


'''simple docstring'''

import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase				:List[Any]        =      get_tests_dir('''fixtures/test_sentencepiece.model''')


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

lowerCAmelCase				:int        =      2_5_0_0_0_4
lowerCAmelCase				:Optional[Any]        =      2_5_0_0_2_0
@require_sentencepiece
@require_tokenizers
class _lowerCamelCase	(						lowercase__		,					unittest.TestCase							):



		'''simple docstring'''







		A_     :      Optional[Any]				   =    MBartTokenizer
		A_     :      List[str]				   =    MBartTokenizerFast
		A_     :      List[Any]				   =    True
		A_     :      int				   =    True







		def        __lowerCAmelCase		( self		:						Union[str, Any]      )  ->			Any:
			super().setUp()

			# We have a SentencePiece fixture for testing
			__magic_name__	:   List[Any]					     =					MBartTokenizer(_A  ,					keep_accents=_A      )
			tokenizer.save_pretrained(self.tmpdirname      )







		def        __lowerCAmelCase		( self		:						Tuple      )  ->			Tuple:
			__magic_name__	:   Union[str, Any]					     =					MBartTokenizer(_A  ,					keep_accents=_A      )

			__magic_name__	:   Union[str, Any]					     =					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]]  ,					)

			__magic_name__	:   Union[str, Any]					     =					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',
			        '.',
			    ]  ,					)
			__magic_name__	:   Optional[Any]					     =					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]
			        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
			    ]  ,					)

			__magic_name__	:   int					     =					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>',
			        '.',
			    ]  ,					)







		def        __lowerCAmelCase		( self		:						Tuple      )  ->			str:
			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

			__magic_name__	:   Any					     =					(self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart', {})
			for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
				with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'      ):
					__magic_name__	:   Union[str, Any]					     =					self.rust_tokenizer_class.from_pretrained(_A  ,					**_A      )
					__magic_name__	:   Any					     =					self.tokenizer_class.from_pretrained(_A  ,					**_A      )

					__magic_name__	:   int					     =					tempfile.mkdtemp()

					__magic_name__	:   List[str]					     =					tokenizer_r.save_pretrained(_A      )
					__magic_name__	:   str					     =					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      )      )
					__magic_name__	:   Dict					     =					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
					__magic_name__	:   Any					     =					tokenizer_r.from_pretrained(_A      )
					__magic_name__	:   Union[str, Any]					     =					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
					__magic_name__	:   List[Any]					     =					tempfile.mkdtemp()

					__magic_name__	:   Tuple					     =					tokenizer_r.save_pretrained(_A  ,					legacy_format=_A      )
					__magic_name__	:   Optional[int]					     =					tokenizer_p.save_pretrained(_A      )

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

					# Checks everything loads correctly in the same way
					__magic_name__	:   Optional[int]					     =					tokenizer_r.from_pretrained(_A      )
					__magic_name__	:   int					     =					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
					__magic_name__	:   int					     =					tempfile.mkdtemp()

					__magic_name__	:   List[str]					     =					tokenizer_r.save_pretrained(_A  ,					legacy_format=_A      )
					__magic_name__	:   int					     =					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
					__magic_name__	:   Optional[Any]					     =					tokenizer_r.from_pretrained(_A      )
					__magic_name__	:   Optional[int]					     =					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 _lowerCamelCase	(						unittest.TestCase							):



		'''simple docstring'''







		A_     :      Tuple				   =    """facebook/mbart-large-en-ro"""
		A_     :      List[str]				   =    [
		    """ 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.""",
		]
		A_     :      Tuple				   =    [
		    """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.""",
		]
		A_     :      List[str]				   =    [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, EN_CODE]







		@classmethod
		def        __lowerCAmelCase		( cls		:						int      )  ->			str:
			__magic_name__	:   MBartTokenizer					     =					MBartTokenizer.from_pretrained(
			    cls.checkpoint_name  ,					src_lang='en_XX'  ,					tgt_lang='ro_RO'      )
			__magic_name__	:   Tuple					     =					1
			return cls







		def        __lowerCAmelCase		( self		:						str      )  ->			List[Any]:
			self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']  ,					250001      )
			self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']  ,					250004      )
			self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']  ,					250020      )







		def        __lowerCAmelCase		( self		:						int      )  ->			Tuple:
			__magic_name__	:   List[str]					     =					self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
			self.assertListEqual(self.expected_src_tokens  ,					_A      )







		def        __lowerCAmelCase		( self		:						int      )  ->			Union[str, Any]:
			self.assertIn(_A  ,					self.tokenizer.all_special_ids      )
			__magic_name__	:   str					     =					[RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
			__magic_name__	:   Optional[int]					     =					self.tokenizer.decode(_A  ,					skip_special_tokens=_A      )
			__magic_name__	:   int					     =					self.tokenizer.decode(generated_ids[1:]  ,					skip_special_tokens=_A      )
			self.assertEqual(_A  ,					_A      )
			self.assertNotIn(self.tokenizer.eos_token  ,					_A      )







		def        __lowerCAmelCase		( self		:						Tuple      )  ->			List[str]:
			__magic_name__	:   List[str]					     =					['this is gunna be a long sentence ' * 20]
			assert isinstance(src_text[0]  ,					_A      )
			__magic_name__	:   List[Any]					     =					10
			__magic_name__	:   List[str]					     =					self.tokenizer(_A  ,					max_length=_A  ,					truncation=_A      ).input_ids[0]
			self.assertEqual(ids[-2]  ,					2      )
			self.assertEqual(ids[-1]  ,					_A      )
			self.assertEqual(len(_A      )  ,					_A      )







		def        __lowerCAmelCase		( self		:						List[Any]      )  ->			Optional[Any]:
			self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']      )  ,					[250026, 250001]      )







		def        __lowerCAmelCase		( self		:						Tuple      )  ->			Any:
			__magic_name__	:   int					     =					tempfile.mkdtemp()
			__magic_name__	:   Dict					     =					self.tokenizer.fairseq_tokens_to_ids
			self.tokenizer.save_pretrained(_A      )
			__magic_name__	:   Dict					     =					MBartTokenizer.from_pretrained(_A      )
			self.assertDictEqual(new_tok.fairseq_tokens_to_ids  ,					_A      )







		@require_torch
		def        __lowerCAmelCase		( self		:						int      )  ->			Tuple:
			__magic_name__	:   Optional[int]					     =					self.tokenizer(self.src_text  ,					text_target=self.tgt_text  ,					padding=_A  ,					return_tensors='pt'      )
			__magic_name__	:   int					     =					shift_tokens_right(batch['labels']  ,					self.tokenizer.pad_token_id      )

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







		@require_torch
		def        __lowerCAmelCase		( self		:						Optional[Any]      )  ->			str:
			__magic_name__	:   str					     =					self.tokenizer(
			    self.src_text  ,					text_target=self.tgt_text  ,					padding=_A  ,					truncation=_A  ,					max_length=len(self.expected_src_tokens      )  ,					return_tensors='pt'  ,					)

			__magic_name__	:   Optional[int]					     =					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      )
			__magic_name__	:   List[Any]					     =					batch.input_ids.tolist()[0]
			self.assertListEqual(self.expected_src_tokens  ,					_A      )
			self.assertEqual(2  ,					batch.decoder_input_ids[0, -1]      )  # EOS
			# Test that special tokens are reset
			self.assertEqual(self.tokenizer.prefix_tokens  ,					[]      )
			self.assertEqual(self.tokenizer.suffix_tokens  ,					[self.tokenizer.eos_token_id, EN_CODE]      )







		def        __lowerCAmelCase		( self		:						Optional[int]      )  ->			Union[str, Any]:
			__magic_name__	:   List[Any]					     =					self.tokenizer(self.src_text  ,					padding=_A  ,					truncation=_A  ,					max_length=3  ,					return_tensors='pt'      )
			__magic_name__	:   Dict					     =					self.tokenizer(
			    text_target=self.tgt_text  ,					padding=_A  ,					truncation=_A  ,					max_length=10  ,					return_tensors='pt'      )
			__magic_name__	:   Tuple					     =					targets['input_ids']
			__magic_name__	:   Dict					     =					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        __lowerCAmelCase		( self		:						Dict      )  ->			Any:
			__magic_name__	:   List[str]					     =					self.tokenizer._build_translation_inputs(
			    'A test'  ,					return_tensors='pt'  ,					src_lang='en_XX'  ,					tgt_lang='ar_AR'      )

			self.assertEqual(
			    nested_simplify(_A      )  ,					{
			        # A, test, EOS, en_XX
			        'input_ids': [[62, 3034, 2, 250004]],
			        'attention_mask': [[1, 1, 1, 1]],
			        # ar_AR
			        'forced_bos_token_id': 250001,
			    }  ,					)



'''simple docstring'''

def lowerCamelCase      (      lowerCAmelCase    :     str		):





	"""simple docstring"""







	return "".join(chr(ord(lowerCAmelCase		) - 32		) if 'a' <= char <= 'z' else char for char in word		)


if __name__ == "__main__":
							from doctest import testmod

							testmod()