






"""simple docstring"""






import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE						:						int					   =       get_tests_dir('''fixtures/test_sentencepiece.model''')

if is_torch_available():
					from transformers.models.mbart.modeling_mbart import shift_tokens_right

SCREAMING_SNAKE_CASE						:						Any					   =       250_004
SCREAMING_SNAKE_CASE						:						Optional[Any]					   =       250_020





@require_sentencepiece
@require_tokenizers
class       snake_case_       (    _lowerCamelCase    ,							unittest.TestCase       ):
	SCREAMING_SNAKE_CASE_:							Optional[int]   			=					MBartaaTokenizer
	SCREAMING_SNAKE_CASE_:							Dict   			=					MBartaaTokenizerFast
	SCREAMING_SNAKE_CASE_:							Union[str, Any]   			=					True
	SCREAMING_SNAKE_CASE_:							Dict   			=					True


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					super().setUp()

					# We have a SentencePiece fixture for testing
					A__							 =       MBartaaTokenizer(__a  ,					src_lang='en_XX'  ,					tgt_lang='ro_RO'  ,					keep_accents=__a						)
					tokenizer.save_pretrained(self.tmpdirname						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       '<s>'
					A__							 =       0

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


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       list(self.get_tokenizer().get_vocab().keys()						)

					self.assertEqual(vocab_keys[0]  ,					'<s>'						)
					self.assertEqual(vocab_keys[1]  ,					'<pad>'						)
					self.assertEqual(vocab_keys[-1]  ,					'<mask>'						)
					self.assertEqual(len(__a						)  ,					1054						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					self.assertEqual(self.get_tokenizer().vocab_size  ,					1054						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       MBartaaTokenizer(__a  ,					src_lang='en_XX'  ,					tgt_lang='ro_RO'  ,					keep_accents=__a						)

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

					self.assertListEqual(
					    tokenizer.convert_tokens_to_ids(__a						)  ,					[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]  ,					)

					A__							 =       tokenizer.tokenize('I was born in 92000, and this is falsé.'						)
					self.assertListEqual(
					    __a  ,					[SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '9', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', 'é', '.']  ,					)
					A__							 =       tokenizer.convert_tokens_to_ids(__a						)
					self.assertListEqual(
					    __a  ,					[
					        value + tokenizer.fairseq_offset
					        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
					    ]  ,					)

					A__							 =       tokenizer.convert_ids_to_tokens(__a						)
					self.assertListEqual(
					    __a  ,					[SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '<unk>', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', '<unk>', '.']  ,					)


	@slow
	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       {'input_ids': [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 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], [25_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 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]], '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, 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], [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]]}  # noqa: E501
					# fmt: on

					self.tokenizer_integration_test_util(
					    expected_encoding=__a  ,					model_name='facebook/mbart-large-50'  ,					revision='d3913889c59cd5c9e456b269c376325eabad57e2'  ,					)






	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					if not self.test_slow_tokenizer:
									# as we don't have a slow version, we can't compare the outputs between slow and fast versions
									return

					A__							 =       (self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart50', {})
					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
													A__							 =       self.rust_tokenizer_class.from_pretrained(__a  ,					**__a						)
													A__							 =       self.tokenizer_class.from_pretrained(__a  ,					**__a						)

													A__							 =       tempfile.mkdtemp()

													A__							 =       tokenizer_r.save_pretrained(__a						)
													A__							 =       tokenizer_p.save_pretrained(__a						)

													# Checks it save with the same files + the tokenizer.json file for the fast one
													self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files						)						)
													A__							 =       tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f						)
													self.assertSequenceEqual(__a  ,					__a						)

													# Checks everything loads correctly in the same way
													A__							 =       tokenizer_r.from_pretrained(__a						)
													A__							 =       tokenizer_p.from_pretrained(__a						)

													# Check special tokens are set accordingly on Rust and Python
													for key in tokenizer_pp.special_tokens_map:
																	self.assertTrue(hasattr(__a  ,					__a						)						)
																	# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																	# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

													shutil.rmtree(__a						)

													# Save tokenizer rust, legacy_format=True
													A__							 =       tempfile.mkdtemp()

													A__							 =       tokenizer_r.save_pretrained(__a  ,					legacy_format=__a						)
													A__							 =       tokenizer_p.save_pretrained(__a						)

													# Checks it save with the same files
													self.assertSequenceEqual(__a  ,					__a						)

													# Checks everything loads correctly in the same way
													A__							 =       tokenizer_r.from_pretrained(__a						)
													A__							 =       tokenizer_p.from_pretrained(__a						)

													# Check special tokens are set accordingly on Rust and Python
													for key in tokenizer_pp.special_tokens_map:
																	self.assertTrue(hasattr(__a  ,					__a						)						)

													shutil.rmtree(__a						)

													# Save tokenizer rust, legacy_format=False
													A__							 =       tempfile.mkdtemp()

													A__							 =       tokenizer_r.save_pretrained(__a  ,					legacy_format=__a						)
													A__							 =       tokenizer_p.save_pretrained(__a						)

													# Checks it saved the tokenizer.json file
													self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files						)						)

													# Checks everything loads correctly in the same way
													A__							 =       tokenizer_r.from_pretrained(__a						)
													A__							 =       tokenizer_p.from_pretrained(__a						)

													# Check special tokens are set accordingly on Rust and Python
													for key in tokenizer_pp.special_tokens_map:
																	self.assertTrue(hasattr(__a  ,					__a						)						)

													shutil.rmtree(__a						)





@require_torch
@require_sentencepiece
@require_tokenizers
class       snake_case_       (    unittest.TestCase       ):
	SCREAMING_SNAKE_CASE_:							Any   			=					"""facebook/mbart-large-50-one-to-many-mmt"""
	SCREAMING_SNAKE_CASE_:							List[Any]   			=					[
	    """ UN Chief Says There Is No Military Solution in Syria""",
	    """ Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
	]
	SCREAMING_SNAKE_CASE_:							List[Any]   			=					[
	    """Şeful ONU declară că nu există o soluţie militară în Siria""",
	    """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
	    """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
	    """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
	]
	SCREAMING_SNAKE_CASE_:							Optional[Any]   			=					[EN_CODE, 82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2]


	@classmethod
	def       _UpperCAmelCase						(      cls						):


					"""simple docstring"""

					A__							 =       MBartaaTokenizer.from_pretrained(
					    cls.checkpoint_name  ,					src_lang='en_XX'  ,					tgt_lang='ro_RO'						)
					A__							 =       1
					return cls


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']  ,					25_0001						)
					self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']  ,					25_0004						)
					self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']  ,					25_0020						)
					self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']  ,					25_0038						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       self.tokenizer.batch_encode_plus(self.src_text						).input_ids[0]
					self.assertListEqual(self.expected_src_tokens  ,					__a						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					self.assertIn(__a  ,					self.tokenizer.all_special_ids						)
					A__							 =       [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
					A__							 =       self.tokenizer.decode(__a  ,					skip_special_tokens=__a						)
					A__							 =       self.tokenizer.decode(generated_ids[1:]  ,					skip_special_tokens=__a						)
					self.assertEqual(__a  ,					__a						)
					self.assertNotIn(self.tokenizer.eos_token  ,					__a						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       ['this is gunna be a long sentence ' * 20]
					assert isinstance(src_text[0]  ,					__a						)
					A__							 =       10
					A__							 =       self.tokenizer(__a  ,					max_length=__a  ,					truncation=__a						).input_ids[0]
					self.assertEqual(ids[0]  ,					__a						)
					self.assertEqual(ids[-1]  ,					2						)
					self.assertEqual(len(__a						)  ,					__a						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']						)  ,					[25_0053, 25_0001]						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       tempfile.mkdtemp()
					A__							 =       self.tokenizer.fairseq_tokens_to_ids
					self.tokenizer.save_pretrained(__a						)
					A__							 =       MBartaaTokenizer.from_pretrained(__a						)
					self.assertDictEqual(new_tok.fairseq_tokens_to_ids  ,					__a						)


	@require_torch
	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       self.tokenizer(self.src_text  ,					text_target=self.tgt_text  ,					padding=__a  ,					return_tensors='pt'						)
					A__							 =       shift_tokens_right(batch['labels']  ,					self.tokenizer.pad_token_id						)

					# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
					assert batch.input_ids[1][0] == EN_CODE
					assert batch.input_ids[1][-1] == 2
					assert batch.labels[1][0] == RO_CODE
					assert batch.labels[1][-1] == 2
					assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]


	@require_torch
	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       self.tokenizer(
					    self.src_text  ,					text_target=self.tgt_text  ,					padding=__a  ,					truncation=__a  ,					max_length=len(self.expected_src_tokens						)  ,					return_tensors='pt'  ,					)
					A__							 =       shift_tokens_right(batch['labels']  ,					self.tokenizer.pad_token_id						)

					self.assertIsInstance(__a  ,					__a						)

					self.assertEqual((2, 14)  ,					batch.input_ids.shape						)
					self.assertEqual((2, 14)  ,					batch.attention_mask.shape						)
					A__							 =       batch.input_ids.tolist()[0]
					self.assertListEqual(self.expected_src_tokens  ,					__a						)
					self.assertEqual(2  ,					batch.decoder_input_ids[0, 0]						)  # decoder_start_token_id
					# Test that special tokens are reset
					self.assertEqual(self.tokenizer.prefix_tokens  ,					[EN_CODE]						)
					self.assertEqual(self.tokenizer.suffix_tokens  ,					[self.tokenizer.eos_token_id]						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       self.tokenizer(self.src_text  ,					padding=__a  ,					truncation=__a  ,					max_length=3  ,					return_tensors='pt'						)
					A__							 =       self.tokenizer(
					    text_target=self.tgt_text  ,					padding=__a  ,					truncation=__a  ,					max_length=10  ,					return_tensors='pt'						)
					A__							 =       targets['input_ids']
					A__							 =       shift_tokens_right(__a  ,					self.tokenizer.pad_token_id						)

					self.assertEqual(batch.input_ids.shape[1]  ,					3						)
					self.assertEqual(batch.decoder_input_ids.shape[1]  ,					10						)






	@require_torch
	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       self.tokenizer._build_translation_inputs(
					    'A test'  ,					return_tensors='pt'  ,					src_lang='en_XX'  ,					tgt_lang='ar_AR'						)

					self.assertEqual(
					    nested_simplify(__a						)  ,					{
					        # en_XX, A, test, EOS
					        'input_ids': [[25_0004, 62, 3034, 2]],
					        'attention_mask': [[1, 1, 1, 1]],
					        # ar_AR
					        'forced_bos_token_id': 25_0001,
					    }  ,					)










"""simple docstring"""






def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__				):
				return 1 if input_a == input_a else 0



def  __lowerCamelCase					(					):
				assert xnor_gate(0       ,0				) == 1
				assert xnor_gate(0       ,1				) == 0
				assert xnor_gate(1       ,0				) == 0
				assert xnor_gate(1       ,1				) == 1


if __name__ == "__main__":
					print(xnor_gate(0, 0))
					print(xnor_gate(0, 1))
					print(xnor_gate(1, 0))
					print(xnor_gate(1, 1))


