




"""simple docstring"""







from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
    IMAGENET_STANDARD_MEAN,
    IMAGENET_STANDARD_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


if is_vision_available():
  import PIL


SCREAMING_SNAKE_CASE_	     =       logging.get_logger(__name__)

class 				snake_case_			(					lowerCamelCase_			):







   """simple docstring"""




   A_				      =       ['''pixel_values''']







   def __init__(		self       ,					lowerCamelCase_ = True       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = PIL.Image.BICUBIC       ,					lowerCamelCase_ = True       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = 1 / 2_5_5       ,					lowerCamelCase_ = True       ,					lowerCamelCase_ = True       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = None       ,					**lowerCamelCase_       ,					)				->   None:
       super().__init__(**lowerCamelCase_)
       UpperCamelCase              =	size if size is not None else {'''height''': 2_5_6, '''width''': 2_5_6}
       UpperCamelCase              =	get_size_dict(lowerCamelCase_)
       UpperCamelCase              =	crop_size if crop_size is not None else {'''height''': 2_2_4, '''width''': 2_2_4}
       UpperCamelCase              =	get_size_dict(lowerCamelCase_       ,					param_name='''crop_size''')

       UpperCamelCase              =	do_resize
       UpperCamelCase              =	size
       UpperCamelCase              =	resample
       UpperCamelCase              =	do_center_crop
       UpperCamelCase              =	crop_size
       UpperCamelCase              =	do_rescale
       UpperCamelCase              =	rescale_factor
       UpperCamelCase              =	do_normalize
       UpperCamelCase              =	image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
       UpperCamelCase              =	image_std if image_std is not None else IMAGENET_STANDARD_STD







   def   UpperCAmelCase__			(		self       ,					lowerCamelCase_       ,					lowerCamelCase_       ,					lowerCamelCase_ = PIL.Image.BICUBIC       ,					lowerCamelCase_ = None       ,					**lowerCamelCase_       ,					)				->   np.ndarray:
       UpperCamelCase              =	get_size_dict(lowerCamelCase_)
       if "height" not in size or "width" not in size:
           raise ValueError(F'The size dictionary must have keys \'height\' and \'width\'. Got {size.keys()}')
       return resize(
           lowerCamelCase_       ,					size=(size['''height'''], size['''width'''])       ,					resample=lowerCamelCase_       ,					data_format=lowerCamelCase_       ,					**lowerCamelCase_)







   def   UpperCAmelCase__			(		self       ,					lowerCamelCase_       ,					lowerCamelCase_       ,					lowerCamelCase_ = None       ,					**lowerCamelCase_       ,					)				->   np.ndarray:
       UpperCamelCase              =	get_size_dict(lowerCamelCase_)
       if "height" not in size or "width" not in size:
           raise ValueError(F'The size dictionary must have keys \'height\' and \'width\'. Got {size.keys()}')
       return center_crop(lowerCamelCase_       ,					size=(size['''height'''], size['''width'''])       ,					data_format=lowerCamelCase_       ,					**lowerCamelCase_)







   def   UpperCAmelCase__			(		self       ,					lowerCamelCase_       ,					lowerCamelCase_       ,					lowerCamelCase_ = None       ,					**lowerCamelCase_       ,					)				->   Tuple:
       return rescale(lowerCamelCase_       ,					scale=lowerCamelCase_       ,					data_format=lowerCamelCase_       ,					**lowerCamelCase_)







   def   UpperCAmelCase__			(		self       ,					lowerCamelCase_       ,					lowerCamelCase_       ,					lowerCamelCase_       ,					lowerCamelCase_ = None       ,					**lowerCamelCase_       ,					)				->   np.ndarray:
       return normalize(lowerCamelCase_       ,					mean=lowerCamelCase_       ,					std=lowerCamelCase_       ,					data_format=lowerCamelCase_       ,					**lowerCamelCase_)







   def   UpperCAmelCase__			(		self       ,					lowerCamelCase_       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = None       ,					lowerCamelCase_=None       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = None       ,					lowerCamelCase_ = ChannelDimension.FIRST       ,					**lowerCamelCase_       ,					)				->   PIL.Image.Image:
       UpperCamelCase              =	do_resize if do_resize is not None else self.do_resize
       UpperCamelCase              =	resample if resample is not None else self.resample
       UpperCamelCase              =	do_center_crop if do_center_crop is not None else self.do_center_crop
       UpperCamelCase              =	do_rescale if do_rescale is not None else self.do_rescale
       UpperCamelCase              =	rescale_factor if rescale_factor is not None else self.rescale_factor
       UpperCamelCase              =	do_normalize if do_normalize is not None else self.do_normalize
       UpperCamelCase              =	image_mean if image_mean is not None else self.image_mean
       UpperCamelCase              =	image_std if image_std is not None else self.image_std

       UpperCamelCase              =	size if size is not None else self.size
       UpperCamelCase              =	get_size_dict(lowerCamelCase_)
       UpperCamelCase              =	crop_size if crop_size is not None else self.crop_size
       UpperCamelCase              =	get_size_dict(lowerCamelCase_       ,					param_name='''crop_size''')

       UpperCamelCase              =	make_list_of_images(lowerCamelCase_)

       if not valid_images(lowerCamelCase_):
           raise ValueError(
               '''Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, '''
               '''torch.Tensor, tf.Tensor or jax.ndarray.''')

       if do_resize and size is None or resample is None:
           raise ValueError('''Size and resample must be specified if do_resize is True.''')

       if do_center_crop and crop_size is None:
           raise ValueError('''Crop size must be specified if do_center_crop is True.''')

       if do_rescale and rescale_factor is None:
           raise ValueError('''Rescale factor must be specified if do_rescale is True.''')

       if do_normalize and (image_mean is None or image_std is None):
           raise ValueError('''Image mean and std must be specified if do_normalize is True.''')

       # All transformations expect numpy arrays.
       UpperCamelCase              =	[to_numpy_array(lowerCamelCase_) for image in images]

       if do_resize:
           UpperCamelCase              =	[self.resize(image=lowerCamelCase_       ,					size=lowerCamelCase_       ,					resample=lowerCamelCase_) for image in images]

       if do_center_crop:
           UpperCamelCase              =	[self.center_crop(image=lowerCamelCase_       ,					size=lowerCamelCase_) for image in images]

       if do_rescale:
           UpperCamelCase              =	[self.rescale(image=lowerCamelCase_       ,					scale=lowerCamelCase_) for image in images]

       if do_normalize:
           UpperCamelCase              =	[self.normalize(image=lowerCamelCase_       ,					mean=lowerCamelCase_       ,					std=lowerCamelCase_) for image in images]

       UpperCamelCase              =	[to_channel_dimension_format(lowerCamelCase_       ,					lowerCamelCase_) for image in images]

       UpperCamelCase              =	{'''pixel_values''': images}
       return BatchFeature(data=lowerCamelCase_       ,					tensor_type=lowerCamelCase_)

"""simple docstring"""


import json
import os
import unittest

from transformers.models.roc_bert.tokenization_roc_bert import (
    VOCAB_FILES_NAMES,
    RoCBertBasicTokenizer,
    RoCBertTokenizer,
    RoCBertWordpieceTokenizer,
    _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  __lowerCamelCase  ( lowerCAmelCase						,	unittest.TestCase			):
				a__:      Tuple          =    RoCBertTokenizer
				a__:      int          =    None
				a__:      Optional[Any]          =    False
				a__:      Optional[int]          =    True
				a__:      Tuple          =    filter_non_english




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

							lowerCamelCase_					=  ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''你''', '''好''', '''是''', '''谁''', '''a''', '''b''', '''c''', '''d''']
							lowerCamelCase_					=  {}
							lowerCamelCase_					=  {}
							for i, value in enumerate(UpperCAmelCase   ):
										lowerCamelCase_					=  i
										lowerCamelCase_					=  i
							lowerCamelCase_					=  os.path.join(self.tmpdirname							,						VOCAB_FILES_NAMES['''vocab_file''']   )
							lowerCamelCase_					=  os.path.join(self.tmpdirname							,						VOCAB_FILES_NAMES['''word_shape_file''']   )
							lowerCamelCase_					=  os.path.join(self.tmpdirname							,						VOCAB_FILES_NAMES['''word_pronunciation_file''']   )
							with open(self.vocab_file							,						'''w'''							,						encoding='''utf-8'''   ) as vocab_writer:
										vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]   )   )
							with open(self.word_shape_file							,						'''w'''							,						encoding='''utf-8'''   ) as word_shape_writer:
										json.dump(UpperCAmelCase							,						UpperCAmelCase							,						ensure_ascii=UpperCAmelCase   )
							with open(self.word_pronunciation_file							,						'''w'''							,						encoding='''utf-8'''   ) as word_pronunciation_writer:
										json.dump(UpperCAmelCase							,						UpperCAmelCase							,						ensure_ascii=UpperCAmelCase   )




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  self.tokenizer_class(self.vocab_file							,						self.word_shape_file							,						self.word_pronunciation_file   )

							lowerCamelCase_					=  tokenizer.tokenize('''你好[SEP]你是谁'''   )
							self.assertListEqual(UpperCAmelCase							,						['''你''', '''好''', '''[SEP]''', '''你''', '''是''', '''谁''']   )
							self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase   )							,						[5, 6, 2, 5, 7, 8]   )
							self.assertListEqual(tokenizer.convert_tokens_to_shape_ids(UpperCAmelCase   )							,						[5, 6, 2, 5, 7, 8]   )
							self.assertListEqual(tokenizer.convert_tokens_to_pronunciation_ids(UpperCAmelCase   )							,						[5, 6, 2, 5, 7, 8]   )




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  RoCBertBasicTokenizer()

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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  RoCBertBasicTokenizer(do_lower_case=UpperCAmelCase   )

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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  RoCBertBasicTokenizer(do_lower_case=UpperCAmelCase							,						strip_accents=UpperCAmelCase   )

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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  RoCBertBasicTokenizer(do_lower_case=UpperCAmelCase							,						strip_accents=UpperCAmelCase   )

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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  RoCBertBasicTokenizer(do_lower_case=UpperCAmelCase   )

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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  RoCBertBasicTokenizer(do_lower_case=UpperCAmelCase   )

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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  RoCBertBasicTokenizer(do_lower_case=UpperCAmelCase							,						strip_accents=UpperCAmelCase   )

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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  RoCBertBasicTokenizer(do_lower_case=UpperCAmelCase							,						strip_accents=UpperCAmelCase   )

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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  RoCBertBasicTokenizer(do_lower_case=UpperCAmelCase							,						never_split=['''[UNK]''']   )

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




				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

							lowerCamelCase_					=  {}
							for i, token in enumerate(UpperCAmelCase   ):
										lowerCamelCase_					=  i
							lowerCamelCase_					=  RoCBertWordpieceTokenizer(vocab=UpperCAmelCase							,						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   ):
							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   ):
							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   ):
							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   ):
							lowerCamelCase_					=  self.get_tokenizer()

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

							if self.test_rust_tokenizer:
										lowerCamelCase_					=  self.get_rust_tokenizer()
										self.assertListEqual(
										    [rust_tokenizer.tokenize(UpperCAmelCase   ) for t in ['''Test''', '''\xad''', '''test''']]							,						[['''[UNK]'''], [], ['''[UNK]''']]   )




				def        UpperCAmelCase__						(				self   ):
							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(UpperCAmelCase							,						**UpperCAmelCase   )

													lowerCamelCase_					=  f"A, naïve {tokenizer_r.mask_token} AllenNLP sentence."
													lowerCamelCase_					=  tokenizer_r.encode_plus(
													    UpperCAmelCase							,						return_attention_mask=UpperCAmelCase							,						return_token_type_ids=UpperCAmelCase							,						return_offsets_mapping=UpperCAmelCase							,						add_special_tokens=UpperCAmelCase							,						)

													lowerCamelCase_					=  tokenizer_r.do_lower_case if hasattr(UpperCAmelCase							,						'''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   ):
							lowerCamelCase_					=  ['''的''', '''人''', '''有''']
							lowerCamelCase_					=  ''''''.join(UpperCAmelCase   )
							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(UpperCAmelCase							,						**UpperCAmelCase   )
													lowerCamelCase_					=  self.rust_tokenizer_class.from_pretrained(UpperCAmelCase							,						**UpperCAmelCase   )

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

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

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

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

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

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

													# 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(UpperCAmelCase   )
													]
													self.assertListEqual(UpperCAmelCase							,						UpperCAmelCase   )
													self.assertListEqual(UpperCAmelCase							,						UpperCAmelCase   )




				@slow
				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  self.tokenizer_class(self.vocab_file							,						self.word_shape_file							,						self.word_pronunciation_file   )

							lowerCamelCase_					=  tokenizer.encode('''你好'''							,						add_special_tokens=UpperCAmelCase   )
							lowerCamelCase_					=  tokenizer.encode('''你是谁'''							,						add_special_tokens=UpperCAmelCase   )

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

							assert encoded_sentence == [1] + text + [2]
							assert encoded_pair == [1] + text + [2] + text_a + [2]





				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  self.get_tokenizers(do_lower_case=UpperCAmelCase   )
							for tokenizer in tokenizers:
										with self.subTest(f"{tokenizer.__class__.__name__}"   ):
													lowerCamelCase_					=  '''你好，你是谁'''
													lowerCamelCase_					=  tokenizer.tokenize(UpperCAmelCase   )
													lowerCamelCase_					=  tokenizer.convert_tokens_to_ids(UpperCAmelCase   )
													lowerCamelCase_					=  tokenizer.convert_tokens_to_shape_ids(UpperCAmelCase   )
													lowerCamelCase_					=  tokenizer.convert_tokens_to_pronunciation_ids(UpperCAmelCase   )
													lowerCamelCase_					=  tokenizer.prepare_for_model(
													    UpperCAmelCase							,						UpperCAmelCase							,						UpperCAmelCase							,						add_special_tokens=UpperCAmelCase   )

													lowerCamelCase_					=  tokenizer.encode_plus(UpperCAmelCase							,						add_special_tokens=UpperCAmelCase   )

													self.assertEqual(UpperCAmelCase							,						UpperCAmelCase   )



