





import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
       from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


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

_lowerCamelCase			       =      {'target_lang': 'fi', 'source_lang': 'en'}
_lowerCamelCase			       =      '>>zh<<'
_lowerCamelCase			       =      'Helsinki-NLP/'

if is_torch_available():
       _lowerCamelCase			       =      'pt'
elif is_tf_available():
       _lowerCamelCase			       =      'tf'
else:
       _lowerCamelCase			       =      'jax'







@require_sentencepiece
class 			__A       (      lowerCamelCase__ ,unittest.TestCase  ):




      """simple docstring"""







      UpperCAmelCase__						=      MarianTokenizer
      UpperCAmelCase__						=      False
      UpperCAmelCase__						=      True


      def 				__snake_case			(		self):



             """simple docstring"""





             super().setUp()
             _lowerCamelCase							:     Optional[int]	=		['''</s>''', '''<unk>''', '''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''', '''\u0120''', '''<pad>''']
             _lowerCamelCase							:     Optional[Any]	=		dict(zip(a__      ,							range(len(a__))))
             _lowerCamelCase							:     Optional[Any]	=		Path(self.tmpdirname)
             save_json(a__      ,							save_dir / VOCAB_FILES_NAMES['''vocab'''])
             save_json(a__      ,							save_dir / VOCAB_FILES_NAMES['''tokenizer_config_file'''])
             if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
                    copyfile(a__      ,							save_dir / VOCAB_FILES_NAMES['''source_spm'''])
                    copyfile(a__      ,							save_dir / VOCAB_FILES_NAMES['''target_spm'''])

             _lowerCamelCase							:     Union[str, Any]	=		MarianTokenizer.from_pretrained(self.tmpdirname)
             tokenizer.save_pretrained(self.tmpdirname)


      def 				__snake_case			(		self      ,							**a__):



             """simple docstring"""





             return MarianTokenizer.from_pretrained(self.tmpdirname      ,							**a__)


      def 				__snake_case			(		self      ,							a__):



             """simple docstring"""





             return (
                 "This is a test",
                 "This is a test",
             )


      def 				__snake_case			(		self):



             """simple docstring"""





             _lowerCamelCase							:     Any	=		'''</s>'''
             _lowerCamelCase							:     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 				__snake_case			(		self):



             """simple docstring"""





             _lowerCamelCase							:     Optional[Any]	=		list(self.get_tokenizer().get_vocab().keys())

             self.assertEqual(vocab_keys[0]      ,							'''</s>''')
             self.assertEqual(vocab_keys[1]      ,							'''<unk>''')
             self.assertEqual(vocab_keys[-1]      ,							'''<pad>''')
             self.assertEqual(len(a__)      ,							9)


      def 				__snake_case			(		self):



             """simple docstring"""





             self.assertEqual(self.get_tokenizer().vocab_size      ,							9)


      def 				__snake_case			(		self):



             """simple docstring"""





             _lowerCamelCase							:     Union[str, Any]	=		MarianTokenizer.from_pretrained(F"""{ORG_NAME}opus-mt-en-de""")
             _lowerCamelCase							:     Optional[Any]	=		en_de_tokenizer(['''I am a small frog''']      ,							return_tensors=a__)
             self.assertIsInstance(a__      ,							a__)
             _lowerCamelCase							:     Optional[Any]	=		[38, 121, 14, 697, 3_8848, 0]
             self.assertListEqual(a__      ,							batch.input_ids[0])

             _lowerCamelCase							:     Union[str, Any]	=		tempfile.mkdtemp()
             en_de_tokenizer.save_pretrained(a__)
             _lowerCamelCase							:     int	=		[x.name for x in Path(a__).glob('''*''')]
             self.assertIn('''source.spm'''      ,							a__)
             MarianTokenizer.from_pretrained(a__)


      def 				__snake_case			(		self):



             """simple docstring"""





             _lowerCamelCase							:     Any	=		self.get_tokenizer()

             _lowerCamelCase							:     Any	=		tok(
                 ['''I am a small frog''' * 1000, '''I am a small frog''']      ,							padding=a__      ,							truncation=a__      ,							return_tensors=a__)
             self.assertIsInstance(a__      ,							a__)
             self.assertEqual(batch.input_ids.shape      ,							(2, 512))


      def 				__snake_case			(		self):



             """simple docstring"""





             _lowerCamelCase							:     Optional[Any]	=		self.get_tokenizer()
             _lowerCamelCase							:     Tuple	=		tok(['''I am a tiny frog''', '''I am a small frog''']      ,							padding=a__      ,							return_tensors=a__)
             self.assertIsInstance(a__      ,							a__)
             self.assertEqual(batch_smaller.input_ids.shape      ,							(2, 10))


      @slow
      def 				__snake_case			(		self):



             """simple docstring"""





             _lowerCamelCase							:     Optional[int]	=		{'''input_ids''': [[4_3495, 462, 20, 4_2164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 3_8999, 6, 8, 464, 132, 1703, 492, 13, 4669, 3_7867, 13, 7525, 27, 1593, 988, 13, 3_3972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 1_2338, 2, 1_3958, 387, 2, 3629, 6953, 188, 2900, 2, 1_3958, 8011, 1_1501, 23, 8460, 4073, 3_4009, 20, 435, 1_1439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 3_7867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 2_6453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 1_0767, 6, 316, 304, 4239, 3, 0], [148, 1_5722, 19, 1839, 12, 1350, 13, 2_2327, 5082, 5418, 4_7567, 3_5938, 59, 318, 1_9552, 108, 2183, 54, 1_4976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 1_9088, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100], [36, 6395, 1_2570, 3_9147, 1_1597, 6, 266, 4, 4_5405, 7296, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100]], '''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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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='''Helsinki-NLP/opus-mt-en-de'''      ,							revision='''1a8c2263da11e68e50938f97e10cd57820bd504c'''      ,							decode_kwargs={'''use_source_tokenizer''': True}      ,							)



      def 				__snake_case			(		self):



             """simple docstring"""





             _lowerCamelCase							:     Optional[int]	=		MarianTokenizer.from_pretrained('''hf-internal-testing/test-marian-two-vocabs''')

             _lowerCamelCase							:     int	=		'''Tämä on testi'''
             _lowerCamelCase							:     Union[str, Any]	=		'''This is a test'''

             _lowerCamelCase							:     str	=		[76, 7, 2047, 2]
             _lowerCamelCase							:     Optional[int]	=		[69, 12, 11, 940, 2]

             _lowerCamelCase							:     str	=		tokenizer(a__).input_ids
             self.assertListEqual(a__      ,							a__)

             _lowerCamelCase							:     List[str]	=		tokenizer(text_target=a__).input_ids
             self.assertListEqual(a__      ,							a__)

             _lowerCamelCase							:     str	=		tokenizer.decode(a__      ,							skip_special_tokens=a__)
             self.assertEqual(a__      ,							a__)








import math




def    __UpperCAmelCase(      lowercase_ ,    lowercase_      ):
       _lowerCamelCase							:     List[str]	=		len(lowercase_      )
       _lowerCamelCase							:     Optional[int]	=		int(math.floor(math.sqrt(lowercase_      )      )      )
       _lowerCamelCase							:     Tuple	=		0
       while arr[min(lowercase_ ,    lowercase_      ) - 1] < x:
              _lowerCamelCase							:     Optional[Any]	=		step
              step += int(math.floor(math.sqrt(lowercase_      )      )      )
              if prev >= n:
                     return -1

       while arr[prev] < x:
              _lowerCamelCase							:     int	=		prev + 1
              if prev == min(lowercase_ ,    lowercase_      ):
                     return -1
       if arr[prev] == x:
              return prev
       return -1


if __name__ == "__main__":
       _lowerCamelCase			       =      input('Enter numbers separated by a comma:\n').strip()
       _lowerCamelCase			       =      [int(item) for item in user_input.split(',')]
       _lowerCamelCase			       =      int(input('Enter the number to be searched:\n'))
       _lowerCamelCase			       =      jump_search(arr, x)
       if res == -1:
              print('Number not found!')
       else:
              print(F'''Number {x} is at index {res}''')

