"""simple docstring"""



import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin



class      _A	(						_lowerCamelCase							, unittest.TestCase					):




    """simple docstring"""




    UpperCamelCase_	:					List[Any]							=					CanineTokenizer
    UpperCamelCase_	:					List[Any]							=					False
    def  lowercase					(		self							:     Optional[Any]    )    ->       str:
         super().setUp()
         __snake_case				=							CanineTokenizer()
         tokenizer.save_pretrained(self.tmpdirname    )
    @cached_property
    def  lowercase					(		self							:     Optional[Any]    )    ->       str:
         return CanineTokenizer.from_pretrained('''google/canine-s'''    )
    def  lowercase					(		self							:     Union[str, Any]	,      **A_							:     int    )    ->       CanineTokenizer:
         __snake_case				=							self.tokenizer_class.from_pretrained(self.tmpdirname	,      **A__    )
         __snake_case				=							1_024
         return tokenizer
    @require_torch
    def  lowercase					(		self							:     Optional[int]    )    ->       Union[str, Any]:
         __snake_case				=							self.canine_tokenizer
         __snake_case				=							['''Life is like a box of chocolates.''', '''You never know what you\'re gonna get.''']
         # fmt: off
         __snake_case				=							[57_344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 57_345, 0, 0, 0, 0]
         # fmt: on
         __snake_case				=							tokenizer(A__	,      padding=A__	,      return_tensors='''pt'''    )
         self.assertIsInstance(A__	,      A__    )

         __snake_case				=							list(batch.input_ids.numpy()[0]    )

         self.assertListEqual(A__	,      A__    )

         self.assertEqual((2, 39)	,      batch.input_ids.shape    )
         self.assertEqual((2, 39)	,      batch.attention_mask.shape    )
    @require_torch
    def  lowercase					(		self							:     Dict    )    ->       List[str]:
         __snake_case				=							self.canine_tokenizer
         __snake_case				=							['''Once there was a man.''', '''He wrote a test in HuggingFace Tranformers.''']
         __snake_case				=							tokenizer(A__	,      padding=A__	,      return_tensors='''pt'''    )
         # check if input_ids, attention_mask and token_type_ids are returned
         self.assertIn('''input_ids'''	,      A__    )
         self.assertIn('''attention_mask'''	,      A__    )
         self.assertIn('''token_type_ids'''	,      A__    )
    @require_torch
    def  lowercase					(		self							:     int    )    ->       Union[str, Any]:
         __snake_case				=							self.canine_tokenizer
         __snake_case				=							[
             '''What\'s the weater?''',
             '''It\'s about 25 degrees.''',
         ]
         __snake_case				=							tokenizer(
             text_target=A__	,      max_length=32	,      padding='''max_length'''	,      truncation=A__	,      return_tensors='''pt'''    )
         self.assertEqual(32	,      targets['''input_ids'''].shape[1]    )
    def  lowercase					(		self							:     int    )    ->       Optional[Any]:
         # safety check on max_len default value so we are sure the test works
         __snake_case				=							self.get_tokenizers()
         for tokenizer in tokenizers:
              with self.subTest(f"{tokenizer.__class__.__name__}"    ):
                   self.assertNotEqual(tokenizer.model_max_length	,      42    )

        # Now let's start the test
         __snake_case				=							self.get_tokenizers()
         for tokenizer in tokenizers:
              with self.subTest(f"{tokenizer.__class__.__name__}"    ):
                   # Isolate this from the other tests because we save additional tokens/etc
                   __snake_case				=							tempfile.mkdtemp()

                   __snake_case				=							''' He is very happy, UNwant\u00E9d,running'''
                   __snake_case				=							tokenizer.encode(A__	,      add_special_tokens=A__    )
                   tokenizer.save_pretrained(A__    )

                   __snake_case				=							tokenizer.__class__.from_pretrained(A__    )
                   __snake_case				=							after_tokenizer.encode(A__	,      add_special_tokens=A__    )
                   self.assertListEqual(A__	,      A__    )

                   shutil.rmtree(A__    )

         __snake_case				=							self.get_tokenizers(model_max_length=42    )
         for tokenizer in tokenizers:
              with self.subTest(f"{tokenizer.__class__.__name__}"    ):
                   # Isolate this from the other tests because we save additional tokens/etc
                   __snake_case				=							tempfile.mkdtemp()

                   __snake_case				=							''' He is very happy, UNwant\u00E9d,running'''

                   __snake_case				=							tokenizer.additional_special_tokens

                   # We can add a new special token for Canine as follows:
                   __snake_case				=							chr(0xe_007    )
                   additional_special_tokens.append(A__    )
                   tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}    )
                   __snake_case				=							tokenizer.encode(A__	,      add_special_tokens=A__    )
                   tokenizer.save_pretrained(A__    )

                   __snake_case				=							tokenizer.__class__.from_pretrained(A__    )
                   __snake_case				=							after_tokenizer.encode(A__	,      add_special_tokens=A__    )
                   self.assertListEqual(A__	,      A__    )
                   self.assertIn(A__	,      after_tokenizer.additional_special_tokens    )
                   self.assertEqual(after_tokenizer.model_max_length	,      42    )

                   __snake_case				=							tokenizer.__class__.from_pretrained(A__	,      model_max_length=43    )
                   self.assertEqual(tokenizer.model_max_length	,      43    )

                   shutil.rmtree(A__    )
    def  lowercase					(		self							:     Tuple    )    ->       Optional[Any]:
         __snake_case				=							self.get_tokenizers(do_lower_case=A__    )
         for tokenizer in tokenizers:
              with self.subTest(f"{tokenizer.__class__.__name__}"    ):
                   __snake_case		,	__snake_case				=							self.get_clean_sequence(A__    )

                   # a special token for Canine can be defined as follows:
                   __snake_case				=							0xe_005
                   __snake_case				=							chr(A__    )

                   tokenizer.add_special_tokens({'''cls_token''': special_token}    )
                   __snake_case				=							tokenizer.encode(A__	,      add_special_tokens=A__    )
                   self.assertEqual(len(A__    )	,      1    )

                   __snake_case				=							tokenizer.decode(ids + encoded_special_token	,      clean_up_tokenization_spaces=A__    )
                   __snake_case				=							tokenizer.encode(A__	,      add_special_tokens=A__    )

                   __snake_case				=							tokenizer.encode(A__	,      add_special_tokens=A__    )
                   __snake_case				=							tokenizer.encode(A__	,      add_special_tokens=A__    )
                   self.assertEqual(A__	,      input_encoded + special_token_id    )

                   __snake_case				=							tokenizer.decode(A__	,      skip_special_tokens=A__    )
                   self.assertTrue(special_token not in decoded    )
    def  lowercase					(		self							:     Optional[int]    )    ->       Union[str, Any]:
         __snake_case				=							self.get_tokenizers(do_lower_case=A__    )
         for tokenizer in tokenizers:
              with self.subTest(f"{tokenizer.__class__.__name__}"    ):
                   __snake_case				=							chr(0xe_005    )
                   __snake_case				=							chr(0xe_006    )

                   # `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
                   tokenizer.add_tokens([SPECIAL_TOKEN_1]	,      special_tokens=A__    )
                   # `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
                   # which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
                   tokenizer.add_special_tokens({'''additional_special_tokens''': [SPECIAL_TOKEN_2]}    )

                   __snake_case				=							tokenizer.tokenize(A__    )
                   __snake_case				=							tokenizer.tokenize(A__    )

                   self.assertEqual(len(A__    )	,      1    )
                   self.assertEqual(len(A__    )	,      1    )
                   self.assertEqual(token_a[0]	,      A__    )
                   self.assertEqual(token_a[0]	,      A__    )
    @require_tokenizers
    def  lowercase					(		self							:     Union[str, Any]    )    ->       int:
         __snake_case				=							self.get_tokenizers(do_lower_case=A__    )
         for tokenizer in tokenizers:
              with self.subTest(f"{tokenizer.__class__.__name__}"    ):
                   # a special token for Canine can be defined as follows:
                   __snake_case				=							0xe_006
                   __snake_case				=							chr(A__    )

                   __snake_case				=							AddedToken(A__	,      lstrip=A__    )
                   tokenizer.add_special_tokens({'''additional_special_tokens''': [new_token]}    )

                   with tempfile.TemporaryDirectory() as tmp_dir_name:
                        tokenizer.save_pretrained(A__    )
                        tokenizer.from_pretrained(A__    )
    def  lowercase					(		self							:     Tuple    )    ->       List[Any]:
         __snake_case				=							[]
         if self.test_slow_tokenizer:
              tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())    )

         if self.test_rust_tokenizer:
              tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())    )

         for tokenizer_class, tokenizer_utils in tokenizer_list:
              with tempfile.TemporaryDirectory() as tmp_dir:
                   tokenizer_utils.save_pretrained(A__    )

                   with open(os.path.join(A__	,      '''special_tokens_map.json'''    )	,      encoding='''utf-8'''    ) as json_file:
                        __snake_case				=							json.load(A__    )

                   with open(os.path.join(A__	,      '''tokenizer_config.json'''    )	,      encoding='''utf-8'''    ) as json_file:
                        __snake_case				=							json.load(A__    )

                   # a special token for Canine can be defined as follows:
                   __snake_case				=							0xe_006
                   __snake_case				=							chr(A__    )

                   __snake_case				=							[new_token_a]
                   __snake_case				=							[new_token_a]

                   with open(os.path.join(A__	,      '''special_tokens_map.json'''    )	,      '''w'''	,      encoding='''utf-8'''    ) as outfile:
                        json.dump(A__	,      A__    )
                   with open(os.path.join(A__	,      '''tokenizer_config.json'''    )	,      '''w'''	,      encoding='''utf-8'''    ) as outfile:
                        json.dump(A__	,      A__    )

                   # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
                   # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
                   # "special_tokens_map.json" files
                   __snake_case				=							tokenizer_class.from_pretrained(A__	,      extra_ids=0    )
                   self.assertIn(A__	,      tokenizer_without_change_in_init.additional_special_tokens    )
                   # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
                   self.assertEqual(
                       [new_token_a]	,      tokenizer_without_change_in_init.convert_ids_to_tokens(
                           tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]    )    )	,      )

                   __snake_case				=							0xe_007
                   __snake_case				=							chr(A__    )
                   # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                   __snake_case				=							[AddedToken(A__	,      lstrip=A__    )]
                   __snake_case				=							tokenizer_class.from_pretrained(
                       A__	,      additional_special_tokens=A__	,      extra_ids=0    )

                   self.assertIn(A__	,      tokenizer.additional_special_tokens    )
                   # self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
                   self.assertEqual(
                       [new_token_a]	,      tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]    )    )    )
    @require_tokenizers
    def  lowercase					(		self							:     Union[str, Any]    )    ->       List[str]:
         __snake_case				=							self.get_tokenizers(do_lower_case=A__    )
         for tokenizer in tokenizers:
              with self.subTest(f"{tokenizer.__class__.__name__}"    ):
                   __snake_case				=							'''hello world'''
                   if self.space_between_special_tokens:
                        __snake_case				=							'''[CLS] hello world [SEP]'''
                   else:
                        __snake_case				=							input
                   __snake_case				=							tokenizer.encode(A__	,      add_special_tokens=A__    )
                   __snake_case				=							tokenizer.decode(A__	,      spaces_between_special_tokens=self.space_between_special_tokens    )
                   self.assertIn(A__	,      [output, output.lower()]    )
    def  lowercase					(		self							:     Dict    )    ->       Union[str, Any]:
         __snake_case				=							self.get_tokenizers()
         for tokenizer in tokenizers:
              with self.subTest(f"{tokenizer.__class__.__name__}"    ):
                   __snake_case				=							[
                       '''bos_token''',
                       '''eos_token''',
                       '''unk_token''',
                       '''sep_token''',
                       '''pad_token''',
                       '''cls_token''',
                       '''mask_token''',
                   ]

         __snake_case				=							'''a'''
         __snake_case				=							ord(A__    )

         for attr in attributes_list:
              setattr(A__	,      attr + '''_id'''	,      A__    )
              self.assertEqual(getattr(A__	,      A__    )	,      A__    )
              self.assertEqual(getattr(A__	,      attr + '''_id'''    )	,      A__    )

              setattr(A__	,      attr + '''_id'''	,      A__    )
              self.assertEqual(getattr(A__	,      A__    )	,      A__    )
              self.assertEqual(getattr(A__	,      attr + '''_id'''    )	,      A__    )

         setattr(A__	,      '''additional_special_tokens_ids'''	,      []    )
         self.assertListEqual(getattr(A__	,      '''additional_special_tokens'''    )	,      []    )
         self.assertListEqual(getattr(A__	,      '''additional_special_tokens_ids'''    )	,      []    )

         __snake_case				=							0xe_006
         __snake_case				=							chr(A__    )
         setattr(A__	,      '''additional_special_tokens_ids'''	,      [additional_special_token_id]    )
         self.assertListEqual(getattr(A__	,      '''additional_special_tokens'''    )	,      [additional_special_token]    )
         self.assertListEqual(getattr(A__	,      '''additional_special_tokens_ids'''    )	,      [additional_special_token_id]    )
    def  lowercase					(		self							:     List[Any]    )    ->       Union[str, Any]:
         pass
    def  lowercase					(		self							:     List[Any]    )    ->       List[str]:
         pass
    def  lowercase					(		self							:     Optional[Any]    )    ->       Optional[Any]:
         pass
    def  lowercase					(		self							:     Dict    )    ->       List[Any]:
         pass
    def  lowercase					(		self							:     Union[str, Any]    )    ->       Optional[int]:
         pass
    def  lowercase					(		self							:     Tuple    )    ->       List[Any]:
         pass
    def  lowercase					(		self							:     List[Any]    )    ->       int:
         pass







    def  lowercase					(		self							:     Optional[int]    )    ->       Optional[int]:
         pass
"""simple docstring"""



def    SCREAMING_SNAKE_CASE       (     snake_case):
     __snake_case				=							len(snake_case)
     for i in range(length - 1):
          __snake_case				=							i
          for k in range(i + 1,      snake_case):
               if collection[k] < collection[least]:
                    __snake_case				=							k
          if least != i:
               __snake_case		,	__snake_case				=							(collection[i], collection[least])
     return collection


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