


'''simple docstring'''



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


__UpperCAmelCase    :List[str]				       =     get_tests_dir("fixtures/test_sentencepiece.model")

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

__UpperCAmelCase    :int				       =     2_5_0_0_0_4
__UpperCAmelCase    :Optional[int]				       =     2_5_0_0_2_0



@require_sentencepiece
@require_tokenizers
class 			a       (	lowercase__			,						unittest.TestCase ):


     """simple docstring"""






     SCREAMING_SNAKE_CASE :				List[str]							     =     MBartaaTokenizer
     SCREAMING_SNAKE_CASE :				List[Any]							     =     MBartaaTokenizerFast
     SCREAMING_SNAKE_CASE :				Any							     =     True
     SCREAMING_SNAKE_CASE :				Dict							     =     True

     def 				lowerCamelCase__				(       self  :	str    )		->							Tuple:
          super().setUp()

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

     def 				lowerCamelCase__				(       self  :	Tuple    )		->							str:
          __UpperCAmelCase			:				Optional[int]													=    "<s>"
          __UpperCAmelCase			:				Any													=    0

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

     def 				lowerCamelCase__				(       self  :	Optional[int]    )		->							str:
          __UpperCAmelCase			:				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(__lowerCamelCase    )							,				1054    )

     def 				lowerCamelCase__				(       self  :	Optional[Any]    )		->							List[Any]:
          self.assertEqual(self.get_tokenizer().vocab_size							,				1054    )

     def 				lowerCamelCase__				(       self  :	Tuple    )		->							List[str]:
          __UpperCAmelCase			:				Dict													=    MBartaaTokenizer(__lowerCamelCase							,				src_lang='''en_XX'''							,				tgt_lang='''ro_RO'''							,				keep_accents=__lowerCamelCase    )

          __UpperCAmelCase			:				str													=    tokenizer.tokenize('''This is a test'''    )
          self.assertListEqual(__lowerCamelCase							,				['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']    )

          self.assertListEqual(
              tokenizer.convert_tokens_to_ids(__lowerCamelCase    )							,				[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]							,				)

          __UpperCAmelCase			:				Dict													=    tokenizer.tokenize('''I was born in 92000, and this is falsé.'''    )
          self.assertListEqual(
              __lowerCamelCase							,				[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			:				Union[str, Any]													=    tokenizer.convert_tokens_to_ids(__lowerCamelCase    )
          self.assertListEqual(
              __lowerCamelCase							,				[
                  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]
              ]							,				)

          __UpperCAmelCase			:				Tuple													=    tokenizer.convert_ids_to_tokens(__lowerCamelCase    )
          self.assertListEqual(
              __lowerCamelCase							,				[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[int]    )		->							Tuple:
          __UpperCAmelCase			:				str													=    {"input_ids": [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 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_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 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=__lowerCamelCase							,				model_name='''facebook/mbart-large-50'''							,				revision='''d3913889c59cd5c9e456b269c376325eabad57e2'''							,				)






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



          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			:				Dict													=    (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})'    ):
                    __UpperCAmelCase			:				int													=    self.rust_tokenizer_class.from_pretrained(__lowerCamelCase							,				**__lowerCamelCase    )
                    __UpperCAmelCase			:				List[str]													=    self.tokenizer_class.from_pretrained(__lowerCamelCase							,				**__lowerCamelCase    )

                    __UpperCAmelCase			:				List[Any]													=    tempfile.mkdtemp()

                    __UpperCAmelCase			:				List[str]													=    tokenizer_r.save_pretrained(__lowerCamelCase    )
                    __UpperCAmelCase			:				Optional[int]													=    tokenizer_p.save_pretrained(__lowerCamelCase    )

                    # 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			:				List[Any]													=    tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f    )
                    self.assertSequenceEqual(__lowerCamelCase							,				__lowerCamelCase    )

                    # Checks everything loads correctly in the same way
                    __UpperCAmelCase			:				List[str]													=    tokenizer_r.from_pretrained(__lowerCamelCase    )
                    __UpperCAmelCase			:				Any													=    tokenizer_p.from_pretrained(__lowerCamelCase    )

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

                    shutil.rmtree(__lowerCamelCase    )

                    # Save tokenizer rust, legacy_format=True
                    __UpperCAmelCase			:				List[str]													=    tempfile.mkdtemp()

                    __UpperCAmelCase			:				Tuple													=    tokenizer_r.save_pretrained(__lowerCamelCase							,				legacy_format=__lowerCamelCase    )
                    __UpperCAmelCase			:				str													=    tokenizer_p.save_pretrained(__lowerCamelCase    )

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

                    # Checks everything loads correctly in the same way
                    __UpperCAmelCase			:				Union[str, Any]													=    tokenizer_r.from_pretrained(__lowerCamelCase    )
                    __UpperCAmelCase			:				str													=    tokenizer_p.from_pretrained(__lowerCamelCase    )

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

                    shutil.rmtree(__lowerCamelCase    )

                    # Save tokenizer rust, legacy_format=False
                    __UpperCAmelCase			:				Optional[Any]													=    tempfile.mkdtemp()

                    __UpperCAmelCase			:				Union[str, Any]													=    tokenizer_r.save_pretrained(__lowerCamelCase							,				legacy_format=__lowerCamelCase    )
                    __UpperCAmelCase			:				str													=    tokenizer_p.save_pretrained(__lowerCamelCase    )

                    # 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			:				Optional[int]													=    tokenizer_r.from_pretrained(__lowerCamelCase    )
                    __UpperCAmelCase			:				Optional[int]													=    tokenizer_p.from_pretrained(__lowerCamelCase    )

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

                    shutil.rmtree(__lowerCamelCase    )



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


     """simple docstring"""






     SCREAMING_SNAKE_CASE :				Optional[Any]							     =     "facebook/mbart-large-50-one-to-many-mmt"
     SCREAMING_SNAKE_CASE :				Optional[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.",
     ]
     SCREAMING_SNAKE_CASE :				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.",
     ]
     SCREAMING_SNAKE_CASE :				Union[str, Any]							     =     [EN_CODE, 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]

     @classmethod
     def 				lowerCamelCase__				(       cls  :	Optional[int]    )		->							str:
          __UpperCAmelCase			:				MBartaaTokenizer													=    MBartaaTokenizer.from_pretrained(
              cls.checkpoint_name							,				src_lang='''en_XX'''							,				tgt_lang='''ro_RO'''    )
          __UpperCAmelCase			:				Optional[int]													=    1
          return cls

     def 				lowerCamelCase__				(       self  :	Optional[Any]    )		->							Any:
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ar_AR''']							,				25_0001    )
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''en_EN''']							,				25_0004    )
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ro_RO''']							,				25_0020    )
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''mr_IN''']							,				25_0038    )

     def 				lowerCamelCase__				(       self  :	Optional[Any]    )		->							Dict:
          __UpperCAmelCase			:				Union[str, Any]													=    self.tokenizer.batch_encode_plus(self.src_text    ).input_ids[0]
          self.assertListEqual(self.expected_src_tokens							,				__lowerCamelCase    )

     def 				lowerCamelCase__				(       self  :	List[str]    )		->							Any:
          self.assertIn(__lowerCamelCase							,				self.tokenizer.all_special_ids    )
          __UpperCAmelCase			:				List[Any]													=    [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
          __UpperCAmelCase			:				List[str]													=    self.tokenizer.decode(__lowerCamelCase							,				skip_special_tokens=__lowerCamelCase    )
          __UpperCAmelCase			:				List[Any]													=    self.tokenizer.decode(generated_ids[1:]							,				skip_special_tokens=__lowerCamelCase    )
          self.assertEqual(__lowerCamelCase							,				__lowerCamelCase    )
          self.assertNotIn(self.tokenizer.eos_token							,				__lowerCamelCase    )

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

     def 				lowerCamelCase__				(       self  :	int    )		->							Optional[Any]:
          self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['''<mask>''', '''ar_AR''']    )							,				[25_0053, 25_0001]    )

     def 				lowerCamelCase__				(       self  :	str    )		->							int:
          __UpperCAmelCase			:				int													=    tempfile.mkdtemp()
          __UpperCAmelCase			:				List[str]													=    self.tokenizer.fairseq_tokens_to_ids
          self.tokenizer.save_pretrained(__lowerCamelCase    )
          __UpperCAmelCase			:				Optional[int]													=    MBartaaTokenizer.from_pretrained(__lowerCamelCase    )
          self.assertDictEqual(new_tok.fairseq_tokens_to_ids							,				__lowerCamelCase    )

     @require_torch
     def 				lowerCamelCase__				(       self  :	Optional[Any]    )		->							Union[str, Any]:
          __UpperCAmelCase			:				Tuple													=    self.tokenizer(self.src_text							,				text_target=self.tgt_text							,				padding=__lowerCamelCase							,				return_tensors='''pt'''    )
          __UpperCAmelCase			:				List[Any]													=    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  :	Tuple    )		->							List[str]:
          __UpperCAmelCase			:				List[str]													=    self.tokenizer(
              self.src_text							,				text_target=self.tgt_text							,				padding=__lowerCamelCase							,				truncation=__lowerCamelCase							,				max_length=len(self.expected_src_tokens    )							,				return_tensors='''pt'''							,				)
          __UpperCAmelCase			:				Tuple													=    shift_tokens_right(batch['''labels''']							,				self.tokenizer.pad_token_id    )

          self.assertIsInstance(__lowerCamelCase							,				__lowerCamelCase    )

          self.assertEqual((2, 14)							,				batch.input_ids.shape    )
          self.assertEqual((2, 14)							,				batch.attention_mask.shape    )
          __UpperCAmelCase			:				str													=    batch.input_ids.tolist()[0]
          self.assertListEqual(self.expected_src_tokens							,				__lowerCamelCase    )
          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  :	str    )		->							Optional[Any]:
          __UpperCAmelCase			:				int													=    self.tokenizer(self.src_text							,				padding=__lowerCamelCase							,				truncation=__lowerCamelCase							,				max_length=3							,				return_tensors='''pt'''    )
          __UpperCAmelCase			:				str													=    self.tokenizer(
              text_target=self.tgt_text							,				padding=__lowerCamelCase							,				truncation=__lowerCamelCase							,				max_length=10							,				return_tensors='''pt'''    )
          __UpperCAmelCase			:				Any													=    targets["input_ids"]
          __UpperCAmelCase			:				Union[str, Any]													=    shift_tokens_right(__lowerCamelCase							,				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  :	Optional[Any]    )		->							List[Any]:
          __UpperCAmelCase			:				Dict													=    self.tokenizer._build_translation_inputs(
              '''A test'''							,				return_tensors='''pt'''							,				src_lang='''en_XX'''							,				tgt_lang='''ar_AR'''    )

          self.assertEqual(
              nested_simplify(__lowerCamelCase    )							,				{
                  # en_XX, A, test, EOS
                  '''input_ids''': [[25_0004, 62, 3034, 2]],
                  '''attention_mask''': [[1, 1, 1, 1]],
                  # ar_AR
                  '''forced_bos_token_id''': 25_0001,
              }							,				)








'''simple docstring'''



import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey



class 			a       :


     """simple docstring"""






     def __init__(       self  :	Union[str, Any]							,				snake_case  :	List[Any]							,				snake_case  :	int							,				snake_case  :	int    )		->							List[Any]:
          if dst_width < 0 or dst_height < 0:
               raise ValueError('''Destination width/height should be > 0'''    )

          __UpperCAmelCase			:				str													=    img
          __UpperCAmelCase			:				List[Any]													=    img.shape[1]
          __UpperCAmelCase			:				Optional[Any]													=    img.shape[0]
          __UpperCAmelCase			:				Dict													=    dst_width
          __UpperCAmelCase			:				List[str]													=    dst_height

          __UpperCAmelCase			:				Union[str, Any]													=    self.src_w / self.dst_w
          __UpperCAmelCase			:				List[str]													=    self.src_h / self.dst_h

          __UpperCAmelCase			:				Optional[int]													=    (
              np.ones((self.dst_h, self.dst_w, 3)							,				np.uinta    ) * 255
          )

     def 				lowerCamelCase__				(       self  :	Any    )		->							str:
          for i in range(self.dst_h    ):
               for j in range(self.dst_w    ):
                    __UpperCAmelCase			:				Any													=    self.img[self.get_y(snake_case    )][self.get_x(snake_case    )]

     def 				lowerCamelCase__				(       self  :	int							,				snake_case  :	int    )		->							int:
          return int(self.ratio_x * x    )






     def 				lowerCamelCase__				(       self  :	Optional[Any]							,				snake_case  :	int    )		->							int:
          return int(self.ratio_y * y    )


if __name__ == "__main__":
      __UpperCAmelCase       ,					__UpperCAmelCase    :int				       =     8_0_0, 6_0_0
      __UpperCAmelCase    :Dict				       =     imread("image_data/lena.jpg", 1)
      __UpperCAmelCase    :int				       =     NearestNeighbour(im, dst_w, dst_h)
      n.process()

      imshow(
          f"""Image resized from: {im.shape[1]}x{im.shape[0]} to {dst_w}x{dst_h}""", n.output
      )
      waitKey(0)
      destroyAllWindows()