






"""simple docstring"""





import unittest

import numpy as np

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
  import torch

if is_vision_available():
  from PIL import Image

  from transformers import LevitImageProcessor






class      a						(					unittest.TestCase		):






    def __init__(       self     :							List[str]       ,						__SCREAMING_SNAKE_CASE     :							Optional[int]       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=7       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=3       ,						__SCREAMING_SNAKE_CASE     :							Tuple=18       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any]=30       ,						__SCREAMING_SNAKE_CASE     :							List[Any]=400       ,						__SCREAMING_SNAKE_CASE     :							Dict=True       ,						__SCREAMING_SNAKE_CASE     :							Any=None       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any]=True       ,						__SCREAMING_SNAKE_CASE     :							Tuple=None       ,						__SCREAMING_SNAKE_CASE     :							int=True       ,						__SCREAMING_SNAKE_CASE     :							Tuple=[0.5, 0.5, 0.5]       ,						__SCREAMING_SNAKE_CASE     :							str=[0.5, 0.5, 0.5]       ,						)     ->		Optional[Any]:
      lowerCamelCase_         =						size if size is not None else {'shortest_edge': 18}
      lowerCamelCase_         =						crop_size if crop_size is not None else {'height': 18, 'width': 18}
      lowerCamelCase_         =						parent
      lowerCamelCase_         =						batch_size
      lowerCamelCase_         =						num_channels
      lowerCamelCase_         =						image_size
      lowerCamelCase_         =						min_resolution
      lowerCamelCase_         =						max_resolution
      lowerCamelCase_         =						do_resize
      lowerCamelCase_         =						size
      lowerCamelCase_         =						do_center_crop
      lowerCamelCase_         =						crop_size
      lowerCamelCase_         =						do_normalize
      lowerCamelCase_         =						image_mean
      lowerCamelCase_         =						image_std






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		Any:
      return {
          "image_mean": self.image_mean,
          "image_std": self.image_std,
          "do_normalize": self.do_normalize,
          "do_resize": self.do_resize,
          "do_center_crop": self.do_center_crop,
          "size": self.size,
          "crop_size": self.crop_size,
      }






@require_torch
@require_vision
class      a						(					__snake_case  ,      unittest.TestCase		):
    SCREAMING_SNAKE_CASE						:     Any						= LevitImageProcessor if is_vision_available() else None






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






    @property
    def    UpperCamelCase       (       self     :							Tuple					)     ->		Optional[int]:
      return self.image_processor_tester.prepare_image_processor_dict()






    def    UpperCamelCase       (       self     :							int					)     ->		Optional[Any]:
      lowerCamelCase_         =						self.image_processing_class(**self.image_processor_dict					)
      self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE       ,						'image_mean'					)					)
      self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE       ,						'image_std'					)					)
      self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE       ,						'do_normalize'					)					)
      self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE       ,						'do_resize'					)					)
      self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE       ,						'do_center_crop'					)					)
      self.assertTrue(hasattr(__SCREAMING_SNAKE_CASE       ,						'size'					)					)






    def    UpperCamelCase       (       self     :							str					)     ->		List[Any]:
      lowerCamelCase_         =						self.image_processing_class.from_dict(self.image_processor_dict					)
      self.assertEqual(image_processor.size       ,						{'shortest_edge': 18}					)
      self.assertEqual(image_processor.crop_size       ,						{'height': 18, 'width': 18}					)

      lowerCamelCase_         =						self.image_processing_class.from_dict(self.image_processor_dict       ,						size=42       ,						crop_size=84					)
      self.assertEqual(image_processor.size       ,						{'shortest_edge': 42}					)
      self.assertEqual(image_processor.crop_size       ,						{'height': 84, 'width': 84}					)






    def    UpperCamelCase       (       self     :							Optional[Any]					)     ->		int:
      pass






    def    UpperCamelCase       (       self     :							Tuple					)     ->		Optional[int]:
      # Initialize image_processing
      lowerCamelCase_         =						self.image_processing_class(**self.image_processor_dict					)
      # create random PIL images
      lowerCamelCase_         =						prepare_image_inputs(self.image_processor_tester       ,						equal_resolution=__SCREAMING_SNAKE_CASE					)
      for image in image_inputs:
        self.assertIsInstance(__SCREAMING_SNAKE_CASE       ,						Image.Image					)

      # Test not batched input
      lowerCamelCase_         =						image_processing(image_inputs[0]       ,						return_tensors='pt'					).pixel_values
      self.assertEqual(
          encoded_images.shape       ,						(
              1,
              self.image_processor_tester.num_channels,
              self.image_processor_tester.crop_size['height'],
              self.image_processor_tester.crop_size['width'],
          )       ,						)

      # Test batched
      lowerCamelCase_         =						image_processing(__SCREAMING_SNAKE_CASE       ,						return_tensors='pt'					).pixel_values
      self.assertEqual(
          encoded_images.shape       ,						(
              self.image_processor_tester.batch_size,
              self.image_processor_tester.num_channels,
              self.image_processor_tester.crop_size['height'],
              self.image_processor_tester.crop_size['width'],
          )       ,						)






    def    UpperCamelCase       (       self     :							int					)     ->		Dict:
      # Initialize image_processing
      lowerCamelCase_         =						self.image_processing_class(**self.image_processor_dict					)
      # create random numpy tensors
      lowerCamelCase_         =						prepare_image_inputs(self.image_processor_tester       ,						equal_resolution=__SCREAMING_SNAKE_CASE       ,						numpify=__SCREAMING_SNAKE_CASE					)
      for image in image_inputs:
        self.assertIsInstance(__SCREAMING_SNAKE_CASE       ,						np.ndarray					)

      # Test not batched input
      lowerCamelCase_         =						image_processing(image_inputs[0]       ,						return_tensors='pt'					).pixel_values
      self.assertEqual(
          encoded_images.shape       ,						(
              1,
              self.image_processor_tester.num_channels,
              self.image_processor_tester.crop_size['height'],
              self.image_processor_tester.crop_size['width'],
          )       ,						)

      # Test batched
      lowerCamelCase_         =						image_processing(__SCREAMING_SNAKE_CASE       ,						return_tensors='pt'					).pixel_values
      self.assertEqual(
          encoded_images.shape       ,						(
              self.image_processor_tester.batch_size,
              self.image_processor_tester.num_channels,
              self.image_processor_tester.crop_size['height'],
              self.image_processor_tester.crop_size['width'],
          )       ,						)






    def    UpperCamelCase       (       self     :							List[str]					)     ->		int:
      # Initialize image_processing
      lowerCamelCase_         =						self.image_processing_class(**self.image_processor_dict					)
      # create random PyTorch tensors
      lowerCamelCase_         =						prepare_image_inputs(self.image_processor_tester       ,						equal_resolution=__SCREAMING_SNAKE_CASE       ,						torchify=__SCREAMING_SNAKE_CASE					)
      for image in image_inputs:
        self.assertIsInstance(__SCREAMING_SNAKE_CASE       ,						torch.Tensor					)

      # Test not batched input
      lowerCamelCase_         =						image_processing(image_inputs[0]       ,						return_tensors='pt'					).pixel_values
      self.assertEqual(
          encoded_images.shape       ,						(
              1,
              self.image_processor_tester.num_channels,
              self.image_processor_tester.crop_size['height'],
              self.image_processor_tester.crop_size['width'],
          )       ,						)

      # Test batched
      lowerCamelCase_         =						image_processing(__SCREAMING_SNAKE_CASE       ,						return_tensors='pt'					).pixel_values
      self.assertEqual(
          encoded_images.shape       ,						(
              self.image_processor_tester.batch_size,
              self.image_processor_tester.num_channels,
              self.image_processor_tester.crop_size['height'],
              self.image_processor_tester.crop_size['width'],
          )       ,						)












"""simple docstring"""





import os
import unittest

from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english






@require_tokenizers
class      a						(					__snake_case  ,      unittest.TestCase		):
    SCREAMING_SNAKE_CASE						:     List[str]						= MobileBertTokenizer
    SCREAMING_SNAKE_CASE						:     int						= MobileBertTokenizerFast
    SCREAMING_SNAKE_CASE						:     Union[str, Any]						= True
    SCREAMING_SNAKE_CASE						:     Optional[Any]						= True
    SCREAMING_SNAKE_CASE						:     Dict						= filter_non_english
    SCREAMING_SNAKE_CASE						:     str						= """google/mobilebert-uncased"""






    def    UpperCamelCase       (       self     :							List[str]					)     ->		Dict:
      super().setUp()

      lowerCamelCase_         =						[
          '[UNK]',
          '[CLS]',
          '[SEP]',
          '[PAD]',
          '[MASK]',
          'want',
          '##want',
          '##ed',
          'wa',
          'un',
          'runn',
          '##ing',
          ',',
          'low',
          'lowest',
      ]
      lowerCamelCase_         =						os.path.join(self.tmpdirname       ,						VOCAB_FILES_NAMES['vocab_file']					)
      with open(self.vocab_file       ,						'w'       ,						encoding='utf-8'					) as vocab_writer:
        vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]					)					)

      lowerCamelCase_         =						[
          (tokenizer_def[0], self.pre_trained_model_path, tokenizer_def[2])  # else the 'google/' prefix is stripped
          for tokenizer_def in self.tokenizers_list
      ]






    def    UpperCamelCase       (       self     :							List[Any]       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any]					)     ->		int:
      lowerCamelCase_         =						'UNwant\u00E9d,running'
      lowerCamelCase_         =						'unwanted, running'
      return input_text, output_text






    def    UpperCamelCase       (       self     :							Dict					)     ->		Any:
      lowerCamelCase_         =						self.tokenizer_class(self.vocab_file					)

      lowerCamelCase_         =						tokenizer.tokenize('UNwant\u00E9d,running'					)
      self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						['un', '##want', '##ed', ',', 'runn', '##ing']					)
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE					)       ,						[9, 6, 7, 12, 10, 11]					)






    def    UpperCamelCase       (       self     :							Dict					)     ->		Dict:
      if not self.test_rust_tokenizer:
        return

      lowerCamelCase_         =						self.get_tokenizer()
      lowerCamelCase_         =						self.get_rust_tokenizer()

      lowerCamelCase_         =						'UNwant\u00E9d,running'

      lowerCamelCase_         =						tokenizer.tokenize(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						rust_tokenizer.tokenize(__SCREAMING_SNAKE_CASE					)
      self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)

      lowerCamelCase_         =						tokenizer.encode(__SCREAMING_SNAKE_CASE       ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						rust_tokenizer.encode(__SCREAMING_SNAKE_CASE       ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)
      self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)

      lowerCamelCase_         =						self.get_rust_tokenizer()
      lowerCamelCase_         =						tokenizer.encode(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						rust_tokenizer.encode(__SCREAMING_SNAKE_CASE					)
      self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)

      # With lower casing
      lowerCamelCase_         =						self.get_tokenizer(do_lower_case=__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						self.get_rust_tokenizer(do_lower_case=__SCREAMING_SNAKE_CASE					)

      lowerCamelCase_         =						'UNwant\u00E9d,running'

      lowerCamelCase_         =						tokenizer.tokenize(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						rust_tokenizer.tokenize(__SCREAMING_SNAKE_CASE					)
      self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)

      lowerCamelCase_         =						tokenizer.encode(__SCREAMING_SNAKE_CASE       ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						rust_tokenizer.encode(__SCREAMING_SNAKE_CASE       ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)
      self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)

      lowerCamelCase_         =						self.get_rust_tokenizer()
      lowerCamelCase_         =						tokenizer.encode(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						rust_tokenizer.encode(__SCREAMING_SNAKE_CASE					)
      self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)






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

      self.assertListEqual(tokenizer.tokenize('ah\u535A\u63A8zz'					)       ,						['ah', '\u535A', '\u63A8', 'zz']					)






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		Optional[int]:
      lowerCamelCase_         =						BasicTokenizer(do_lower_case=__SCREAMING_SNAKE_CASE					)

      self.assertListEqual(
          tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '					)       ,						['hello', '!', 'how', 'are', 'you', '?']					)
      self.assertListEqual(tokenizer.tokenize('H\u00E9llo'					)       ,						['hello']					)






    def    UpperCamelCase       (       self     :							Any					)     ->		Any:
      lowerCamelCase_         =						BasicTokenizer(do_lower_case=__SCREAMING_SNAKE_CASE       ,						strip_accents=__SCREAMING_SNAKE_CASE					)

      self.assertListEqual(
          tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '					)       ,						['hällo', '!', 'how', 'are', 'you', '?']					)
      self.assertListEqual(tokenizer.tokenize('H\u00E9llo'					)       ,						['h\u00E9llo']					)






    def    UpperCamelCase       (       self     :							Tuple					)     ->		Union[str, Any]:
      lowerCamelCase_         =						BasicTokenizer(do_lower_case=__SCREAMING_SNAKE_CASE       ,						strip_accents=__SCREAMING_SNAKE_CASE					)

      self.assertListEqual(
          tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '					)       ,						['hallo', '!', 'how', 'are', 'you', '?']					)
      self.assertListEqual(tokenizer.tokenize('H\u00E9llo'					)       ,						['hello']					)






    def    UpperCamelCase       (       self     :							Tuple					)     ->		List[str]:
      lowerCamelCase_         =						BasicTokenizer(do_lower_case=__SCREAMING_SNAKE_CASE					)

      self.assertListEqual(
          tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '					)       ,						['hallo', '!', 'how', 'are', 'you', '?']					)
      self.assertListEqual(tokenizer.tokenize('H\u00E9llo'					)       ,						['hello']					)






    def    UpperCamelCase       (       self     :							Optional[int]					)     ->		Any:
      lowerCamelCase_         =						BasicTokenizer(do_lower_case=__SCREAMING_SNAKE_CASE					)

      self.assertListEqual(
          tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '					)       ,						['HeLLo', '!', 'how', 'Are', 'yoU', '?']					)






    def    UpperCamelCase       (       self     :							Tuple					)     ->		Tuple:
      lowerCamelCase_         =						BasicTokenizer(do_lower_case=__SCREAMING_SNAKE_CASE       ,						strip_accents=__SCREAMING_SNAKE_CASE					)

      self.assertListEqual(
          tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '					)       ,						['HäLLo', '!', 'how', 'Are', 'yoU', '?']					)






    def    UpperCamelCase       (       self     :							List[str]					)     ->		List[Any]:
      lowerCamelCase_         =						BasicTokenizer(do_lower_case=__SCREAMING_SNAKE_CASE       ,						strip_accents=__SCREAMING_SNAKE_CASE					)

      self.assertListEqual(
          tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '					)       ,						['HaLLo', '!', 'how', 'Are', 'yoU', '?']					)






    def    UpperCamelCase       (       self     :							Tuple					)     ->		str:
      lowerCamelCase_         =						BasicTokenizer(do_lower_case=__SCREAMING_SNAKE_CASE       ,						never_split=['[UNK]']					)

      self.assertListEqual(
          tokenizer.tokenize(' \tHeLLo!how  \n Are yoU? [UNK]'					)       ,						['HeLLo', '!', 'how', 'Are', 'yoU', '?', '[UNK]']					)






    def    UpperCamelCase       (       self     :							List[str]					)     ->		Any:
      lowerCamelCase_         =						['[UNK]', '[CLS]', '[SEP]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing']

      lowerCamelCase_         =						{}
      for i, token in enumerate(__SCREAMING_SNAKE_CASE					):
        lowerCamelCase_         =						i
      lowerCamelCase_         =						WordpieceTokenizer(vocab=__SCREAMING_SNAKE_CASE       ,						unk_token='[UNK]'					)

      self.assertListEqual(tokenizer.tokenize(''					)       ,						[]					)

      self.assertListEqual(tokenizer.tokenize('unwanted running'					)       ,						['un', '##want', '##ed', 'runn', '##ing']					)

      self.assertListEqual(tokenizer.tokenize('unwantedX running'					)       ,						['[UNK]', 'runn', '##ing']					)






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		Any:
      self.assertTrue(_is_whitespace(' '					)					)
      self.assertTrue(_is_whitespace('\t'					)					)
      self.assertTrue(_is_whitespace('\r'					)					)
      self.assertTrue(_is_whitespace('\n'					)					)
      self.assertTrue(_is_whitespace('\u00A0'					)					)

      self.assertFalse(_is_whitespace('A'					)					)
      self.assertFalse(_is_whitespace('-'					)					)






    def    UpperCamelCase       (       self     :							Union[str, Any]					)     ->		int:
      self.assertTrue(_is_control('\u0005'					)					)

      self.assertFalse(_is_control('A'					)					)
      self.assertFalse(_is_control(' '					)					)
      self.assertFalse(_is_control('\t'					)					)
      self.assertFalse(_is_control('\r'					)					)






    def    UpperCamelCase       (       self     :							str					)     ->		Optional[Any]:
      self.assertTrue(_is_punctuation('-'					)					)
      self.assertTrue(_is_punctuation('$'					)					)
      self.assertTrue(_is_punctuation('`'					)					)
      self.assertTrue(_is_punctuation('.'					)					)

      self.assertFalse(_is_punctuation('A'					)					)
      self.assertFalse(_is_punctuation(' '					)					)






    def    UpperCamelCase       (       self     :							int					)     ->		List[Any]:
      lowerCamelCase_         =						self.get_tokenizer()
      lowerCamelCase_         =						self.get_rust_tokenizer()

      # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
      self.assertListEqual([tokenizer.tokenize(__SCREAMING_SNAKE_CASE					) for t in ['Test', '\xad', 'test']]       ,						[['[UNK]'], [], ['[UNK]']]					)

      self.assertListEqual(
          [rust_tokenizer.tokenize(__SCREAMING_SNAKE_CASE					) for t in ['Test', '\xad', 'test']]       ,						[['[UNK]'], [], ['[UNK]']]					)






    @slow
    def    UpperCamelCase       (       self     :							Dict					)     ->		List[str]:
      lowerCamelCase_         =						self.tokenizer_class.from_pretrained('google/mobilebert-uncased'					)

      lowerCamelCase_         =						tokenizer.encode('sequence builders'       ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						tokenizer.encode('multi-sequence build'       ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)

      lowerCamelCase_         =						tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)

      assert encoded_sentence == [101] + text + [102]
      assert encoded_pair == [101] + text + [102] + text_a + [102]






    def    UpperCamelCase       (       self     :							Tuple					)     ->		Union[str, Any]:
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''					):
          lowerCamelCase_         =						self.rust_tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE       ,						**__SCREAMING_SNAKE_CASE					)

          lowerCamelCase_         =						F'''A, naïve {tokenizer_r.mask_token} AllenNLP sentence.'''
          lowerCamelCase_         =						tokenizer_r.encode_plus(
              __SCREAMING_SNAKE_CASE       ,						return_attention_mask=__SCREAMING_SNAKE_CASE       ,						return_token_type_ids=__SCREAMING_SNAKE_CASE       ,						return_offsets_mapping=__SCREAMING_SNAKE_CASE       ,						add_special_tokens=__SCREAMING_SNAKE_CASE       ,						)

          lowerCamelCase_         =						tokenizer_r.do_lower_case if hasattr(__SCREAMING_SNAKE_CASE       ,						'do_lower_case'					) else False
          lowerCamelCase_         =						(
              [
                  ((0, 0), tokenizer_r.cls_token),
                  ((0, 1), 'A'),
                  ((1, 2), ','),
                  ((3, 5), 'na'),
                  ((5, 6), '##ï'),
                  ((6, 8), '##ve'),
                  ((9, 15), tokenizer_r.mask_token),
                  ((16, 21), 'Allen'),
                  ((21, 23), '##NL'),
                  ((23, 24), '##P'),
                  ((25, 33), 'sentence'),
                  ((33, 34), '.'),
                  ((0, 0), tokenizer_r.sep_token),
              ]
              if not do_lower_case
              else [
                  ((0, 0), tokenizer_r.cls_token),
                  ((0, 1), 'a'),
                  ((1, 2), ','),
                  ((3, 8), 'naive'),
                  ((9, 15), tokenizer_r.mask_token),
                  ((16, 21), 'allen'),
                  ((21, 23), '##nl'),
                  ((23, 24), '##p'),
                  ((25, 33), 'sentence'),
                  ((33, 34), '.'),
                  ((0, 0), tokenizer_r.sep_token),
              ]
          )

          self.assertEqual(
              [e[1] for e in expected_results]       ,						tokenizer_r.convert_ids_to_tokens(tokens['input_ids']					)					)
          self.assertEqual([e[0] for e in expected_results]       ,						tokens['offset_mapping']					)






    def    UpperCamelCase       (       self     :							Any					)     ->		List[Any]:
      lowerCamelCase_         =						['的', '人', '有']
      lowerCamelCase_         =						''.join(__SCREAMING_SNAKE_CASE					)
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''					):
          lowerCamelCase_         =						True
          lowerCamelCase_         =						self.tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE       ,						**__SCREAMING_SNAKE_CASE					)
          lowerCamelCase_         =						self.rust_tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE       ,						**__SCREAMING_SNAKE_CASE					)

          lowerCamelCase_         =						tokenizer_p.encode(__SCREAMING_SNAKE_CASE       ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)
          lowerCamelCase_         =						tokenizer_r.encode(__SCREAMING_SNAKE_CASE       ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)

          lowerCamelCase_         =						tokenizer_r.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE					)
          lowerCamelCase_         =						tokenizer_p.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE					)

          # it is expected that each Chinese character is not preceded by "##"
          self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)
          self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)

          lowerCamelCase_         =						False
          lowerCamelCase_         =						self.rust_tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE       ,						**__SCREAMING_SNAKE_CASE					)
          lowerCamelCase_         =						self.tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE       ,						**__SCREAMING_SNAKE_CASE					)

          lowerCamelCase_         =						tokenizer_r.encode(__SCREAMING_SNAKE_CASE       ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)
          lowerCamelCase_         =						tokenizer_p.encode(__SCREAMING_SNAKE_CASE       ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)

          lowerCamelCase_         =						tokenizer_r.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE					)
          lowerCamelCase_         =						tokenizer_p.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE					)

          # it is expected that only the first Chinese character is not preceded by "##".
          lowerCamelCase_         =						[
              F'''##{token}''' if idx != 0 else token for idx, token in enumerate(__SCREAMING_SNAKE_CASE					)
          ]
          self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)
          self.assertListEqual(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)




