



"""simple docstring"""
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():
					SCREAMING_SNAKE_CASE_				= get_tests_dir("""fixtures/test_sentencepiece.model""")


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

SCREAMING_SNAKE_CASE_				= 12_80_22
SCREAMING_SNAKE_CASE_				= 12_80_28




@require_sentencepiece
class 			snake_case_						(						a_     ,unittest.TestCase				):
							__lowerCAmelCase    					=					MaMaaaTokenizer
							__lowerCAmelCase    					=					False
							__lowerCAmelCase    					=					False
							__lowerCAmelCase    					=					True






							def snake_case_  (   self      ):
									super().setUp()

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

									a_     :      Optional[int] 						=     MaMaaaTokenizer.from_pretrained(self.tmpdirname      )
									tokenizer.save_pretrained(self.tmpdirname      )






							def snake_case_  (   self			,     **a_      ):
									return MaMaaaTokenizer.from_pretrained(self.tmpdirname			,     **a_      )






							def snake_case_  (   self			,     a_      ):
									return (
									    "This is a test",
									    "This is a test",
									)






							def snake_case_  (   self      ):
									a_     :      str 						=     "</s>"
									a_     :      List[str] 						=     0

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






							def snake_case_  (   self      ):
									a_     :      Optional[int] 						=     self.get_tokenizer()
									a_     :      List[Any] 						=     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(a_      )			,     tokenizer.vocab_size + len(tokenizer.get_added_vocab()      )      )






							@unittest.skip("Skip this test while all models are still to be uploaded."      )
							def snake_case_  (   self      ):
									pass






							def snake_case_  (   self      ):
									a_     :      List[str] 						=     self.get_tokenizer()

									a_     :      Tuple 						=     tokenizer.tokenize("This is a test"      )
									self.assertListEqual(a_			,     ["▁This", "▁is", "▁a", "▁t", "est"]      )

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

									a_     :      Tuple 						=     tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]      )
									self.assertListEqual(a_			,     ["▁This", "▁is", "▁a", "▁t", "est"]      )

									a_     :      Dict 						=     tokenizer.convert_tokens_to_string(a_      )
									self.assertEqual(a_			,     "This is a test"      )






							@slow
							def snake_case_  (   self      ):
									# fmt: off
									a_     :      List[Any] 						=     {"input_ids": [[1_2_8_0_2_2, 1_1_0_1_0_8, 3_9_7, 1_1, 3_8_2_7_2, 2_2_4_7, 1_2_4_8_1_1, 2_8_5, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 3_9_5_3_4, 4_4_2_8, 3_9_7, 1_0_1_9, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 4_1_3_3_7, 1_6_7_8_6, 2_4_1, 7, 2_0_2_1_4, 1_7, 1_2_5_6_9_0, 1_0_3_9_8, 7, 4_4_3_7_8, 5_8_0_6_9, 6_8_3_4_2, 7_7_9_8, 7_3_4_3, 1_1, 2_9_9, 3_3_3_1_0, 4, 1_5_8, 3_7_3_5_0, 9_4_0_7_7, 4_5_6_9, 2_9_9, 3_3_3_1_0, 9_0, 4, 5_2_8_4_0, 2_9_0, 4, 3_1_2_7_0, 1_1_2, 2_9_9, 6_8_2, 4, 5_2_8_4_0, 3_9_9_5_3, 1_4_0_7_9, 1_9_3, 5_2_5_1_9, 9_0_8_9_4, 1_7_8_9_4, 1_2_0_6_9_7, 1_1, 4_0_4_4_5, 5_5_1, 1_7, 1_0_1_9, 5_2_5_1_9, 9_0_8_9_4, 1_7_7_5_6, 9_6_3, 1_1, 4_0_4_4_5, 4_8_0, 1_7, 9_7_9_2, 1_1_2_0, 5_1_7_3, 1_3_9_3, 6_2_4_0, 1_6_7_8_6, 2_4_1, 1_2_0_9_9_6, 2_8, 1_2_4_5, 1_3_9_3, 1_1_8_2_4_0, 1_1_1_2_3, 1_0_1_9, 9_3_6_1_2, 2_6_9_1, 1_0_6_1_8, 9_8_0_5_8, 1_2_0_4_0_9, 1_9_2_8, 2_7_9, 4, 4_0_6_8_3, 3_6_7, 1_7_8, 2_0_7, 1_0_1_9, 1_0_3, 1_0_3_1_2_1, 5_0_6, 6_5_2_9_6, 5, 2], [1_2_8_0_2_2, 2_1_2_1_7, 3_6_7, 1_1_7, 1_2_5_4_5_0, 1_2_8, 7_1_9, 7, 7_3_0_8, 4_0, 9_3_6_1_2, 1_2_6_6_9, 1_1_1_6, 1_6_7_0_4, 7_1, 1_7_7_8_5, 3_6_9_9, 1_5_5_9_2, 3_5, 1_4_4, 9_5_8_4, 2_4_1, 1_1_9_4_3, 7_1_3, 9_5_0, 7_9_9, 2_2_4_7, 8_8_4_2_7, 1_5_0, 1_4_9, 1_1_8_8_1_3, 1_2_0_7_0_6, 1_0_1_9, 1_0_6_9_0_6, 8_1_5_1_8, 2_8, 1_2_2_4, 2_2_7_9_9, 3_9_7, 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_2_8_0_2_2, 1_6_5_8, 1_2_3_3_1_1, 5_1_5_5, 5_5_7_8, 4_7_2_2, 2_7_9, 1_4_9_4_7, 2_3_6_6, 1_1_2_0, 1_1_9_7, 1_4, 1_3_4_8, 9_2_3_2, 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=a_			,     model_name="facebook/m2m100_418M"			,     revision="c168bae485c864188cf9aa0e4108b0b6934dc91e"			,     )




@require_torch
@require_sentencepiece
@require_tokenizers
class 			snake_case_						(						unittest.TestCase				):
							__lowerCAmelCase    					=					"facebook/m2m100_418M"
							__lowerCAmelCase    					=					[
							    "In my opinion, there are two levels of response from the French government.",
							    "NSA Affair Emphasizes Complete Lack of Debate on Intelligence",
							]
							__lowerCAmelCase    					=					[
							    "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
							__lowerCAmelCase    					=					[EN_CODE, 5_9_3, 1_9_4_9, 1_1_5_7_8_1, 4, 7_1_5_8_6, 4_2_3_4, 6_0_6_3_3, 1_2_6_2_3_3, 4_3_2, 1_2_3_8_0_8, 1_5_5_9_2, 1_1_9_7, 1_1_7_1_3_2, 1_2_0_6_1_8, 5, 2]






							@classmethod
							def snake_case_  (   cls      ):
									a_     :      MaMaaaTokenizer 						=     MaMaaaTokenizer.from_pretrained(
									    cls.checkpoint_name			,     src_lang="en"			,     tgt_lang="fr"      )
									a_     :      Optional[Any] 						=     1
									return cls






							def snake_case_  (   self      ):
									self.assertEqual(self.tokenizer.get_lang_id("ar"      )			,     1_2_8_0_0_6      )
									self.assertEqual(self.tokenizer.get_lang_id("en"      )			,     1_2_8_0_2_2      )
									self.assertEqual(self.tokenizer.get_lang_id("ro"      )			,     1_2_8_0_7_6      )
									self.assertEqual(self.tokenizer.get_lang_id("mr"      )			,     1_2_8_0_6_3      )






							def snake_case_  (   self      ):
									a_     :      Tuple 						=     self.tokenizer.get_vocab()
									self.assertEqual(len(a_      )			,     self.tokenizer.vocab_size      )
									self.assertEqual(vocab["<unk>"]			,     3      )
									self.assertIn(self.tokenizer.get_lang_token("en"      )			,     a_      )






							def snake_case_  (   self      ):
									a_     :      Optional[int] 						=     "en"
									a_     :      Optional[int] 						=     self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
									self.assertListEqual(self.expected_src_tokens			,     a_      )






							def snake_case_  (   self      ):
									self.assertIn(a_			,     self.tokenizer.all_special_ids      )
									# fmt: off
									a_     :      List[Any] 						=     [FR_CODE, 5_3_6_4, 8_2, 8_6_4_2, 4, 2_9_4, 4_7, 8, 1_4_0_2_8, 1_3_6, 3_2_8_6, 9_7_0_6, 6, 9_0_7_9_7, 6, 1_4_4_0_1_2, 1_6_2, 8_8_1_2_8, 3_0_0_6_1, 5, 2]
									# fmt: on
									a_     :      List[Any] 						=     self.tokenizer.decode(a_			,     skip_special_tokens=a_      )
									a_     :      Dict 						=     self.tokenizer.decode(generated_ids[1:]			,     skip_special_tokens=a_      )
									self.assertEqual(a_			,     a_      )
									self.assertNotIn(self.tokenizer.eos_token			,     a_      )






							def snake_case_  (   self      ):
									a_     :      Any 						=     tempfile.mkdtemp()
									a_     :      List[str] 						=     self.tokenizer.lang_token_to_id
									self.tokenizer.save_pretrained(a_      )
									a_     :      Tuple 						=     MaMaaaTokenizer.from_pretrained(a_      )
									self.assertDictEqual(new_tok.lang_token_to_id			,     a_      )






							@require_torch
							def snake_case_  (   self      ):
									a_     :      Optional[Any] 						=     "en"
									a_     :      Dict 						=     "fr"

									a_     :      Optional[int] 						=     self.tokenizer(self.src_text			,     text_target=self.tgt_text			,     padding=a_			,     return_tensors="pt"      )

									a_     :      List[str] 						=     shift_tokens_right(
									    batch["labels"]			,     self.tokenizer.pad_token_id			,     self.tokenizer.eos_token_id      )

									for k in batch:
											a_     :      Dict 						=     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 snake_case_  (   self      ):
									a_     :      Dict 						=     "mr"
									self.assertListEqual(self.tokenizer.prefix_tokens			,     [self.tokenizer.get_lang_id("mr"      )]      )
									self.assertListEqual(self.tokenizer.suffix_tokens			,     [self.tokenizer.eos_token_id]      )

									a_     :      List[str] 						=     "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 snake_case_  (   self      ):
									a_     :      List[str] 						=     "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      )]      )

									a_     :      Union[str, Any] 						=     "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 snake_case_  (   self      ):
									a_     :      Optional[int] 						=     self.tokenizer._build_translation_inputs("A test"			,     return_tensors="pt"			,     src_lang="en"			,     tgt_lang="ar"      )

									self.assertEqual(
									    nested_simplify(a_      )			,     {
									        # en_XX, A, test, EOS
									        "input_ids": [[1_2_8_0_2_2, 5_8, 4_1_8_3, 2]],
									        "attention_mask": [[1, 1, 1, 1]],
									        # ar_AR
									        "forced_bos_token_id": 1_2_8_0_0_6,
									    }			,     )




"""simple docstring"""
def        lowerCAmelCase_						(							SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__ = False	)			->      bool:
		if n == 2:
				return True
		if not n % 2 or n < 2:
				return False
		if n > 5 and n % 10 not in (1, 3, 7, 9):  # can quickly check last digit
				return False
		if n > 3_317_044_064_679_887_385_961_981 and not allow_probable:
				raise ValueError(
				    "Warning: upper bound of deterministic test is exceeded. "
				    "Pass allow_probable=True to allow probabilistic test. "
				    "A return value of True indicates a probable prime."	)
		# array bounds provided by analysis
		a_     :      Optional[Any] 						=     [
		    2_047,
		    1_373_653,
		    25_326_001,
		    3_215_031_751,
		    2_152_302_898_747,
		    3_474_749_660_383,
		    341_550_071_728_321,
		    1,
		    3_825_123_056_546_413_051,
		    1,
		    1,
		    318_665_857_834_031_151_167_461,
		    3_317_044_064_679_887_385_961_981,
		]

		a_     :      Optional[int] 						=     [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
		for idx, _p in enumerate(SCREAMING_SNAKE_CASE__, 1	):
				if n < _p:
						# then we have our last prime to check
						a_     :      List[Any] 						=     primes[:idx]
						break
		a_						,				a_     :      Tuple 						=     n - 1, 0
		# break up n -1 into a power of 2 (s) and
		# remaining odd component
		# essentially, solve for d * 2 ** s == n - 1
		while d % 2 == 0:
				d //= 2
				s += 1
		for prime in plist:
				a_     :      str 						=     False
				for r in range(SCREAMING_SNAKE_CASE__	):
						a_     :      List[str] 						=     pow(SCREAMING_SNAKE_CASE__, d * 2**r, SCREAMING_SNAKE_CASE__	)
						# see article for analysis explanation for m
						if (r == 0 and m == 1) or ((m + 1) % n == 0):
								a_     :      List[Any] 						=     True
								# this loop will not determine compositeness
								break
				if pr:
						continue
				# if pr is False, then the above loop never evaluated to true,
				# and the n MUST be composite
				return False
		return True



def        lowerCAmelCase_						(							)			->      None:
		assert not miller_rabin(561	)
		assert miller_rabin(563	)
		# 2047

		assert not miller_rabin(838_201	)
		assert miller_rabin(838_207	)
		# 1_373_653

		assert not miller_rabin(17_316_001	)
		assert miller_rabin(17_316_017	)
		# 25_326_001

		assert not miller_rabin(3_078_386_641	)
		assert miller_rabin(3_078_386_653	)
		# 3_215_031_751

		assert not miller_rabin(1_713_045_574_801	)
		assert miller_rabin(1_713_045_574_819	)
		# 2_152_302_898_747

		assert not miller_rabin(2_779_799_728_307	)
		assert miller_rabin(2_779_799_728_327	)
		# 3_474_749_660_383

		assert not miller_rabin(113_850_023_909_441	)
		assert miller_rabin(113_850_023_909_527	)
		# 341_550_071_728_321

		assert not miller_rabin(1_275_041_018_848_804_351	)
		assert miller_rabin(1_275_041_018_848_804_391	)
		# 3_825_123_056_546_413_051

		assert not miller_rabin(79_666_464_458_507_787_791_867	)
		assert miller_rabin(79_666_464_458_507_787_791_951	)
		# 318_665_857_834_031_151_167_461

		assert not miller_rabin(552_840_677_446_647_897_660_333	)
		assert miller_rabin(552_840_677_446_647_897_660_359	)
		# 3_317_044_064_679_887_385_961_981
		# upper limit for probabilistic test


if __name__ == "__main__":
					test_miller_rabin()