

import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard



class     lowercase_       (    unittest.TestCase	):



      def 		UpperCamelCase_						(     self :							int						)       ->	Any:
        _snake_case		=				{
            '''model_details''': {
                '''Organization''': '''testing''',
                '''Model date''': '''today''',
                '''Model version''': '''v2.1, Developed by Test Corp in 2019.''',
                '''Architecture''': '''Convolutional Neural Network.''',
            },
            '''metrics''': '''BLEU and ROUGE-1''',
            '''evaluation_data''': {
                '''Datasets''': {'''BLEU''': '''My-great-dataset-v1''', '''ROUGE-1''': '''My-short-dataset-v2.1'''},
                '''Preprocessing''': '''See details on https://arxiv.org/pdf/1810.03993.pdf''',
            },
            '''training_data''': {
                '''Dataset''': '''English Wikipedia dump dated 2018-12-01''',
                '''Preprocessing''': (
                    '''Using SentencePiece vocabulary of size 52k tokens. See details on'''
                    ''' https://arxiv.org/pdf/1810.03993.pdf'''
                ),
            },
            '''quantitative_analyses''': {'''BLEU''': 55.1, '''ROUGE-1''': 76},
        }



      def 		UpperCamelCase_						(     self :							int						)       ->	Union[str, Any]:
        _snake_case		=				ModelCard.from_dict(self.inputs_dict						)
        self.assertTrue(hasattr(A__     ,   '''model_details'''						)						)
        self.assertTrue(hasattr(A__     ,   '''intended_use'''						)						)
        self.assertTrue(hasattr(A__     ,   '''factors'''						)						)
        self.assertTrue(hasattr(A__     ,   '''metrics'''						)						)
        self.assertTrue(hasattr(A__     ,   '''evaluation_data'''						)						)
        self.assertTrue(hasattr(A__     ,   '''training_data'''						)						)
        self.assertTrue(hasattr(A__     ,   '''quantitative_analyses'''						)						)
        self.assertTrue(hasattr(A__     ,   '''ethical_considerations'''						)						)
        self.assertTrue(hasattr(A__     ,   '''caveats_and_recommendations'''						)						)



      def 		UpperCamelCase_						(     self :							Union[str, Any]						)       ->	Union[str, Any]:
        _snake_case		=				ModelCard.from_dict(self.inputs_dict						)
        _snake_case		=				json.loads(modelcard.to_json_string()						)
        for key, value in self.inputs_dict.items():
          self.assertEqual(obj[key]     ,   A__						)



      def 		UpperCamelCase_						(     self :							int						)       ->	Tuple:
        _snake_case		=				ModelCard.from_dict(self.inputs_dict						)

        with tempfile.TemporaryDirectory() as tmpdirname:
          _snake_case		=				os.path.join(A__     ,   '''modelcard.json'''						)
          model_card_first.to_json_file(A__						)
          _snake_case		=				ModelCard.from_json_file(A__						)

        self.assertEqual(model_card_second.to_dict()     ,   model_card_first.to_dict()						)







      def 		UpperCamelCase_						(     self :							int						)       ->	int:
        _snake_case		=				ModelCard.from_dict(self.inputs_dict						)

        with tempfile.TemporaryDirectory() as tmpdirname:
          model_card_first.save_pretrained(A__						)
          _snake_case		=				ModelCard.from_pretrained(A__						)

        self.assertEqual(model_card_second.to_dict()     ,   model_card_first.to_dict()						)




def  snake_case_(_UpperCamelCase	)				->      int:



  """simple docstring"""






  _snake_case		=				len(_UpperCamelCase	)
  _snake_case		=				[0] * length
  _snake_case		=				[[False for i in range(_UpperCamelCase	)] for j in range(_UpperCamelCase	)]
  for i, c in enumerate(_UpperCamelCase	):
    _snake_case		=				i
    for j in range(i + 1	):
      if c == string[j] and (i - j < 2 or is_palindromic[j + 1][i - 1]):
        _snake_case		=				True
        _snake_case		=				min(_UpperCamelCase					,			0 if j == 0 else (cut[j - 1] + 1)	)
    _snake_case		=				mincut
  return cut[length - 1]


if __name__ == "__main__":
 __A     						=      input('''Enter the string: ''').strip()
 __A     						=      find_minimum_partitions(s)
 print(f'''Minimum number of partitions required for the \'{s}\' is {ans}''')

