





"""simple docstring"""



import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 		__snake_case (		SCREAMING_SNAKE_CASE__							,							unittest.TestCase					):





 """simple docstring"""


 _lowerCamelCase				=					RobertaTokenizer
 _lowerCamelCase				=					RobertaTokenizerFast
 _lowerCamelCase				=					True
 _lowerCamelCase				=					{"""cls_token""": """<s>"""}

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     super().setUp()

     # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
     __A   :						List[str]									=					[
         '''l''',
         '''o''',
         '''w''',
         '''e''',
         '''r''',
         '''s''',
         '''t''',
         '''i''',
         '''d''',
         '''n''',
         '''\u0120''',
         '''\u0120l''',
         '''\u0120n''',
         '''\u0120lo''',
         '''\u0120low''',
         '''er''',
         '''\u0120lowest''',
         '''\u0120newer''',
         '''\u0120wider''',
         '''<unk>''',
     ]
     __A   :						int									=					dict(zip(__lowerCamelCase ,						range(len(__lowerCamelCase  )  )  )  )
     __A   :						str									=					['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
     __A   :						Dict									=					{'''unk_token''': '''<unk>'''}

     __A   :						List[str]									=					os.path.join(self.tmpdirname ,						VOCAB_FILES_NAMES['''vocab_file''']  )
     __A   :						Union[str, Any]									=					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  UpperCamelCase__(   self ,						**__lowerCamelCase  ):



     '''simple docstring'''




     kwargs.update(self.special_tokens_map  )
     return self.tokenizer_class.from_pretrained(self.tmpdirname ,						**__lowerCamelCase  )

 def  UpperCamelCase__(   self ,						**__lowerCamelCase  ):



     '''simple docstring'''




     kwargs.update(self.special_tokens_map  )
     return RobertaTokenizerFast.from_pretrained(self.tmpdirname ,						**__lowerCamelCase  )

 def  UpperCamelCase__(   self ,						__lowerCamelCase  ):



     '''simple docstring'''




     __A   :						str									=					'''lower newer'''
     __A   :						int									=					'''lower newer'''
     return input_text, output_text

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Tuple									=					self.tokenizer_class(self.vocab_file ,						self.merges_file ,						**self.special_tokens_map  )
     __A   :						List[Any]									=					'''lower newer'''
     __A   :						int									=					['''l''', '''o''', '''w''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
     __A   :						List[Any]									=					tokenizer.tokenize(__lowerCamelCase  )  # , add_prefix_space=True)
     self.assertListEqual(__lowerCamelCase ,						__lowerCamelCase  )

     __A   :						str									=					tokens + [tokenizer.unk_token]
     __A   :						Any									=					[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase  ) ,						__lowerCamelCase  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Union[str, Any]									=					self.get_tokenizer()

     self.assertListEqual(tokenizer.encode('''Hello world!''' ,						add_special_tokens=__lowerCamelCase  ) ,						[0, 3_1414, 232, 328, 2]  )
     self.assertListEqual(
         tokenizer.encode('''Hello world! cécé herlolip 418''' ,						add_special_tokens=__lowerCamelCase  ) ,						[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2] ,						)

 @slow
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Dict									=					self.tokenizer_class.from_pretrained('''roberta-base'''  )

     __A   :						Union[str, Any]									=					tokenizer.encode('''sequence builders''' ,						add_special_tokens=__lowerCamelCase  )
     __A   :						Union[str, Any]									=					tokenizer.encode('''multi-sequence build''' ,						add_special_tokens=__lowerCamelCase  )

     __A   :						List[Any]									=					tokenizer.encode(
         '''sequence builders''' ,						add_special_tokens=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase  )
     __A   :						Tuple									=					tokenizer.encode(
         '''sequence builders''' ,						'''multi-sequence build''' ,						add_special_tokens=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase  )

     __A   :						str									=					tokenizer.build_inputs_with_special_tokens(__lowerCamelCase  )
     __A   :						List[Any]									=					tokenizer.build_inputs_with_special_tokens(__lowerCamelCase ,						__lowerCamelCase  )

     assert encoded_sentence == encoded_text_from_decode
     assert encoded_pair == encoded_pair_from_decode

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Tuple									=					self.get_tokenizer()

     __A   :						Union[str, Any]									=					'''Encode this sequence.'''
     __A   :						Optional[Any]									=					tokenizer.byte_encoder[''' '''.encode('''utf-8'''  )[0]]

     # Testing encoder arguments
     __A   :						List[Any]									=					tokenizer.encode(__lowerCamelCase ,						add_special_tokens=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase  )
     __A   :						int									=					tokenizer.convert_ids_to_tokens(encoded[0]  )[0]
     self.assertNotEqual(__lowerCamelCase ,						__lowerCamelCase  )

     __A   :						Tuple									=					tokenizer.encode(__lowerCamelCase ,						add_special_tokens=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase  )
     __A   :						str									=					tokenizer.convert_ids_to_tokens(encoded[0]  )[0]
     self.assertEqual(__lowerCamelCase ,						__lowerCamelCase  )

     tokenizer.add_special_tokens({'''bos_token''': '''<s>'''}  )
     __A   :						int									=					tokenizer.encode(__lowerCamelCase ,						add_special_tokens=__lowerCamelCase  )
     __A   :						List[Any]									=					tokenizer.convert_ids_to_tokens(encoded[1]  )[0]
     self.assertNotEqual(__lowerCamelCase ,						__lowerCamelCase  )

     # Testing spaces after special tokens
     __A   :						Any									=					'''<mask>'''
     tokenizer.add_special_tokens(
         {'''mask_token''': AddedToken(__lowerCamelCase ,						lstrip=__lowerCamelCase ,						rstrip=__lowerCamelCase  )}  )  # mask token has a left space
     __A   :						Union[str, Any]									=					tokenizer.convert_tokens_to_ids(__lowerCamelCase  )

     __A   :						Tuple									=					'''Encode <mask> sequence'''
     __A   :						str									=					'''Encode <mask>sequence'''

     __A   :						Optional[Any]									=					tokenizer.encode(__lowerCamelCase  )
     __A   :						Dict									=					encoded.index(__lowerCamelCase  )
     __A   :						Any									=					tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]  )[0]
     self.assertEqual(__lowerCamelCase ,						__lowerCamelCase  )

     __A   :						Dict									=					tokenizer.encode(__lowerCamelCase  )
     __A   :						List[Any]									=					encoded.index(__lowerCamelCase  )
     __A   :						Union[str, Any]									=					tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]  )[0]
     self.assertNotEqual(__lowerCamelCase ,						__lowerCamelCase  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     pass

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""  ):
             __A   :						str									=					self.rust_tokenizer_class.from_pretrained(__lowerCamelCase ,						**__lowerCamelCase  )
             __A   :						List[Any]									=					self.tokenizer_class.from_pretrained(__lowerCamelCase ,						**__lowerCamelCase  )
             __A   :						List[Any]									=					'''A, <mask> AllenNLP sentence.'''
             __A   :						Union[str, Any]									=					tokenizer_r.encode_plus(__lowerCamelCase ,						add_special_tokens=__lowerCamelCase ,						return_token_type_ids=__lowerCamelCase  )
             __A   :						Any									=					tokenizer_p.encode_plus(__lowerCamelCase ,						add_special_tokens=__lowerCamelCase ,						return_token_type_ids=__lowerCamelCase  )

             # token_type_ids should put 0 everywhere
             self.assertEqual(sum(tokens_r['''token_type_ids''']  ) ,						sum(tokens_p['''token_type_ids''']  )  )

             # attention_mask should put 1 everywhere, so sum over length should be 1
             self.assertEqual(
                 sum(tokens_r['''attention_mask''']  ) / len(tokens_r['''attention_mask''']  ) ,						sum(tokens_p['''attention_mask''']  ) / len(tokens_p['''attention_mask''']  ) ,						)

             __A   :						Tuple									=					tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']  )
             __A   :						Dict									=					tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']  )

             # Rust correctly handles the space before the mask while python doesnt
             self.assertSequenceEqual(tokens_p['''input_ids'''] ,						[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]  )
             self.assertSequenceEqual(tokens_r['''input_ids'''] ,						[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]  )

             self.assertSequenceEqual(
                 __lowerCamelCase ,						['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']  )
             self.assertSequenceEqual(
                 __lowerCamelCase ,						['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     for trim_offsets, add_prefix_space in itertools.product([True, False] ,						repeat=2  ):
         __A   :						str									=					self.rust_tokenizer_class.from_pretrained(
             self.tmpdirname ,						use_fast=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase ,						trim_offsets=__lowerCamelCase  )

         __A   :						List[Any]									=					json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()  )
         __A   :						List[Any]									=					json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()  )

         self.assertEqual(pre_tokenizer_state['''add_prefix_space'''] ,						__lowerCamelCase  )

         self.assertEqual(post_processor_state['''add_prefix_space'''] ,						__lowerCamelCase  )
         self.assertEqual(post_processor_state['''trim_offsets'''] ,						__lowerCamelCase  )







 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""  ):
             __A   :						Optional[int]									=					'''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
             __A   :						str									=					F"""{text_of_1_token} {text_of_1_token}"""

             __A   :						int									=					self.rust_tokenizer_class.from_pretrained(
                 __lowerCamelCase ,						use_fast=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase ,						trim_offsets=__lowerCamelCase  )
             __A   :						List[Any]									=					tokenizer_r(__lowerCamelCase ,						return_offsets_mapping=__lowerCamelCase ,						add_special_tokens=__lowerCamelCase  )
             self.assertEqual(encoding.offset_mapping[0] ,						(0, len(__lowerCamelCase  ))  )
             self.assertEqual(
                 encoding.offset_mapping[1] ,						(len(__lowerCamelCase  ) + 1, len(__lowerCamelCase  ) + 1 + len(__lowerCamelCase  )) ,						)

             __A   :						List[str]									=					self.rust_tokenizer_class.from_pretrained(
                 __lowerCamelCase ,						use_fast=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase ,						trim_offsets=__lowerCamelCase  )
             __A   :						Tuple									=					tokenizer_r(__lowerCamelCase ,						return_offsets_mapping=__lowerCamelCase ,						add_special_tokens=__lowerCamelCase  )
             self.assertEqual(encoding.offset_mapping[0] ,						(0, len(__lowerCamelCase  ))  )
             self.assertEqual(
                 encoding.offset_mapping[1] ,						(len(__lowerCamelCase  ) + 1, len(__lowerCamelCase  ) + 1 + len(__lowerCamelCase  )) ,						)

             __A   :						int									=					self.rust_tokenizer_class.from_pretrained(
                 __lowerCamelCase ,						use_fast=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase ,						trim_offsets=__lowerCamelCase  )
             __A   :						List[Any]									=					tokenizer_r(__lowerCamelCase ,						return_offsets_mapping=__lowerCamelCase ,						add_special_tokens=__lowerCamelCase  )
             self.assertEqual(encoding.offset_mapping[0] ,						(0, len(__lowerCamelCase  ))  )
             self.assertEqual(
                 encoding.offset_mapping[1] ,						(len(__lowerCamelCase  ), len(__lowerCamelCase  ) + 1 + len(__lowerCamelCase  )) ,						)

             __A   :						Optional[Any]									=					self.rust_tokenizer_class.from_pretrained(
                 __lowerCamelCase ,						use_fast=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase ,						trim_offsets=__lowerCamelCase  )
             __A   :						List[Any]									=					tokenizer_r(__lowerCamelCase ,						return_offsets_mapping=__lowerCamelCase ,						add_special_tokens=__lowerCamelCase  )
             self.assertEqual(encoding.offset_mapping[0] ,						(0, len(__lowerCamelCase  ))  )
             self.assertEqual(
                 encoding.offset_mapping[1] ,						(len(__lowerCamelCase  ), len(__lowerCamelCase  ) + 1 + len(__lowerCamelCase  )) ,						)

             __A   :						List[Any]									=					F""" {text}"""

             # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
             #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
             # )
             # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
             # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
             # self.assertEqual(
             #     encoding.offset_mapping[1],
             #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
             # )

             __A   :						Optional[int]									=					self.rust_tokenizer_class.from_pretrained(
                 __lowerCamelCase ,						use_fast=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase ,						trim_offsets=__lowerCamelCase  )
             __A   :						Optional[int]									=					tokenizer_r(__lowerCamelCase ,						return_offsets_mapping=__lowerCamelCase ,						add_special_tokens=__lowerCamelCase  )
             self.assertEqual(encoding.offset_mapping[0] ,						(1, 1 + len(__lowerCamelCase  ))  )
             self.assertEqual(
                 encoding.offset_mapping[1] ,						(1 + len(__lowerCamelCase  ) + 1, 1 + len(__lowerCamelCase  ) + 1 + len(__lowerCamelCase  )) ,						)

             __A   :						List[str]									=					self.rust_tokenizer_class.from_pretrained(
                 __lowerCamelCase ,						use_fast=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase ,						trim_offsets=__lowerCamelCase  )
             __A   :						Optional[Any]									=					tokenizer_r(__lowerCamelCase ,						return_offsets_mapping=__lowerCamelCase ,						add_special_tokens=__lowerCamelCase  )
             self.assertEqual(encoding.offset_mapping[0] ,						(0, 1 + len(__lowerCamelCase  ))  )
             self.assertEqual(
                 encoding.offset_mapping[1] ,						(1 + len(__lowerCamelCase  ), 1 + len(__lowerCamelCase  ) + 1 + len(__lowerCamelCase  )) ,						)

             __A   :						Optional[Any]									=					self.rust_tokenizer_class.from_pretrained(
                 __lowerCamelCase ,						use_fast=__lowerCamelCase ,						add_prefix_space=__lowerCamelCase ,						trim_offsets=__lowerCamelCase  )
             __A   :						Optional[Any]									=					tokenizer_r(__lowerCamelCase ,						return_offsets_mapping=__lowerCamelCase ,						add_special_tokens=__lowerCamelCase  )
             self.assertEqual(encoding.offset_mapping[0] ,						(0, 1 + len(__lowerCamelCase  ))  )
             self.assertEqual(
                 encoding.offset_mapping[1] ,						(1 + len(__lowerCamelCase  ), 1 + len(__lowerCamelCase  ) + 1 + len(__lowerCamelCase  )) ,						)











"""simple docstring"""



def 		__lowercase					(       snake_case_  :  int						)       ->Optional[Any]:



    '''simple docstring'''







    stooge(snake_case_    ,0    ,len(snake_case_						) - 1						)
    return arr







def 		__lowercase					(       snake_case_  :  Optional[Any]    ,snake_case_  :  Union[str, Any]    ,snake_case_  :  Any						)       ->Tuple:



    '''simple docstring'''







    if i >= h:
        return

    # If first element is smaller than the last then swap them
    if arr[i] > arr[h]:
        __A			,	__A   :						Optional[int]									=					arr[h], arr[i]

    # If there are more than 2 elements in the array
    if h - i + 1 > 2:
        __A   :						Any									=					(int)((h - i + 1) / 3						)

        # Recursively sort first 2/3 elements
        stooge(snake_case_    ,snake_case_    ,(h - t)						)

        # Recursively sort last 2/3 elements
        stooge(snake_case_    ,i + t    ,(snake_case_)						)

        # Recursively sort first 2/3 elements
        stooge(snake_case_    ,snake_case_    ,(h - t)						)


if __name__ == "__main__":
       a_			=      input("""Enter numbers separated by a comma:\n""").strip()
       a_			=      [int(item) for item in user_input.split(""",""")]
       print(stooge_sort(unsorted))




