

'''simple docstring'''





from __future__ import annotations







def   _UpperCamelCase	(		__UpperCamelCase    ,__UpperCamelCase	)       ->			bool:
					lowerCamelCase_  				=      get_failure_array(__UpperCamelCase	)

					# 2) Step through text searching for pattern
					lowerCamelCase_				,lowerCamelCase_  				=      0, 0  # index into text, pattern
					while i < len(__UpperCamelCase	):
										if pattern[j] == text[i]:
															if j == (len(__UpperCamelCase	) - 1):
																				return True
															j += 1

										# if this is a prefix in our pattern
										# just go back far enough to continue
										elif j > 0:
															lowerCamelCase_  				=      failure[j - 1]
															continue
										i += 1
					return False







def   _UpperCamelCase	(		__UpperCamelCase	)       ->			list[int]:
					lowerCamelCase_  				=      [0]
					lowerCamelCase_  				=      0
					lowerCamelCase_  				=      1
					while j < len(__UpperCamelCase	):
										if pattern[i] == pattern[j]:
															i += 1
										elif i > 0:
															lowerCamelCase_  				=      failure[i - 1]
															continue
										j += 1
										failure.append(__UpperCamelCase	)
					return failure


if __name__ == "__main__":
				# Test 1)
				A_	= "abc1abc12"
				A_	= "alskfjaldsabc1abc1abc12k23adsfabcabc"
				A_	= "alskfjaldsk23adsfabcabc"
				assert kmp(pattern, texta) and not kmp(pattern, texta)

				# Test 2)
				A_	= "ABABX"
				A_	= "ABABZABABYABABX"
				assert kmp(pattern, text)

				# Test 3)
				A_	= "AAAB"
				A_	= "ABAAAAAB"
				assert kmp(pattern, text)

				# Test 4)
				A_	= "abcdabcy"
				A_	= "abcxabcdabxabcdabcdabcy"
				assert kmp(pattern, text)

				# Test 5)
				A_	= "aabaabaaa"
				assert get_failure_array(pattern) == [0, 1, 0, 1, 2, 3, 4, 5, 2]











import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
       from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
       __magic_name__   :  Any        =							get_tests_dir('''fixtures/test_sentencepiece.model''')


if is_torch_available():
       from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

__magic_name__   :  Optional[Any]        =							12_8022
__magic_name__   :  Dict        =							12_8028





@require_sentencepiece
class 					A__     (     __snake_case   ,    unittest.TestCase ):

     '''simple docstring'''






     snake_case__					=					MaMaaaTokenizer
     snake_case__					=					False
     snake_case__					=					False
     snake_case__					=					True







     def   _SCREAMING_SNAKE_CASE     ( self      :    List[str] ):






           """simple docstring"""




           super().setUp()

           UpperCamelCase					       =  ['</s>', '<unk>', '▁This', '▁is', '▁a', '▁t', 'est', '\u0120', '<pad>']
           UpperCamelCase					       =  dict(zip(_SCREAMING_SNAKE_CASE   ,						range(len(_SCREAMING_SNAKE_CASE ) ) ) )
           UpperCamelCase					       =  Path(self.tmpdirname )
           save_json(_SCREAMING_SNAKE_CASE   ,						save_dir / VOCAB_FILES_NAMES['vocab_file'] )
           if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
                 copyfile(_SCREAMING_SNAKE_CASE   ,						save_dir / VOCAB_FILES_NAMES['spm_file'] )

           UpperCamelCase					       =  MaMaaaTokenizer.from_pretrained(self.tmpdirname )
           tokenizer.save_pretrained(self.tmpdirname )







     def   _SCREAMING_SNAKE_CASE     ( self      :    str   ,						**_SCREAMING_SNAKE_CASE      :    List[str] ):






           """simple docstring"""




           return MaMaaaTokenizer.from_pretrained(self.tmpdirname   ,						**_SCREAMING_SNAKE_CASE )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Optional[int]   ,						_SCREAMING_SNAKE_CASE      :    Optional[Any] ):






           """simple docstring"""




           return (
               "This is a test",
               "This is a test",
           )







     def   _SCREAMING_SNAKE_CASE     ( self      :    List[Any] ):






           """simple docstring"""




           UpperCamelCase					       =  '</s>'
           UpperCamelCase					       =  0

           self.assertEqual(self.get_tokenizer()._convert_token_to_id(_SCREAMING_SNAKE_CASE )   ,						_SCREAMING_SNAKE_CASE )
           self.assertEqual(self.get_tokenizer()._convert_id_to_token(_SCREAMING_SNAKE_CASE )   ,						_SCREAMING_SNAKE_CASE )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Optional[Any] ):






           """simple docstring"""




           UpperCamelCase					       =  self.get_tokenizer()
           UpperCamelCase					       =  list(tokenizer.get_vocab().keys() )

           self.assertEqual(vocab_keys[0]   ,						'</s>' )
           self.assertEqual(vocab_keys[1]   ,						'<unk>' )
           self.assertEqual(vocab_keys[-1]   ,						'<s>' )
           self.assertEqual(len(_SCREAMING_SNAKE_CASE )   ,						tokenizer.vocab_size + len(tokenizer.get_added_vocab() ) )







     @unittest.skip('Skip this test while all models are still to be uploaded.' )
     def   _SCREAMING_SNAKE_CASE     ( self      :    str ):






           """simple docstring"""




           pass







     def   _SCREAMING_SNAKE_CASE     ( self      :    Any ):






           """simple docstring"""




           UpperCamelCase					       =  self.get_tokenizer()

           UpperCamelCase					       =  tokenizer.tokenize('This is a test' )
           self.assertListEqual(_SCREAMING_SNAKE_CASE   ,						['▁This', '▁is', '▁a', '▁t', 'est'] )

           self.assertListEqual(
               tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE )   ,						[2, 3, 4, 5, 6]   ,						)

           UpperCamelCase					       =  tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6] )
           self.assertListEqual(_SCREAMING_SNAKE_CASE   ,						['▁This', '▁is', '▁a', '▁t', 'est'] )

           UpperCamelCase					       =  tokenizer.convert_tokens_to_string(_SCREAMING_SNAKE_CASE )
           self.assertEqual(_SCREAMING_SNAKE_CASE   ,						'This is a test' )







     @slow
     def   _SCREAMING_SNAKE_CASE     ( self      :    str ):






           """simple docstring"""




           UpperCamelCase					       =  {'input_ids': [[12_8022, 11_0108, 397, 11, 3_8272, 2247, 12_4811, 285, 1_8105, 1586, 207, 7, 3_9534, 4428, 397, 1019, 1_8105, 1586, 207, 7, 4_1337, 1_6786, 241, 7, 2_0214, 17, 12_5690, 1_0398, 7, 4_4378, 5_8069, 6_8342, 7798, 7343, 11, 299, 3_3310, 4, 158, 3_7350, 9_4077, 4569, 299, 3_3310, 90, 4, 5_2840, 290, 4, 3_1270, 112, 299, 682, 4, 5_2840, 3_9953, 1_4079, 193, 5_2519, 9_0894, 1_7894, 12_0697, 11, 4_0445, 551, 17, 1019, 5_2519, 9_0894, 1_7756, 963, 11, 4_0445, 480, 17, 9792, 1120, 5173, 1393, 6240, 1_6786, 241, 12_0996, 28, 1245, 1393, 11_8240, 1_1123, 1019, 9_3612, 2691, 1_0618, 9_8058, 12_0409, 1928, 279, 4, 4_0683, 367, 178, 207, 1019, 103, 10_3121, 506, 6_5296, 5, 2], [12_8022, 2_1217, 367, 117, 12_5450, 128, 719, 7, 7308, 40, 9_3612, 1_2669, 1116, 1_6704, 71, 1_7785, 3699, 1_5592, 35, 144, 9584, 241, 1_1943, 713, 950, 799, 2247, 8_8427, 150, 149, 11_8813, 12_0706, 1019, 10_6906, 8_1518, 28, 1224, 2_2799, 397, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [12_8022, 1658, 12_3311, 5155, 5578, 4722, 279, 1_4947, 2366, 1120, 1197, 14, 1348, 9232, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
           # fmt: on

           self.tokenizer_integration_test_util(
               expected_encoding=_SCREAMING_SNAKE_CASE   ,						model_name='facebook/m2m100_418M'   ,						revision='c168bae485c864188cf9aa0e4108b0b6934dc91e'   ,						)





@require_torch
@require_sentencepiece
@require_tokenizers
class 					A__     (     unittest.TestCase ):

     '''simple docstring'''






     snake_case__					=					"""facebook/m2m100_418M"""
     snake_case__					=					[
         """In my opinion, there are two levels of response from the French government.""",
         """NSA Affair Emphasizes Complete Lack of Debate on Intelligence""",
     ]
     snake_case__					=					[
         """Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.""",
         """L'affaire NSA souligne l'absence totale de débat sur le renseignement""",
     ]

     # fmt: off
     snake_case__					=					[EN_CODE, 5_93, 19_49, 11_57_81, 4, 7_15_86, 42_34, 6_06_33, 12_62_33, 4_32, 12_38_08, 1_55_92, 11_97, 11_71_32, 12_06_18, 5, 2]







     @classmethod
     def   _SCREAMING_SNAKE_CASE     ( cls      :    Any ):






           """simple docstring"""




           UpperCamelCase					       =  MaMaaaTokenizer.from_pretrained(
               cls.checkpoint_name   ,						src_lang='en'   ,						tgt_lang='fr' )
           UpperCamelCase					       =  1
           return cls







     def   _SCREAMING_SNAKE_CASE     ( self      :    str ):






           """simple docstring"""




           self.assertEqual(self.tokenizer.get_lang_id('ar' )   ,						12_8006 )
           self.assertEqual(self.tokenizer.get_lang_id('en' )   ,						12_8022 )
           self.assertEqual(self.tokenizer.get_lang_id('ro' )   ,						12_8076 )
           self.assertEqual(self.tokenizer.get_lang_id('mr' )   ,						12_8063 )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Tuple ):






           """simple docstring"""




           UpperCamelCase					       =  self.tokenizer.get_vocab()
           self.assertEqual(len(_SCREAMING_SNAKE_CASE )   ,						self.tokenizer.vocab_size )
           self.assertEqual(vocab['<unk>']   ,						3 )
           self.assertIn(self.tokenizer.get_lang_token('en' )   ,						_SCREAMING_SNAKE_CASE )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Optional[Any] ):






           """simple docstring"""




           UpperCamelCase					       =  'en'
           UpperCamelCase					       =  self.tokenizer.batch_encode_plus(self.src_text ).input_ids[0]
           self.assertListEqual(self.expected_src_tokens   ,						_SCREAMING_SNAKE_CASE )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Union[str, Any] ):






           """simple docstring"""




           self.assertIn(_SCREAMING_SNAKE_CASE   ,						self.tokenizer.all_special_ids )
           # fmt: off
           UpperCamelCase					       =  [FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 1_4028, 136, 3286, 9706, 6, 9_0797, 6, 14_4012, 162, 8_8128, 3_0061, 5, 2]
           # fmt: on
           UpperCamelCase					       =  self.tokenizer.decode(_SCREAMING_SNAKE_CASE   ,						skip_special_tokens=_SCREAMING_SNAKE_CASE )
           UpperCamelCase					       =  self.tokenizer.decode(generated_ids[1:]   ,						skip_special_tokens=_SCREAMING_SNAKE_CASE )
           self.assertEqual(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )
           self.assertNotIn(self.tokenizer.eos_token   ,						_SCREAMING_SNAKE_CASE )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Optional[Any] ):






           """simple docstring"""




           UpperCamelCase					       =  tempfile.mkdtemp()
           UpperCamelCase					       =  self.tokenizer.lang_token_to_id
           self.tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE )
           UpperCamelCase					       =  MaMaaaTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE )
           self.assertDictEqual(new_tok.lang_token_to_id   ,						_SCREAMING_SNAKE_CASE )







     @require_torch
     def   _SCREAMING_SNAKE_CASE     ( self      :    Union[str, Any] ):






           """simple docstring"""




           UpperCamelCase					       =  'en'
           UpperCamelCase					       =  'fr'

           UpperCamelCase					       =  self.tokenizer(self.src_text   ,						text_target=self.tgt_text   ,						padding=_SCREAMING_SNAKE_CASE   ,						return_tensors='pt' )

           UpperCamelCase					       =  shift_tokens_right(
               batch['labels']   ,						self.tokenizer.pad_token_id   ,						self.tokenizer.eos_token_id )

           for k in batch:
                 UpperCamelCase					       =  batch[k].tolist()
           # batch = {k: v.tolist() for k,v in batch.items()}
           # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
           # batch.decoder_inputs_ids[0][0] ==
           assert batch.input_ids[1][0] == EN_CODE
           assert batch.input_ids[1][-1] == 2
           assert batch.labels[1][0] == FR_CODE
           assert batch.labels[1][-1] == 2
           assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]







     @require_torch
     def   _SCREAMING_SNAKE_CASE     ( self      :    Any ):






           """simple docstring"""




           UpperCamelCase					       =  'mr'
           self.assertListEqual(self.tokenizer.prefix_tokens   ,						[self.tokenizer.get_lang_id('mr' )] )
           self.assertListEqual(self.tokenizer.suffix_tokens   ,						[self.tokenizer.eos_token_id] )

           UpperCamelCase					       =  'zh'
           self.assertListEqual(self.tokenizer.prefix_tokens   ,						[self.tokenizer.get_lang_id('zh' )] )
           self.assertListEqual(self.tokenizer.suffix_tokens   ,						[self.tokenizer.eos_token_id] )







     @require_torch
     def   _SCREAMING_SNAKE_CASE     ( self      :    Tuple ):






           """simple docstring"""




           UpperCamelCase					       =  'mr'
           self.tokenizer._switch_to_target_mode()
           self.assertListEqual(self.tokenizer.prefix_tokens   ,						[self.tokenizer.get_lang_id('mr' )] )
           self.assertListEqual(self.tokenizer.suffix_tokens   ,						[self.tokenizer.eos_token_id] )
           self.tokenizer._switch_to_input_mode()
           self.assertListEqual(self.tokenizer.prefix_tokens   ,						[self.tokenizer.get_lang_id(self.tokenizer.src_lang )] )

           UpperCamelCase					       =  'zh'
           self.tokenizer._switch_to_target_mode()
           self.assertListEqual(self.tokenizer.prefix_tokens   ,						[self.tokenizer.get_lang_id('zh' )] )
           self.assertListEqual(self.tokenizer.suffix_tokens   ,						[self.tokenizer.eos_token_id] )
           self.tokenizer._switch_to_input_mode()
           self.assertListEqual(self.tokenizer.prefix_tokens   ,						[self.tokenizer.get_lang_id(self.tokenizer.src_lang )] )







     @require_torch
     def   _SCREAMING_SNAKE_CASE     ( self      :    Any ):






           """simple docstring"""




           UpperCamelCase					       =  self.tokenizer._build_translation_inputs('A test'   ,						return_tensors='pt'   ,						src_lang='en'   ,						tgt_lang='ar' )

           self.assertEqual(
               nested_simplify(_SCREAMING_SNAKE_CASE )   ,						{
                   # en_XX, A, test, EOS
                   'input_ids': [[12_8022, 58, 4183, 2]],
                   'attention_mask': [[1, 1, 1, 1]],
                   # ar_AR
                   'forced_bos_token_id': 12_8006,
               }   ,						)



