






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_           = get_tests_dir('fixtures/test_sentencepiece.model')


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

lowerCAmelCase_           = 250_004
lowerCAmelCase_           = 250_020
@require_sentencepiece
@require_tokenizers
class      UpperCamelCase (				snake_case__			,       unittest.TestCase ):







		"""simple docstring"""



		snake_case    =   MBartTokenizer
		snake_case    =   MBartTokenizerFast
		snake_case    =   True
		snake_case    =   True
		def       A(  self		:       Any		)    ->   Optional[int]:


						'''simple docstring'''
						super().setUp()

						# We have a SentencePiece fixture for testing
						A	 =      MBartTokenizer(_SCREAMING_SNAKE_CASE						,keep_accents=_SCREAMING_SNAKE_CASE		)
						tokenizer.save_pretrained(self.tmpdirname		)
		def       A(  self		:       Union[str, Any]		)    ->   List[str]:


						'''simple docstring'''
						A	 =      MBartTokenizer(_SCREAMING_SNAKE_CASE						,keep_accents=_SCREAMING_SNAKE_CASE		)

						A	 =      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		)						,[value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]						,)

						A	 =      tokenizer.tokenize('I was born in 92000, and this is falsé.'		)
						self.assertListEqual(
						    _SCREAMING_SNAKE_CASE						,[
						        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(_SCREAMING_SNAKE_CASE		)
						self.assertListEqual(
						    _SCREAMING_SNAKE_CASE						,[
						        value + tokenizer.fairseq_offset
						        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
						        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
						    ]						,)

						A	 =      tokenizer.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE		)
						self.assertListEqual(
						    _SCREAMING_SNAKE_CASE						,[
						        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       A(  self		:       List[str]		)    ->   Optional[int]:


						'''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-mbart', {})
						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(_SCREAMING_SNAKE_CASE						,**_SCREAMING_SNAKE_CASE		)
														A	 =      self.tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE						,**_SCREAMING_SNAKE_CASE		)

														A	 =      tempfile.mkdtemp()

														A	 =      tokenizer_r.save_pretrained(_SCREAMING_SNAKE_CASE		)
														A	 =      tokenizer_p.save_pretrained(_SCREAMING_SNAKE_CASE		)

														# 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(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)

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

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

														shutil.rmtree(_SCREAMING_SNAKE_CASE		)

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

														A	 =      tokenizer_r.save_pretrained(_SCREAMING_SNAKE_CASE						,legacy_format=_SCREAMING_SNAKE_CASE		)
														A	 =      tokenizer_p.save_pretrained(_SCREAMING_SNAKE_CASE		)

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

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

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

														shutil.rmtree(_SCREAMING_SNAKE_CASE		)

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

														A	 =      tokenizer_r.save_pretrained(_SCREAMING_SNAKE_CASE						,legacy_format=_SCREAMING_SNAKE_CASE		)
														A	 =      tokenizer_p.save_pretrained(_SCREAMING_SNAKE_CASE		)

														# 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(_SCREAMING_SNAKE_CASE		)
														A	 =      tokenizer_p.from_pretrained(_SCREAMING_SNAKE_CASE		)

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

														shutil.rmtree(_SCREAMING_SNAKE_CASE		)


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







		"""simple docstring"""



		snake_case    =   "facebook/mbart-large-en-ro"
		snake_case    =   [
		    " 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.",
		]
		snake_case    =   [
		    "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.",
		]
		snake_case    =   [8_2_7_4, 1_2_7_8_7_3, 2_5_9_1_6, 7, 8_6_2_2, 2_0_7_1, 4_3_8, 6_7_4_8_5, 5_3, 1_8_7_8_9_5, 2_3, 5_1_7_1_2, 2, EN_CODE]
		@classmethod
		def       A(  cls		:       str		)    ->   Tuple:


						'''simple docstring'''
						A	 =      MBartTokenizer.from_pretrained(
						    cls.checkpoint_name						,src_lang='en_XX'						,tgt_lang='ro_RO'		)
						A	 =      1
						return cls
		def       A(  self		:       Union[str, Any]		)    ->   str:


						'''simple docstring'''
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']						,2_5_0_0_0_1		)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']						,2_5_0_0_0_4		)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']						,2_5_0_0_2_0		)
		def       A(  self		:       Optional[Any]		)    ->   Any:


						'''simple docstring'''
						A	 =      self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
						self.assertListEqual(self.expected_src_tokens						,_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       Optional[Any]		)    ->   List[str]:


						'''simple docstring'''
						self.assertIn(_SCREAMING_SNAKE_CASE						,self.tokenizer.all_special_ids		)
						A	 =      [RO_CODE, 8_8_4, 9_0_1_9, 9_6, 9, 9_1_6, 8_6_7_9_2, 3_6, 1_8_7_4_3, 1_5_5_9_6, 5, 2]
						A	 =      self.tokenizer.decode(_SCREAMING_SNAKE_CASE						,skip_special_tokens=_SCREAMING_SNAKE_CASE		)
						A	 =      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       A(  self		:       List[str]		)    ->   List[str]:


						'''simple docstring'''
						A	 =      ['this is gunna be a long sentence ' * 2_0]
						assert isinstance(src_text[0]						,_SCREAMING_SNAKE_CASE		)
						A	 =      1_0
						A	 =      self.tokenizer(_SCREAMING_SNAKE_CASE						,max_length=_SCREAMING_SNAKE_CASE						,truncation=_SCREAMING_SNAKE_CASE		).input_ids[0]
						self.assertEqual(ids[-2]						,2		)
						self.assertEqual(ids[-1]						,_SCREAMING_SNAKE_CASE		)
						self.assertEqual(len(_SCREAMING_SNAKE_CASE		)						,_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       Optional[int]		)    ->   List[str]:


						'''simple docstring'''
						self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']		)						,[2_5_0_0_2_6, 2_5_0_0_0_1]		)
		def       A(  self		:       Union[str, Any]		)    ->   Tuple:


						'''simple docstring'''
						A	 =      tempfile.mkdtemp()
						A	 =      self.tokenizer.fairseq_tokens_to_ids
						self.tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE		)
						A	 =      MBartTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE		)
						self.assertDictEqual(new_tok.fairseq_tokens_to_ids						,_SCREAMING_SNAKE_CASE		)
		@require_torch
		def       A(  self		:       str		)    ->   Optional[int]:


						'''simple docstring'''
						A	 =      self.tokenizer(self.src_text						,text_target=self.tgt_text						,padding=_SCREAMING_SNAKE_CASE						,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][-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       A(  self		:       Tuple		)    ->   Any:


						'''simple docstring'''
						A	 =      self.tokenizer(
						    self.src_text						,text_target=self.tgt_text						,padding=_SCREAMING_SNAKE_CASE						,truncation=_SCREAMING_SNAKE_CASE						,max_length=len(self.expected_src_tokens		)						,return_tensors='pt'						,)

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

						self.assertIsInstance(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)

						self.assertEqual((2, 1_4)						,batch.input_ids.shape		)
						self.assertEqual((2, 1_4)						,batch.attention_mask.shape		)
						A	 =      batch.input_ids.tolist()[0]
						self.assertListEqual(self.expected_src_tokens						,_SCREAMING_SNAKE_CASE		)
						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       A(  self		:       Dict		)    ->   Any:


						'''simple docstring'''
						A	 =      self.tokenizer(self.src_text						,padding=_SCREAMING_SNAKE_CASE						,truncation=_SCREAMING_SNAKE_CASE						,max_length=3						,return_tensors='pt'		)
						A	 =      self.tokenizer(
						    text_target=self.tgt_text						,padding=_SCREAMING_SNAKE_CASE						,truncation=_SCREAMING_SNAKE_CASE						,max_length=1_0						,return_tensors='pt'		)
						A	 =      targets['input_ids']
						A	 =      shift_tokens_right(_SCREAMING_SNAKE_CASE						,self.tokenizer.pad_token_id		)

						self.assertEqual(batch.input_ids.shape[1]						,3		)
						self.assertEqual(batch.decoder_input_ids.shape[1]						,1_0		)







		@require_torch
		def       A(  self		:       int		)    ->   Optional[int]:


						'''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(_SCREAMING_SNAKE_CASE		)						,{
						        # A, test, EOS, en_XX
						        'input_ids': [[6_2, 3_0_3_4, 2, 2_5_0_0_0_4]],
						        'attention_mask': [[1, 1, 1, 1]],
						        # ar_AR
						        'forced_bos_token_id': 2_5_0_0_0_1,
						    }						,)













import copy
import re
class      UpperCamelCase :







		"""simple docstring"""



		snake_case    =   "hp"
		snake_case    =   {}
		snake_case    =   None
		@classmethod
		def       A(  cls		:       Union[str, Any]						,_SCREAMING_SNAKE_CASE		:       int						,_SCREAMING_SNAKE_CASE		:       List[Any]		)    ->   int:


						'''simple docstring'''
						A	 =      prefix
						A	 =      defaults
						cls.build_naming_info()
		@staticmethod
		def       A(  _SCREAMING_SNAKE_CASE		:       List[str]						,_SCREAMING_SNAKE_CASE		:       List[Any]		)    ->   Optional[Any]:


						'''simple docstring'''
						if len(_SCREAMING_SNAKE_CASE		) == 0:
										return ""
						A	 =      None
						if any(char.isdigit() for char in word		):
										raise Exception(f'Parameters should not contain numbers: \'{word}\' contains a number'		)
						if word in info["short_word"]:
										return info["short_word"][word]
						for prefix_len in range(1						,len(_SCREAMING_SNAKE_CASE		) + 1		):
										A	 =      word[:prefix_len]
										if prefix in info["reverse_short_word"]:
														continue
										else:
														A	 =      prefix
														break

						if short_word is None:
										# Paranoid fallback
										def int_to_alphabetic(_SCREAMING_SNAKE_CASE		:       Optional[int]		):
														A	 =      ''
														while integer != 0:
																		A	 =      chr(ord('A'		) + integer % 1_0		) + s
																		integer //= 1_0
														return s

										A	 =      0
										while True:
														A	 =      word + '#' + int_to_alphabetic(_SCREAMING_SNAKE_CASE		)
														if sword in info["reverse_short_word"]:
																		continue
														else:
																		A	 =      sword
																		break

						A	 =      short_word
						A	 =      word
						return short_word
		@staticmethod
		def       A(  _SCREAMING_SNAKE_CASE		:       Optional[int]						,_SCREAMING_SNAKE_CASE		:       Optional[int]		)    ->   int:


						'''simple docstring'''
						A	 =      param_name.split('_'		)

						A	 =      [TrialShortNamer.shortname_for_word(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		) for word in words]

						# We try to create a separatorless short name, but if there is a collision we have to fallback
						# to a separated short name
						A	 =      ['', '_']

						for separator in separators:
										A	 =      separator.join(_SCREAMING_SNAKE_CASE		)
										if shortname not in info["reverse_short_param"]:
														A	 =      shortname
														A	 =      param_name
														return shortname

						return param_name
		@staticmethod
		def       A(  _SCREAMING_SNAKE_CASE		:       Optional[Any]						,_SCREAMING_SNAKE_CASE		:       Optional[int]		)    ->   List[str]:


						'''simple docstring'''
						A	 =      TrialShortNamer.shortname_for_key(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)
						A	 =      short_name
						A	 =      param_name
		@classmethod
		def       A(  cls		:       Optional[int]		)    ->   str:


						'''simple docstring'''
						if cls.NAMING_INFO is not None:
										return

						A	 =      {
						    'short_word': {},
						    'reverse_short_word': {},
						    'short_param': {},
						    'reverse_short_param': {},
						}

						A	 =      list(cls.DEFAULTS.keys()		)

						for k in field_keys:
										cls.add_new_param_name(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)

						A	 =      info
		@classmethod
		def       A(  cls		:       List[str]						,_SCREAMING_SNAKE_CASE		:       str		)    ->   List[Any]:


						'''simple docstring'''
						cls.build_naming_info()
						assert cls.PREFIX is not None
						A	 =      [copy.copy(cls.PREFIX		)]

						for k, v in params.items():
										if k not in cls.DEFAULTS:
														raise Exception(f'You should provide a default value for the param name {k} with value {v}'		)
										if v == cls.DEFAULTS[k]:
														# The default value is not added to the name
														continue

										A	 =      cls.NAMING_INFO['short_param'][k]

										if isinstance(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		):
														A	 =      1 if v else 0

										A	 =      '' if isinstance(_SCREAMING_SNAKE_CASE						,(int, float)		) else '-'
										A	 =      f'{key}{sep}{v}'
										name.append(_SCREAMING_SNAKE_CASE		)

						return "_".join(_SCREAMING_SNAKE_CASE		)







		@classmethod
		def       A(  cls		:       int						,_SCREAMING_SNAKE_CASE		:       Optional[int]		)    ->   str:


						'''simple docstring'''
						A	 =      repr[len(cls.PREFIX		) + 1 :]
						if repr == "":
										A	 =      []
						else:
										A	 =      repr.split('_'		)

						A	 =      {}

						for value in values:
										if "-" in value:
														A ,		A	 =      value.split('-'		)
										else:
														A	 =      re.sub('[0-9.]'						,''						,_SCREAMING_SNAKE_CASE		)
														A	 =      float(re.sub('[^0-9.]'						,''						,_SCREAMING_SNAKE_CASE		)		)

										A	 =      cls.NAMING_INFO['reverse_short_param'][p_k]

										A	 =      p_v

						for k in cls.DEFAULTS:
										if k not in parameters:
														A	 =      cls.DEFAULTS[k]

						return parameters





