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


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

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

_lowercase							:      Union[str, Any]      							=2_5_0_0_0_4
_lowercase							:      Any      							=2_5_0_0_2_0



@require_sentencepiece
@require_tokenizers
class  SCREAMING_SNAKE_CASE_ (					lowerCAmelCase_   ,						unittest.TestCase			):
  '''simple docstring'''


  lowercase		:     Any            =				MBartaaTokenizer
  lowercase		:     Union[str, Any]            =				MBartaaTokenizerFast
  lowercase		:     Dict            =				True
  lowercase		:     str            =				True







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

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







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict     )    ->				int:
         A						:     Optional[int]         ='<s>'
         A						:     str         =0

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







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[Any]     )    ->				int:
         A						:     Optional[Any]         =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(SCREAMING_SNAKE_CASE__     )      ,	10_54     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Union[str, Any]     )    ->				Tuple:
         self.assertEqual(self.get_tokenizer().vocab_size      ,	10_54     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[int]     )    ->				Tuple:
         A						:     List[Any]         =MBartaaTokenizer(SCREAMING_SNAKE_CASE__      ,	src_lang='en_XX'      ,	tgt_lang='ro_RO'      ,	keep_accents=SCREAMING_SNAKE_CASE__     )

         A						:     str         =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_85, 46, 10, 1_70, 3_82]]      ,	)

         A						:     List[str]         =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						:     Dict         =tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__     )
         self.assertListEqual(
             SCREAMING_SNAKE_CASE__      ,	[
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             ]      ,	)

         A						:     Optional[int]         =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>', '.']      ,	)







  @slow
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Any     )    ->				str:
         # fmt: off
         A						:     Union[str, Any]         ={'input_ids': [[25_00_04, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [25_00_04, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 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_00_04, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 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=SCREAMING_SNAKE_CASE__      ,	model_name='facebook/mbart-large-50'      ,	revision='d3913889c59cd5c9e456b269c376325eabad57e2'      ,	)







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[int]     )    ->				Dict:
         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						:     Any         =(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						:     Dict         =self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__      ,	**SCREAMING_SNAKE_CASE__     )
                       A						:     Tuple         =self.tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__      ,	**SCREAMING_SNAKE_CASE__     )

                       A						:     str         =tempfile.mkdtemp()

                       A						:     Optional[Any]         =tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE__     )
                       A						:     Optional[int]         =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						:     Dict         =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						:     Tuple         =tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE__     )
                       A						:     Optional[Any]         =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						:     Union[str, Any]         =tempfile.mkdtemp()

                       A						:     Any         =tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE__      ,	legacy_format=SCREAMING_SNAKE_CASE__     )
                       A						:     Dict         =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						:     List[Any]         =tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE__     )
                       A						:     Tuple         =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						:     Optional[Any]         =tempfile.mkdtemp()

                       A						:     List[Any]         =tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE__      ,	legacy_format=SCREAMING_SNAKE_CASE__     )
                       A						:     List[Any]         =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						:     List[str]         =tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE__     )
                       A						:     Optional[Any]         =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  SCREAMING_SNAKE_CASE_ (					unittest.TestCase			):
  '''simple docstring'''


  lowercase		:     List[str]            =				"facebook/mbart-large-50-one-to-many-mmt"
  lowercase		:     int            =				[
      " 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.",
  ]
  lowercase		:     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.",
  ]
  lowercase		:     str            =				[EN_CODE, 8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2]







  @classmethod
  def 		SCREAMING_SNAKE_CASE_		(				cls    :					int     )    ->				Dict:
         A						:     MBartaaTokenizer         =MBartaaTokenizer.from_pretrained(
             cls.checkpoint_name      ,	src_lang='en_XX'      ,	tgt_lang='ro_RO'     )
         A						:     Any         =1
         return cls







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[Any]     )    ->				Dict:
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']      ,	25_00_01     )
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']      ,	25_00_04     )
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']      ,	25_00_20     )
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']      ,	25_00_38     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					str     )    ->				str:
         A						:     Optional[Any]         =self.tokenizer.batch_encode_plus(self.src_text     ).input_ids[0]
         self.assertListEqual(self.expected_src_tokens      ,	SCREAMING_SNAKE_CASE__     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[str]     )    ->				Any:
         self.assertIn(SCREAMING_SNAKE_CASE__      ,	self.tokenizer.all_special_ids     )
         A						:     List[str]         =[RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
         A						:     Any         =self.tokenizer.decode(SCREAMING_SNAKE_CASE__      ,	skip_special_tokens=SCREAMING_SNAKE_CASE__     )
         A						:     str         =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 		SCREAMING_SNAKE_CASE_		(				self    :					Tuple     )    ->				Any:
         A						:     Optional[int]         =['this is gunna be a long sentence ' * 20]
         assert isinstance(src_text[0]      ,	SCREAMING_SNAKE_CASE__     )
         A						:     Tuple         =10
         A						:     List[Any]         =self.tokenizer(SCREAMING_SNAKE_CASE__      ,	max_length=SCREAMING_SNAKE_CASE__      ,	truncation=SCREAMING_SNAKE_CASE__     ).input_ids[0]
         self.assertEqual(ids[0]      ,	SCREAMING_SNAKE_CASE__     )
         self.assertEqual(ids[-1]      ,	2     )
         self.assertEqual(len(SCREAMING_SNAKE_CASE__     )      ,	SCREAMING_SNAKE_CASE__     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[int]     )    ->				Optional[int]:
         self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']     )      ,	[25_00_53, 25_00_01]     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					int     )    ->				Any:
         A						:     Dict         =tempfile.mkdtemp()
         A						:     str         =self.tokenizer.fairseq_tokens_to_ids
         self.tokenizer.save_pretrained(SCREAMING_SNAKE_CASE__     )
         A						:     Union[str, Any]         =MBartaaTokenizer.from_pretrained(SCREAMING_SNAKE_CASE__     )
         self.assertDictEqual(new_tok.fairseq_tokens_to_ids      ,	SCREAMING_SNAKE_CASE__     )







  @require_torch
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[Any]     )    ->				Dict:
         A						:     Optional[int]         =self.tokenizer(self.src_text      ,	text_target=self.tgt_text      ,	padding=SCREAMING_SNAKE_CASE__      ,	return_tensors='pt'     )
         A						:     str         =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 		SCREAMING_SNAKE_CASE_		(				self    :					str     )    ->				Any:
         A						:     Union[str, Any]         =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						:     List[str]         =shift_tokens_right(batch['labels']      ,	self.tokenizer.pad_token_id     )

         self.assertIsInstance(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__     )

         self.assertEqual((2, 14)      ,	batch.input_ids.shape     )
         self.assertEqual((2, 14)      ,	batch.attention_mask.shape     )
         A						:     Dict         =batch.input_ids.tolist()[0]
         self.assertListEqual(self.expected_src_tokens      ,	SCREAMING_SNAKE_CASE__     )
         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 		SCREAMING_SNAKE_CASE_		(				self    :					Dict     )    ->				str:
         A						:     int         =self.tokenizer(self.src_text      ,	padding=SCREAMING_SNAKE_CASE__      ,	truncation=SCREAMING_SNAKE_CASE__      ,	max_length=3      ,	return_tensors='pt'     )
         A						:     Tuple         =self.tokenizer(
             text_target=self.tgt_text      ,	padding=SCREAMING_SNAKE_CASE__      ,	truncation=SCREAMING_SNAKE_CASE__      ,	max_length=10      ,	return_tensors='pt'     )
         A						:     Tuple         =targets['input_ids']
         A						:     Any         =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]      ,	10     )







  @require_torch
  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[str]     )    ->				Any:
         A						:     Dict         =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__     )      ,	{
                 # en_XX, A, test, EOS
                 'input_ids': [[25_00_04, 62, 30_34, 2]],
                 'attention_mask': [[1, 1, 1, 1]],
                 # ar_AR
                 'forced_bos_token_id': 25_00_01,
             }      ,	)







import inspect
import warnings
from typing import Any, Dict, Optional, Union

from packaging import version



def A__  (			*lowercase:     Tuple,		lowercase:     Optional[Union[Dict, Any]] = None,		lowercase:     Dict=True,		lowercase:     Any=2					)				->		List[Any]:
       from .. import __version__

       A						:     Optional[Any]         =take_from
       A						:     Union[str, Any]         =()
       if not isinstance(args[0],		lowercase					):
              A						:     List[str]         =(args,)

       for attribute, version_name, message in args:
              if version.parse(version.parse(lowercase					).base_version					) >= version.parse(lowercase					):
                     raise ValueError(
                         F'The deprecation tuple {(attribute, version_name, message)} should be removed since diffusers\''
                         F' version {__version__} is >= {version_name}'					)

              A						:     Tuple         =None
              if isinstance(lowercase,		lowercase					) and attribute in deprecated_kwargs:
                     values += (deprecated_kwargs.pop(lowercase					),)
                     A						:     Union[str, Any]         =F'The `{attribute}` argument is deprecated and will be removed in version {version_name}.'
              elif hasattr(lowercase,		lowercase					):
                     values += (getattr(lowercase,		lowercase					),)
                     A						:     Optional[Any]         =F'The `{attribute}` attribute is deprecated and will be removed in version {version_name}.'
              elif deprecated_kwargs is None:
                     A						:     List[Any]         =F'`{attribute}` is deprecated and will be removed in version {version_name}.'

              if warning is not None:
                     A						:     List[Any]         =warning + ' ' if standard_warn else ''
                     warnings.warn(warning + message,		lowercase,		stacklevel=lowercase					)

       if isinstance(lowercase,		lowercase					) and len(lowercase					) > 0:
              A						:     Any         =inspect.getouterframes(inspect.currentframe()					)[1]
              A						:     int         =call_frame.filename
              A						:     int         =call_frame.lineno
              A						:     Optional[int]         =call_frame.function
              A  ,  A						:     int         =next(iter(deprecated_kwargs.items()					)					)
              raise TypeError(F'{function} in {filename} line {line_number-1} got an unexpected keyword argument `{key}`'					)

       if len(lowercase					) == 0:
              return
       elif len(lowercase					) == 1:
              return values[0]
       return values






