"""simple docstring"""
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError

from transformers import (
    AlbertTokenizer,
    AutoTokenizer,
    BertTokenizer,
    BertTokenizerFast,
    GPTaTokenizerFast,
    is_tokenizers_available,
)
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_tokenizers
from transformers.tokenization_utils import Trie


sys.path.append(str(Path(__file__).parent.parent / 'utils'))

from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
 from test_module.custom_tokenization_fast import CustomTokenizerFast




class        __snake_case	(					unittest.TestCase    ):



      def   lowerCamelCase_       (						self)     ->      str:





        '''simple docstring'''





        a__:					Dict      							=     mock.Mock()
        a__:					Union[str, Any]      							=     5_00
        a__:					Optional[Any]      							=     {}
        a__:					str      							=     HTTPError
        a__:					str      							=     {}

        # Download this model to make sure it's in the cache.
        a__:					List[Any]      							=     BertTokenizer.from_pretrained('hf-internal-testing/tiny-random-bert')

        # Under the mock environment we get a 500 error when trying to reach the tokenizer.
        with mock.patch('requests.Session.request'   ,      return_value=_SCREAMING_SNAKE_CASE) as mock_head:
          a__:					Dict      							=     BertTokenizer.from_pretrained('hf-internal-testing/tiny-random-bert')
          # This check we did call the fake head request
          mock_head.assert_called()



      @require_tokenizers
      def   lowerCamelCase_       (						self)     ->      List[Any]:





        '''simple docstring'''





        a__:					Any      							=     mock.Mock()
        a__:					Dict      							=     5_00
        a__:					Dict      							=     {}
        a__:					List[Any]      							=     HTTPError
        a__:					str      							=     {}

        # Download this model to make sure it's in the cache.
        a__:					Optional[int]      							=     GPTaTokenizerFast.from_pretrained('gpt2')

        # Under the mock environment we get a 500 error when trying to reach the tokenizer.
        with mock.patch('requests.Session.request'   ,      return_value=_SCREAMING_SNAKE_CASE) as mock_head:
          a__:					Any      							=     GPTaTokenizerFast.from_pretrained('gpt2')
          # This check we did call the fake head request
          mock_head.assert_called()



      def   lowerCamelCase_       (						self)     ->      List[str]:





        '''simple docstring'''





        try:
          a__:					List[Any]      							=     tempfile.mktemp()
          with open(_SCREAMING_SNAKE_CASE   ,      'wb') as f:
            http_get('https://huggingface.co/albert-base-v1/resolve/main/spiece.model'   ,      _SCREAMING_SNAKE_CASE)

          a__:					List[str]      							=     AlbertTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE)
        finally:
          os.remove(_SCREAMING_SNAKE_CASE)

        # Supporting this legacy load introduced a weird bug where the tokenizer would load local files if they are in
        # the current folder and have the right name.
        if os.path.isfile('tokenizer.json'):
          # We skip the test if the user has a `tokenizer.json` in this folder to avoid deleting it.
          return
        try:
          with open('tokenizer.json'   ,      'wb') as f:
            http_get('https://huggingface.co/hf-internal-testing/tiny-random-bert/blob/main/tokenizer.json'   ,      _SCREAMING_SNAKE_CASE)
          a__:					Optional[Any]      							=     AutoTokenizer.from_pretrained('hf-internal-testing/tiny-random-gpt2')
          # The tiny random BERT has a vocab size of 1024, tiny gpt2 as a vocab size of 1000
          self.assertEqual(tokenizer.vocab_size   ,      10_00)
          # Tokenizer should depend on the remote checkpoint, not the local tokenizer.json file.

        finally:
          os.remove('tokenizer.json')



      def   lowerCamelCase_       (						self)     ->      Tuple:





        '''simple docstring'''





        a__:					Any      							=     AlbertTokenizer.from_pretrained('https://huggingface.co/albert-base-v1/resolve/main/spiece.model')







@is_staging_test
class        __snake_case	(					unittest.TestCase    ):
      a__				=		["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "bla", "blou"]



      @classmethod
      def   lowerCamelCase_       (						cls)     ->      Dict:





        '''simple docstring'''





        a__:					Optional[int]      							=     TOKEN
        HfFolder.save_token(_SCREAMING_SNAKE_CASE)



      @classmethod
      def   lowerCamelCase_       (						cls)     ->      Tuple:





        '''simple docstring'''





        try:
          delete_repo(token=cls._token   ,      repo_id='test-tokenizer')
        except HTTPError:
          pass

        try:
          delete_repo(token=cls._token   ,      repo_id='valid_org/test-tokenizer-org')
        except HTTPError:
          pass

        try:
          delete_repo(token=cls._token   ,      repo_id='test-dynamic-tokenizer')
        except HTTPError:
          pass



      def   lowerCamelCase_       (						self)     ->      List[str]:





        '''simple docstring'''





        with tempfile.TemporaryDirectory() as tmp_dir:
          a__:					List[str]      							=     os.path.join(_SCREAMING_SNAKE_CASE   ,      'vocab.txt')
          with open(_SCREAMING_SNAKE_CASE   ,      'w'   ,      encoding='utf-8') as vocab_writer:
            vocab_writer.write(''.join([x + '\n' for x in self.vocab_tokens]))
          a__:					Union[str, Any]      							=     BertTokenizer(_SCREAMING_SNAKE_CASE)

        tokenizer.push_to_hub('test-tokenizer'   ,      use_auth_token=self._token)
        a__:					Dict      							=     BertTokenizer.from_pretrained(f'{USER}/test-tokenizer')
        self.assertDictEqual(new_tokenizer.vocab   ,      tokenizer.vocab)

        # Reset repo
        delete_repo(token=self._token   ,      repo_id='test-tokenizer')

        # Push to hub via save_pretrained
        with tempfile.TemporaryDirectory() as tmp_dir:
          tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE   ,      repo_id='test-tokenizer'   ,      push_to_hub=_SCREAMING_SNAKE_CASE   ,      use_auth_token=self._token)

        a__:					List[str]      							=     BertTokenizer.from_pretrained(f'{USER}/test-tokenizer')
        self.assertDictEqual(new_tokenizer.vocab   ,      tokenizer.vocab)



      def   lowerCamelCase_       (						self)     ->      List[str]:





        '''simple docstring'''





        with tempfile.TemporaryDirectory() as tmp_dir:
          a__:					str      							=     os.path.join(_SCREAMING_SNAKE_CASE   ,      'vocab.txt')
          with open(_SCREAMING_SNAKE_CASE   ,      'w'   ,      encoding='utf-8') as vocab_writer:
            vocab_writer.write(''.join([x + '\n' for x in self.vocab_tokens]))
          a__:					str      							=     BertTokenizer(_SCREAMING_SNAKE_CASE)

        tokenizer.push_to_hub('valid_org/test-tokenizer-org'   ,      use_auth_token=self._token)
        a__:					List[Any]      							=     BertTokenizer.from_pretrained('valid_org/test-tokenizer-org')
        self.assertDictEqual(new_tokenizer.vocab   ,      tokenizer.vocab)

        # Reset repo
        delete_repo(token=self._token   ,      repo_id='valid_org/test-tokenizer-org')

        # Push to hub via save_pretrained
        with tempfile.TemporaryDirectory() as tmp_dir:
          tokenizer.save_pretrained(
              _SCREAMING_SNAKE_CASE   ,      repo_id='valid_org/test-tokenizer-org'   ,      push_to_hub=_SCREAMING_SNAKE_CASE   ,      use_auth_token=self._token)

        a__:					List[Any]      							=     BertTokenizer.from_pretrained('valid_org/test-tokenizer-org')
        self.assertDictEqual(new_tokenizer.vocab   ,      tokenizer.vocab)



      @require_tokenizers
      def   lowerCamelCase_       (						self)     ->      List[Any]:





        '''simple docstring'''





        CustomTokenizer.register_for_auto_class()
        with tempfile.TemporaryDirectory() as tmp_dir:
          a__:					int      							=     os.path.join(_SCREAMING_SNAKE_CASE   ,      'vocab.txt')
          with open(_SCREAMING_SNAKE_CASE   ,      'w'   ,      encoding='utf-8') as vocab_writer:
            vocab_writer.write(''.join([x + '\n' for x in self.vocab_tokens]))
          a__:					Union[str, Any]      							=     CustomTokenizer(_SCREAMING_SNAKE_CASE)

        # No fast custom tokenizer
        tokenizer.push_to_hub('test-dynamic-tokenizer'   ,      use_auth_token=self._token)

        a__:					List[Any]      							=     AutoTokenizer.from_pretrained(f'{USER}/test-dynamic-tokenizer'   ,      trust_remote_code=_SCREAMING_SNAKE_CASE)
        # Can't make an isinstance check because the new_model.config is from the CustomTokenizer class of a dynamic module
        self.assertEqual(tokenizer.__class__.__name__   ,      'CustomTokenizer')

        # Fast and slow custom tokenizer
        CustomTokenizerFast.register_for_auto_class()
        with tempfile.TemporaryDirectory() as tmp_dir:
          a__:					Dict      							=     os.path.join(_SCREAMING_SNAKE_CASE   ,      'vocab.txt')
          with open(_SCREAMING_SNAKE_CASE   ,      'w'   ,      encoding='utf-8') as vocab_writer:
            vocab_writer.write(''.join([x + '\n' for x in self.vocab_tokens]))

          a__:					List[str]      							=     BertTokenizerFast.from_pretrained(_SCREAMING_SNAKE_CASE)
          bert_tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE)
          a__:					Optional[Any]      							=     CustomTokenizerFast.from_pretrained(_SCREAMING_SNAKE_CASE)

        tokenizer.push_to_hub('test-dynamic-tokenizer'   ,      use_auth_token=self._token)

        a__:					Tuple      							=     AutoTokenizer.from_pretrained(f'{USER}/test-dynamic-tokenizer'   ,      trust_remote_code=_SCREAMING_SNAKE_CASE)
        # Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
        self.assertEqual(tokenizer.__class__.__name__   ,      'CustomTokenizerFast')
        a__:					Optional[int]      							=     AutoTokenizer.from_pretrained(
            f'{USER}/test-dynamic-tokenizer'   ,      use_fast=_SCREAMING_SNAKE_CASE   ,      trust_remote_code=_SCREAMING_SNAKE_CASE)
        # Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
        self.assertEqual(tokenizer.__class__.__name__   ,      'CustomTokenizer')







class        __snake_case	(					unittest.TestCase    ):



      def   lowerCamelCase_       (						self)     ->      Optional[int]:





        '''simple docstring'''





        a__:					Tuple      							=     Trie()
        trie.add('Hello 友達')
        self.assertEqual(trie.data   ,      {'H': {'e': {'l': {'l': {'o': {' ': {'友': {'達': {'': 1}}}}}}}}})
        trie.add('Hello')
        trie.data
        self.assertEqual(trie.data   ,      {'H': {'e': {'l': {'l': {'o': {'': 1, ' ': {'友': {'達': {'': 1}}}}}}}}})



      def   lowerCamelCase_       (						self)     ->      List[Any]:





        '''simple docstring'''





        a__:					Optional[int]      							=     Trie()
        self.assertEqual(trie.split('[CLS] This is a extra_id_100')   ,      ['[CLS] This is a extra_id_100'])
        trie.add('[CLS]')
        trie.add('extra_id_1')
        trie.add('extra_id_100')
        self.assertEqual(trie.split('[CLS] This is a extra_id_100')   ,      ['[CLS]', ' This is a ', 'extra_id_100'])



      def   lowerCamelCase_       (						self)     ->      List[str]:





        '''simple docstring'''





        a__:					Optional[int]      							=     Trie()
        trie.add('A')
        self.assertEqual(trie.split('ABC')   ,      ['A', 'BC'])
        self.assertEqual(trie.split('BCA')   ,      ['BC', 'A'])



      def   lowerCamelCase_       (						self)     ->      Union[str, Any]:





        '''simple docstring'''





        a__:					Optional[Any]      							=     Trie()
        trie.add('TOKEN]')
        trie.add('[SPECIAL_TOKEN]')
        self.assertEqual(trie.split('This is something [SPECIAL_TOKEN]')   ,      ['This is something ', '[SPECIAL_TOKEN]'])



      def   lowerCamelCase_       (						self)     ->      int:





        '''simple docstring'''





        a__:					List[Any]      							=     Trie()
        trie.add('A')
        trie.add('P')
        trie.add('[SPECIAL_TOKEN]')
        self.assertEqual(trie.split('This is something [SPECIAL_TOKEN]')   ,      ['This is something ', '[SPECIAL_TOKEN]'])



      def   lowerCamelCase_       (						self)     ->      Optional[int]:





        '''simple docstring'''





        a__:					Union[str, Any]      							=     Trie()
        trie.add('AB')
        trie.add('B')
        trie.add('C')
        self.assertEqual(trie.split('ABC')   ,      ['AB', 'C'])



      def   lowerCamelCase_       (						self)     ->      List[Any]:





        '''simple docstring'''





        a__:					List[str]      							=     Trie()
        trie.add('ABC')
        trie.add('B')
        trie.add('CD')
        self.assertEqual(trie.split('ABCD')   ,      ['ABC', 'D'])



      def   lowerCamelCase_       (						self)     ->      int:





        '''simple docstring'''





        a__:					List[str]      							=     Trie()
        a__:					Any      							=     trie.cut_text('ABC'   ,      [0, 0, 2, 1, 2, 3])
        self.assertEqual(_SCREAMING_SNAKE_CASE   ,      ['AB', 'C'])



"""simple docstring"""
from __future__ import annotations




class        __snake_case	:



      def __init__(						self   ,      lowercase=None)     ->      Optional[Any]:





        '''simple docstring'''





        a__:					int      							=     data
        a__:					str      							=     None



      def __repr__(						self)     ->      List[str]:





        '''simple docstring'''





        a__:					Optional[Any]      							=     []
        a__:					Union[str, Any]      							=     self
        while temp:
          string_rep.append(f'{temp.data}')
          a__:					Tuple      							=     temp.next
        return "->".join(lowercase)







def 						__a       (     _SCREAMING_SNAKE_CASE       )     ->str:
  if not elements_list:
    raise Exception('The Elements List is empty'       )

  a__:					Any      							=     Node(elements_list[0]       )
  for i in range(1		,					len(_SCREAMING_SNAKE_CASE       )       ):
    a__:					Optional[Any]      							=     Node(elements_list[i]       )
    a__:					Tuple      							=     current.next
  return head







def 						__a       (     _SCREAMING_SNAKE_CASE       )     ->None:
  if head_node is not None and isinstance(_SCREAMING_SNAKE_CASE		,					_SCREAMING_SNAKE_CASE       ):
    print_reverse(head_node.next       )
    print(head_node.data       )







def 						__a       (     )     ->Optional[Any]:
  from doctest import testmod

  testmod()

  a__:					Tuple      							=     make_linked_list([14, 52, 14, 12, 43]       )
  print('Linked List:'       )
  print(_SCREAMING_SNAKE_CASE       )
  print('Elements in Reverse:'       )
  print_reverse(_SCREAMING_SNAKE_CASE       )


if __name__ == "__main__":
 main()


