






'''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


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


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

SCREAMING_SNAKE_CASE__     =       2_5_0_0_0_4
SCREAMING_SNAKE_CASE__     =       2_5_0_0_2_0






@require_sentencepiece
@require_tokenizers
class     a_						(      lowerCamelCase     ,	unittest.TestCase    ):
  lowercase							=				MBartTokenizer
  lowercase							=				MBartTokenizerFast
  lowercase							=				True
  lowercase							=				True

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



        """simple docstring"""






        super().setUp()

        # We have a SentencePiece fixture for testing
        UpperCamelCase      = MBartTokenizer(_SCREAMING_SNAKE_CASE      ,		keep_accents=_SCREAMING_SNAKE_CASE				)
        tokenizer.save_pretrained(self.tmpdirname				)

  def   A__						(				self				)  ->				Optional[Any]:



        """simple docstring"""






        UpperCamelCase      = MBartTokenizer(_SCREAMING_SNAKE_CASE      ,		keep_accents=_SCREAMING_SNAKE_CASE				)

        UpperCamelCase      = 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 [285, 46, 10, 170, 382]]      ,		)

        UpperCamelCase      = 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""",
                """.""",
            ]      ,		)
        UpperCamelCase      = 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, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
            ]      ,		)

        UpperCamelCase      = 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				)  ->				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

        UpperCamelCase      = (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})"				):
                    UpperCamelCase      = self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE      ,		**_SCREAMING_SNAKE_CASE				)
                    UpperCamelCase      = self.tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE      ,		**_SCREAMING_SNAKE_CASE				)

                    UpperCamelCase      = tempfile.mkdtemp()

                    UpperCamelCase      = tokenizer_r.save_pretrained(_SCREAMING_SNAKE_CASE				)
                    UpperCamelCase      = 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				)				)
                    UpperCamelCase      = 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
                    UpperCamelCase      = tokenizer_r.from_pretrained(_SCREAMING_SNAKE_CASE				)
                    UpperCamelCase      = 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
                    UpperCamelCase      = tempfile.mkdtemp()

                    UpperCamelCase      = tokenizer_r.save_pretrained(_SCREAMING_SNAKE_CASE      ,		legacy_format=_SCREAMING_SNAKE_CASE				)
                    UpperCamelCase      = 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
                    UpperCamelCase      = tokenizer_r.from_pretrained(_SCREAMING_SNAKE_CASE				)
                    UpperCamelCase      = 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
                    UpperCamelCase      = tempfile.mkdtemp()

                    UpperCamelCase      = tokenizer_r.save_pretrained(_SCREAMING_SNAKE_CASE      ,		legacy_format=_SCREAMING_SNAKE_CASE				)
                    UpperCamelCase      = 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
                    UpperCamelCase      = tokenizer_r.from_pretrained(_SCREAMING_SNAKE_CASE				)
                    UpperCamelCase      = 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     a_						(      unittest.TestCase    ):
  lowercase							=				"""facebook/mbart-large-en-ro"""
  lowercase							=				[
      """ 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							=				[
      """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							=				[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   A__						(				cls				)  ->				Any:



        """simple docstring"""






        UpperCamelCase      = MBartTokenizer.from_pretrained(
            cls.checkpoint_name      ,		src_lang="""en_XX"""      ,		tgt_lang="""ro_RO"""				)
        UpperCamelCase      = 1
        return cls

  def   A__						(				self				)  ->				Union[str, 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				)

  def   A__						(				self				)  ->				Optional[Any]:



        """simple docstring"""






        UpperCamelCase      = self.tokenizer.batch_encode_plus(self.src_text				).input_ids[0]
        self.assertListEqual(self.expected_src_tokens      ,		_SCREAMING_SNAKE_CASE				)

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



        """simple docstring"""






        self.assertIn(_SCREAMING_SNAKE_CASE      ,		self.tokenizer.all_special_ids				)
        UpperCamelCase      = [RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
        UpperCamelCase      = self.tokenizer.decode(_SCREAMING_SNAKE_CASE      ,		skip_special_tokens=_SCREAMING_SNAKE_CASE				)
        UpperCamelCase      = 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				)  ->				Any:



        """simple docstring"""






        UpperCamelCase      = ["""this is gunna be a long sentence """ * 20]
        assert isinstance(src_text[0]      ,		_SCREAMING_SNAKE_CASE				)
        UpperCamelCase      = 10
        UpperCamelCase      = 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]:



        """simple docstring"""






        self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]				)      ,		[250026, 250001]				)

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



        """simple docstring"""






        UpperCamelCase      = tempfile.mkdtemp()
        UpperCamelCase      = self.tokenizer.fairseq_tokens_to_ids
        self.tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE				)
        UpperCamelCase      = MBartTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE				)
        self.assertDictEqual(new_tok.fairseq_tokens_to_ids      ,		_SCREAMING_SNAKE_CASE				)

  @require_torch
  def   A__						(				self				)  ->				Any:



        """simple docstring"""






        UpperCamelCase      = self.tokenizer(self.src_text      ,		text_target=self.tgt_text      ,		padding=_SCREAMING_SNAKE_CASE      ,		return_tensors="""pt"""				)
        UpperCamelCase      = 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				)  ->				Any:



        """simple docstring"""






        UpperCamelCase      = 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"""      ,		)

        UpperCamelCase      = 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				)
        UpperCamelCase      = 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:



        """simple docstring"""






        UpperCamelCase      = self.tokenizer(self.src_text      ,		padding=_SCREAMING_SNAKE_CASE      ,		truncation=_SCREAMING_SNAKE_CASE      ,		max_length=3      ,		return_tensors="""pt"""				)
        UpperCamelCase      = self.tokenizer(
            text_target=self.tgt_text      ,		padding=_SCREAMING_SNAKE_CASE      ,		truncation=_SCREAMING_SNAKE_CASE      ,		max_length=10      ,		return_tensors="""pt"""				)
        UpperCamelCase      = targets["""input_ids"""]
        UpperCamelCase      = 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   A__						(				self				)  ->				Dict:



        """simple docstring"""






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








'''simple docstring'''

from PIL import Image







def    lowercase__			(				__UpperCamelCase		,						__UpperCamelCase   )->			Image:

      def brightness(__UpperCamelCase   ) -> float:
            return 128 + level + (c - 128)

      if not -255.0 <= level <= 255.0:
            raise ValueError("""level must be between -255.0 (black) and 255.0 (white)"""   )
      return img.point(__UpperCamelCase   )


if __name__ == "__main__":
     # Load image
     with Image.open('image_data/lena.jpg') as img:
          # Change brightness to 100
          SCREAMING_SNAKE_CASE__     =       change_brightness(img, 1_0_0)
          brigt_img.save('image_data/lena_brightness.png', format='png')
