






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


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

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

lowerCamelCase : List[Any]						   =       25_00_04
lowerCamelCase : int						   =       25_00_20

@require_sentencepiece
@require_tokenizers
class 		lowerCAmelCase     ( __a      ,       unittest.TestCase			):

					'''simple docstring'''

					_A						:			Optional[int]									=      MBartaaTokenizer
					_A						:			Tuple									=      MBartaaTokenizerFast
					_A						:			Optional[int]									=      True
					_A						:			List[str]									=      True



					def       lowerCAmelCase				(  self				:	int							)			->  Optional[int]:


												"""simple docstring"""

												super().setUp()

												# We have a SentencePiece fixture for testing
												__lowercase      :							Union[str, Any]				=     MBartaaTokenizer(__a		,     src_lang="""en_XX"""		,     tgt_lang="""ro_RO"""		,     keep_accents=__a							)
												tokenizer.save_pretrained(self.tmpdirname							)



					def       lowerCAmelCase				(  self				:	Union[str, Any]							)			->  int:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     """<s>"""
												__lowercase      :							List[Any]				=     0

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



					def       lowerCAmelCase				(  self				:	str							)			->  Optional[Any]:


												"""simple docstring"""

												__lowercase      :							str				=     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       lowerCAmelCase				(  self				:	Any							)			->  str:


												"""simple docstring"""

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



					def       lowerCAmelCase				(  self				:	int							)			->  str:


												"""simple docstring"""

												__lowercase      :							str				=     MBartaaTokenizer(__a		,     src_lang="""en_XX"""		,     tgt_lang="""ro_RO"""		,     keep_accents=__a							)

												__lowercase      :							List[str]				=     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]]		,     )

												__lowercase      :							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""", """."""]		,     )
												__lowercase      :							Union[str, 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]
												    ]		,     )

												__lowercase      :							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>""", """."""]		,     )



					@slow
					def       lowerCAmelCase				(  self				:	Optional[Any]							)			->  str:


												"""simple docstring"""

												__lowercase      :							Optional[int]				=     {"""input_ids""": [[250004, 11062, 82772, 7, 15, 82772, 538, 51529, 237, 17198, 1290, 206, 9, 215175, 1314, 136, 17198, 1290, 206, 9, 56359, 42, 122009, 9, 16466, 16, 87344, 4537, 9, 4717, 78381, 6, 159958, 7, 15, 24480, 618, 4, 527, 22693, 5428, 4, 2777, 24480, 9874, 4, 43523, 594, 4, 803, 18392, 33189, 18, 4, 43523, 24447, 12399, 100, 24955, 83658, 9626, 144057, 15, 839, 22335, 16, 136, 24955, 83658, 83479, 15, 39102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 122009, 115774, 23, 805, 1328, 46876, 7, 136, 53894, 1940, 42227, 41159, 17721, 823, 425, 4, 27512, 98722, 206, 136, 5531, 4970, 919, 17336, 5, 2], [250004, 20080, 618, 83, 82775, 47, 479, 9, 1517, 73, 53894, 333, 80581, 110117, 18811, 5256, 1295, 51, 152526, 297, 7986, 390, 124416, 538, 35431, 214, 98, 15044, 25737, 136, 7108, 43701, 23, 756, 135355, 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], [250004, 581, 63773, 119455, 6, 147797, 88203, 7, 645, 70, 21, 3285, 10269, 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       lowerCAmelCase				(  self				:	Optional[int]							)			->  Optional[Any]:


												"""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

												__lowercase      :							Tuple				=     (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})"							):
																										__lowercase      :							int				=     self.rust_tokenizer_class.from_pretrained(__a		,     **__a							)
																										__lowercase      :							Union[str, Any]				=     self.tokenizer_class.from_pretrained(__a		,     **__a							)

																										__lowercase      :							Tuple				=     tempfile.mkdtemp()

																										__lowercase      :							Dict				=     tokenizer_r.save_pretrained(__a							)
																										__lowercase      :							Union[str, Any]				=     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							)							)
																										__lowercase      :							Tuple				=     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
																										__lowercase      :							Any				=     tokenizer_r.from_pretrained(__a							)
																										__lowercase      :							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
																										__lowercase      :							Dict				=     tempfile.mkdtemp()

																										__lowercase      :							int				=     tokenizer_r.save_pretrained(__a		,     legacy_format=__a							)
																										__lowercase      :							Any				=     tokenizer_p.save_pretrained(__a							)

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

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

																										__lowercase      :							int				=     tokenizer_r.save_pretrained(__a		,     legacy_format=__a							)
																										__lowercase      :							Optional[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
																										__lowercase      :							Optional[Any]				=     tokenizer_r.from_pretrained(__a							)
																										__lowercase      :							List[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							)							)

																										shutil.rmtree(__a							)







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

					'''simple docstring'''

					_A						:			Optional[int]									=      '''facebook/mbart-large-50-one-to-many-mmt'''
					_A						:			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						:			str									=      [
					    '''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						:			Any									=      [EN_CODE, 8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2]



					@classmethod
					def       lowerCAmelCase				(  cls				:	Any							)			->  List[str]:


												"""simple docstring"""

												__lowercase      :							MBartaaTokenizer				=     MBartaaTokenizer.from_pretrained(
												    cls.checkpoint_name		,     src_lang="""en_XX"""		,     tgt_lang="""ro_RO"""							)
												__lowercase      :							Tuple				=     1
												return cls



					def       lowerCAmelCase				(  self				:	int							)			->  Any:


												"""simple docstring"""

												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							)
												self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""mr_IN"""]		,     250038							)



					def       lowerCAmelCase				(  self				:	List[Any]							)			->  str:


												"""simple docstring"""

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



					def       lowerCAmelCase				(  self				:	List[str]							)			->  Optional[Any]:


												"""simple docstring"""

												self.assertIn(__a		,     self.tokenizer.all_special_ids							)
												__lowercase      :							List[Any]				=     [RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
												__lowercase      :							Optional[Any]				=     self.tokenizer.decode(__a		,     skip_special_tokens=__a							)
												__lowercase      :							List[str]				=     self.tokenizer.decode(generated_ids[1:]		,     skip_special_tokens=__a							)
												self.assertEqual(__a		,     __a							)
												self.assertNotIn(self.tokenizer.eos_token		,     __a							)



					def       lowerCAmelCase				(  self				:	str							)			->  List[Any]:


												"""simple docstring"""

												__lowercase      :							Any				=     ["""this is gunna be a long sentence """ * 20]
												assert isinstance(src_text[0]		,     __a							)
												__lowercase      :							int				=     10
												__lowercase      :							Optional[Any]				=     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       lowerCAmelCase				(  self				:	List[str]							)			->  Any:


												"""simple docstring"""

												self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]							)		,     [250053, 250001]							)



					def       lowerCAmelCase				(  self				:	Optional[int]							)			->  List[str]:


												"""simple docstring"""

												__lowercase      :							List[str]				=     tempfile.mkdtemp()
												__lowercase      :							Union[str, Any]				=     self.tokenizer.fairseq_tokens_to_ids
												self.tokenizer.save_pretrained(__a							)
												__lowercase      :							List[Any]				=     MBartaaTokenizer.from_pretrained(__a							)
												self.assertDictEqual(new_tok.fairseq_tokens_to_ids		,     __a							)



					@require_torch
					def       lowerCAmelCase				(  self				:	List[Any]							)			->  List[Any]:


												"""simple docstring"""

												__lowercase      :							Optional[int]				=     self.tokenizer(self.src_text		,     text_target=self.tgt_text		,     padding=__a		,     return_tensors="""pt"""							)
												__lowercase      :							Dict				=     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       lowerCAmelCase				(  self				:	str							)			->  List[Any]:


												"""simple docstring"""

												__lowercase      :							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"""		,     )
												__lowercase      :							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							)
												__lowercase      :							Optional[Any]				=     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       lowerCAmelCase				(  self				:	Any							)			->  Dict:


												"""simple docstring"""

												__lowercase      :							List[Any]				=     self.tokenizer(self.src_text		,     padding=__a		,     truncation=__a		,     max_length=3		,     return_tensors="""pt"""							)
												__lowercase      :							str				=     self.tokenizer(
												    text_target=self.tgt_text		,     padding=__a		,     truncation=__a		,     max_length=10		,     return_tensors="""pt"""							)
												__lowercase      :							List[str]				=     targets["""input_ids"""]
												__lowercase      :							Optional[Any]				=     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				:	List[Any]							)			->  Any:


												"""simple docstring"""

												__lowercase      :							Dict				=     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""": [[250004, 62, 3034, 2]],
												        """attention_mask""": [[1, 1, 1, 1]],
												        # ar_AR
												        """forced_bos_token_id""": 250001,
												    }		,     )







from argparse import ArgumentParser

from . import BaseTransformersCLICommand
def       snake_case_		(     lowerCAmelCase_       :						Dict      ):
							return DownloadCommand(args.model       ,       args.cache_dir       ,       args.force       ,       args.trust_remote_code      )



class 		lowerCAmelCase     ( __a			):

					'''simple docstring'''

					@staticmethod
					def       lowerCAmelCase				(  __a				:	ArgumentParser							)			->  Optional[Any]:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     parser.add_parser("""download"""							)
												download_parser.add_argument(
												    """--cache-dir"""		,     type=__a		,     default=__a		,     help="""Path to location to store the models"""							)
												download_parser.add_argument(
												    """--force"""		,     action="""store_true"""		,     help="""Force the model to be download even if already in cache-dir"""							)
												download_parser.add_argument(
												    """--trust-remote-code"""		,     action="""store_true"""		,     help="""Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you've reviewed the code as it will execute on your local machine"""		,     )
												download_parser.add_argument("""model"""		,     type=__a		,     help="""Name of the model to download"""							)
												download_parser.set_defaults(func=__a							)



					def __init__(  self				:	Dict		,     __a				:	str		,     __a				:	str		,     __a				:	bool		,     __a				:	bool							)			->  Union[str, Any]:


												"""simple docstring"""

												__lowercase      :							Dict				=     model
												__lowercase      :							List[Any]				=     cache
												__lowercase      :							Any				=     force
												__lowercase      :							Optional[int]				=     trust_remote_code



					def       lowerCAmelCase				(  self				:	str							)			->  List[str]:


												"""simple docstring"""

												from ..models.auto import AutoModel, AutoTokenizer

												AutoModel.from_pretrained(
												    self._model		,     cache_dir=self._cache		,     force_download=self._force		,     trust_remote_code=self._trust_remote_code							)
												AutoTokenizer.from_pretrained(
												    self._model		,     cache_dir=self._cache		,     force_download=self._force		,     trust_remote_code=self._trust_remote_code							)