	def       UpperCAmelCase (	self       :    Union[str, Any]      )					->   int:

			'''simple docstring'''




			__lowercase					=    FSMTTokenizer.from_pretrained('facebook/wmt19-ru-en'				,			do_lower_case=__lowerCamelCase      )
			__lowercase					=    tokenizer.tokenize('USA is United States of America'      )
			__lowercase					=    ['us', 'a</w>', 'is</w>', 'un', 'i', 'ted</w>', 'st', 'ates</w>', 'of</w>', 'am', 'er', 'ica</w>']
			self.assertListEqual(__lowerCamelCase				,			__lowerCamelCase      )




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

			'''simple docstring'''




			pass






	@unittest.skip('FSMTConfig.__init__  requires non-optional args'      )
	def       UpperCAmelCase (	self       :    Optional[int]      )					->   Dict:

			'''simple docstring'''




			pass











SCREAMING_SNAKE_CASE_      :			str		  =      [chr(i) for i in range(32, 126)]
SCREAMING_SNAKE_CASE_      :			Any		  =      list(range(len(alphabets)))
SCREAMING_SNAKE_CASE_      :			Any		  =      list(range(len(alphabets)))
SCREAMING_SNAKE_CASE_      :			List[str]		  =      list(range(len(alphabets)))
SCREAMING_SNAKE_CASE_      :			Dict		  =      list(reversed(range(len(alphabets))))
SCREAMING_SNAKE_CASE_      :			int		  =      []
SCREAMING_SNAKE_CASE_      :			Union[str, Any]		  =      0



def    SCREAMING_SNAKE_CASE							(			)		->						int:
		global gear_one_pos
		global gear_two_pos
		global gear_three_pos
		__lowercase					=    gear_one[0]
		gear_one.append(snake_case       )
		del gear_one[0]
		gear_one_pos += 1
		if gear_one_pos % int(len(snake_case       )       ) == 0:
				__lowercase					=    gear_two[0]
				gear_two.append(snake_case       )
				del gear_two[0]
				gear_two_pos += 1
				if gear_two_pos % int(len(snake_case       )       ) == 0:
						__lowercase					=    gear_three[0]
						gear_three.append(snake_case       )
						del gear_three[0]
						gear_three_pos += 1



def    SCREAMING_SNAKE_CASE							(			snake_case       )		->						int:
		__lowercase					=    alphabets.index(snake_case       )
		__lowercase					=    gear_one[target]
		__lowercase					=    gear_two[target]
		__lowercase					=    gear_three[target]
		__lowercase					=    reflector[target]
		__lowercase					=    gear_three.index(snake_case       )
		__lowercase					=    gear_two.index(snake_case       )
		__lowercase					=    gear_one.index(snake_case       )
		code.append(alphabets[target]       )
		rotator()


if __name__ == "__main__":
		SCREAMING_SNAKE_CASE_      :			Tuple		  =      list(input('''Type your message:\n'''))
		while True:
				try:
						SCREAMING_SNAKE_CASE_      :			List[str]		  =      int(input('''Please set token:(must be only digits)\n'''))
						break
				except Exception as error:
						print(error)
		for _ in range(token):
				rotator()
		for j in decode:
				engine(j)
		print('''\n''' + ''''''.join(code))
		print(
		    F"""\nYour Token is {token} please write it down.\nIf you want to decode """
		    '''this message again you should input same digits as token!'''
		)




