






import json
import os
import unittest

from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin




class 							_lowerCAmelCase(			UpperCAmelCase_				,      unittest.TestCase   ):





       """simple docstring"""







       a							:						Optional[int]										=CTRLTokenizer
       a							:						Tuple										=False
       a							:						Any										=False





       def      _a       (   self				):
         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         UpperCamelCase_:   Any        =							['adapt', 're@@', 'a@@', 'apt', 'c@@', 't', '<unk>']
         UpperCamelCase_:   str        =							dict(zip(_lowerCamelCase    ,     range(len(_lowerCamelCase				)				)				)				)
         UpperCamelCase_:   Union[str, Any]        =							['#version: 0.2', 'a p', 'ap t</w>', 'r e', 'a d', 'ad apt</w>', '']
         UpperCamelCase_:   Any        =							{'unk_token': '<unk>'}

         UpperCamelCase_:   Tuple        =							os.path.join(self.tmpdirname    ,     VOCAB_FILES_NAMES['vocab_file']				)
         UpperCamelCase_:   Optional[int]        =							os.path.join(self.tmpdirname    ,     VOCAB_FILES_NAMES['merges_file']				)
         with open(self.vocab_file    ,     'w'    ,     encoding='utf-8'				) as fp:
           fp.write(json.dumps(_lowerCamelCase				) + '\n'				)
         with open(self.merges_file    ,     'w'    ,     encoding='utf-8'				) as fp:
           fp.write('\n'.join(_lowerCamelCase				)				)





       def      _a       (   self    ,     **_lowerCamelCase				):
         kwargs.update(self.special_tokens_map				)
         return CTRLTokenizer.from_pretrained(self.tmpdirname    ,     **_lowerCamelCase				)





       def      _a       (   self    ,     _lowerCamelCase				):
         UpperCamelCase_:   Dict        =							'adapt react readapt apt'
         UpperCamelCase_:   int        =							'adapt react readapt apt'
         return input_text, output_text





       def      _a       (   self				):
         UpperCamelCase_:   Any        =							CTRLTokenizer(self.vocab_file    ,     self.merges_file    ,     **self.special_tokens_map				)
         UpperCamelCase_:   Optional[Any]        =							'adapt react readapt apt'
         UpperCamelCase_:   Union[str, Any]        =							'adapt re@@ a@@ c@@ t re@@ adapt apt'.split()
         UpperCamelCase_:   Any        =							tokenizer.tokenize(_lowerCamelCase				)
         self.assertListEqual(_lowerCamelCase    ,     _lowerCamelCase				)

         UpperCamelCase_:   Any        =							tokens + [tokenizer.unk_token]

         UpperCamelCase_:   Any        =							[0, 1, 2, 4, 5, 1, 0, 3, 6]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase				)    ,     _lowerCamelCase				)




"""simple docstring"""






from math import sqrt




def 			snake_case		(		lowerCAmelCase_ = 1000000	)						->				int:
  _snake_case   	=      0
  _snake_case   	=      0
  _snake_case   	=      42

  while num_cuboids <= limit:
    max_cuboid_size += 1
    for sum_shortest_sides in range(2  ,						2 * max_cuboid_size + 1	):
      if sqrt(sum_shortest_sides**2 + max_cuboid_size**2	).is_integer():
        num_cuboids += (
            min(lowerCAmelCase_  ,						sum_shortest_sides // 2	)
            - max(1  ,						sum_shortest_sides - max_cuboid_size	)
            + 1
        )

  return max_cuboid_size


if __name__ == "__main__":
     print(F"{solution() = }")





