



'''simple docstring'''

import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig


_A				:    List[str]     						=logging.get_logger(__name__)

_A				:    Any     						={
    '''Intel/dpt-large''': '''https://huggingface.co/Intel/dpt-large/resolve/main/config.json''',
    # See all DPT models at https://huggingface.co/models?filter=dpt
}



class 		lowerCamelCase__      (						A     ):




					'''simple docstring'''



					A_						    =						"""dpt"""




					def __init__(  self				:	Tuple     ,  UpperCamelCase_				:	List[str]=768     ,  UpperCamelCase_				:	Tuple=12     ,  UpperCamelCase_				:	Tuple=12     ,  UpperCamelCase_				:	Union[str, Any]=3072     ,  UpperCamelCase_				:	Tuple="gelu"     ,  UpperCamelCase_				:	str=0.0     ,  UpperCamelCase_				:	Any=0.0     ,  UpperCamelCase_				:	List[str]=0.02     ,  UpperCamelCase_				:	int=1E-12     ,  UpperCamelCase_				:	List[Any]=384     ,  UpperCamelCase_				:	int=16     ,  UpperCamelCase_				:	Union[str, Any]=3     ,  UpperCamelCase_				:	Union[str, Any]=False     ,  UpperCamelCase_				:	Optional[Any]=True     ,  UpperCamelCase_				:	Union[str, Any]=[2, 5, 8, 11]     ,  UpperCamelCase_				:	Tuple="project"     ,  UpperCamelCase_				:	Tuple=[4, 2, 1, 0.5]     ,  UpperCamelCase_				:	List[Any]=[96, 192, 384, 768]     ,  UpperCamelCase_				:	Any=256     ,  UpperCamelCase_				:	Tuple=-1     ,  UpperCamelCase_				:	Dict=False     ,  UpperCamelCase_				:	int=True     ,  UpperCamelCase_				:	Dict=0.4     ,  UpperCamelCase_				:	List[str]=255     ,  UpperCamelCase_				:	str=0.1     ,  UpperCamelCase_				:	Union[str, Any]=[1, 1024, 24, 24]     ,  UpperCamelCase_				:	List[str]=[0, 1]     ,  UpperCamelCase_				:	Optional[Any]=None     ,  **UpperCamelCase_				:	Dict     ,  )  ->       Optional[Any]:



						'''simple docstring'''





						super().__init__(**UpperCamelCase_					)

						_lowercase					:       List[Any]       =		hidden_size
						_lowercase					:       Optional[int]       =		is_hybrid

						if self.is_hybrid:
							if backbone_config is None:
								logger.info('Initializing the config with a `BiT` backbone.'					)
								_lowercase					:       Optional[int]       =		{
								    'global_padding': 'same',
								    'layer_type': 'bottleneck',
								    'depths': [3, 4, 9],
								    'out_features': ['stage1', 'stage2', 'stage3'],
								    'embedding_dynamic_padding': True,
								}
								_lowercase					:       List[str]       =		BitConfig(**UpperCamelCase_					)
							elif isinstance(UpperCamelCase_     ,  UpperCamelCase_					):
								logger.info('Initializing the config with a `BiT` backbone.'					)
								_lowercase					:       List[Any]       =		BitConfig(**UpperCamelCase_					)
							elif isinstance(UpperCamelCase_     ,  UpperCamelCase_					):
								_lowercase					:       Any       =		backbone_config
							else:
								raise ValueError(
								    F'''backbone_config must be a dictionary or a `PretrainedConfig`, got {backbone_config.__class__}.'''					)

							_lowercase					:       Optional[int]       =		backbone_featmap_shape
							_lowercase					:       str       =		neck_ignore_stages

							if readout_type != "project":
								raise ValueError('Readout type must be \'project\' when using `DPT-hybrid` mode.'					)
						else:
							_lowercase					:       str       =		None
							_lowercase					:       List[str]       =		None
							_lowercase					:       Any       =		[]

						_lowercase					:       List[Any]       =		num_hidden_layers
						_lowercase					:       Optional[int]       =		num_attention_heads
						_lowercase					:       Any       =		intermediate_size
						_lowercase					:       Tuple       =		hidden_act
						_lowercase					:       Optional[int]       =		hidden_dropout_prob
						_lowercase					:       List[Any]       =		attention_probs_dropout_prob
						_lowercase					:       List[str]       =		initializer_range
						_lowercase					:       Union[str, Any]       =		layer_norm_eps
						_lowercase					:       Tuple       =		image_size
						_lowercase					:       List[Any]       =		patch_size
						_lowercase					:       int       =		num_channels
						_lowercase					:       Union[str, Any]       =		qkv_bias
						_lowercase					:       int       =		backbone_out_indices
						if readout_type not in ["ignore", "add", "project"]:
							raise ValueError('Readout_type must be one of [\'ignore\', \'add\', \'project\']'					)
						_lowercase					:       Any       =		readout_type
						_lowercase					:       str       =		reassemble_factors
						_lowercase					:       Union[str, Any]       =		neck_hidden_sizes
						_lowercase					:       Any       =		fusion_hidden_size
						_lowercase					:       Optional[int]       =		head_in_index
						_lowercase					:       str       =		use_batch_norm_in_fusion_residual
						# auxiliary head attributes (semantic segmentation)
						_lowercase					:       Optional[Any]       =		use_auxiliary_head
						_lowercase					:       Any       =		auxiliary_loss_weight
						_lowercase					:       Tuple       =		semantic_loss_ignore_index
						_lowercase					:       Optional[int]       =		semantic_classifier_dropout




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



						'''simple docstring'''





						_lowercase					:       Tuple       =		copy.deepcopy(self.__dict__					)

						if output["backbone_config"] is not None:
							_lowercase					:       Optional[int]       =		self.backbone_config.to_dict()

						_lowercase					:       Union[str, Any]       =		self.__class__.model_type
						return output





'''simple docstring'''

import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
		_A				:    List[str]     						='''pt'''
elif is_tf_available():
		_A				:    Tuple     						='''tf'''
else:
		_A				:    Optional[int]     						='''jax'''



class 		lowerCamelCase__      (						A	,   unittest.TestCase     ):




					'''simple docstring'''



					A_						    =						ByTaTokenizer
					A_						    =						False




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



						'''simple docstring'''





						super().setUp()
						_lowercase					:       Any       =		ByTaTokenizer()
						tokenizer.save_pretrained(self.tmpdirname					)




					@cached_property
					def 						__UpperCAmelCase     (  self				:	int					)  ->       int:



						'''simple docstring'''





						return ByTaTokenizer.from_pretrained('google/byt5-small'					)




					def 						__UpperCAmelCase     (  self				:	int     ,  **UpperCamelCase_				:	List[Any]					)  ->       ByTaTokenizer:



						'''simple docstring'''





						return self.tokenizer_class.from_pretrained(self.tmpdirname     ,  **UpperCamelCase_					)




					def 						__UpperCAmelCase     (  self				:	Optional[int]     ,  UpperCamelCase_				:	str     ,  UpperCamelCase_				:	Union[str, Any]=False     ,  UpperCamelCase_				:	Tuple=20     ,  UpperCamelCase_				:	Optional[int]=5					)  ->       Tuple[str, list]:



						'''simple docstring'''





						_lowercase					:       Dict       =		[]
						for i in range(len(UpperCamelCase_					)					):
							try:
								_lowercase					:       List[Any]       =		tokenizer.decode([i]     ,  clean_up_tokenization_spaces=UpperCamelCase_					)
							except UnicodeDecodeError:
								pass
							toks.append((i, tok)					)

						_lowercase					:       Optional[Any]       =		list(filter(lambda UpperCamelCase_					: re.match(r'^[ a-zA-Z]+$'     ,  t[1]					)     ,  UpperCamelCase_					)					)
						_lowercase					:       List[Any]       =		list(filter(lambda UpperCamelCase_					: [t[0]] == tokenizer.encode(t[1]     ,  add_special_tokens=UpperCamelCase_					)     ,  UpperCamelCase_					)					)
						if max_length is not None and len(UpperCamelCase_					) > max_length:
							_lowercase					:       List[Any]       =		toks[:max_length]
						if min_length is not None and len(UpperCamelCase_					) < min_length and len(UpperCamelCase_					) > 0:
							while len(UpperCamelCase_					) < min_length:
								_lowercase					:       Tuple       =		toks + toks
        # toks_str = [t[1] for t in toks]
						_lowercase					:       Dict       =		[t[0] for t in toks]

						# Ensure consistency
						_lowercase					:       Any       =		tokenizer.decode(UpperCamelCase_     ,  clean_up_tokenization_spaces=UpperCamelCase_					)
						if " " not in output_txt and len(UpperCamelCase_					) > 1:
							_lowercase					:       Any       =		(
							    tokenizer.decode([toks_ids[0]]     ,  clean_up_tokenization_spaces=UpperCamelCase_					)
							    + ' '
							    + tokenizer.decode(toks_ids[1:]     ,  clean_up_tokenization_spaces=UpperCamelCase_					)
							)
						if with_prefix_space:
							_lowercase					:       Union[str, Any]       =		' ' + output_txt
						_lowercase					:       int       =		tokenizer.encode(UpperCamelCase_     ,  add_special_tokens=UpperCamelCase_					)
						return output_txt, output_ids




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



						'''simple docstring'''





						_lowercase					:       List[str]       =		self.ta_base_tokenizer
						_lowercase					:       Union[str, Any]       =		tokenizer(['hi</s>', 'I went to the gym</s>', '</s>']					)
						_lowercase					:       Tuple       =		tokenizer(['hi', 'I went to the gym', '']					)
						self.assertListEqual(batch_with_eos_added['input_ids']     ,  batch_without_eos_added['input_ids']					)




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



						'''simple docstring'''





						_lowercase					:       Optional[int]       =		self.ta_base_tokenizer
						_lowercase					:       Tuple       =		'Unicode €.'
						_lowercase					:       List[Any]       =		tokenizer(UpperCamelCase_					)
						_lowercase					:       List[Any]       =		[88, 113, 108, 102, 114, 103, 104, 35, 229, 133, 175, 49, 1]
						self.assertEqual(encoded['input_ids']     ,  UpperCamelCase_					)

						# decoding
						_lowercase					:       List[str]       =		tokenizer.decode(UpperCamelCase_					)
						self.assertEqual(UpperCamelCase_     ,  'Unicode €.</s>'					)

						_lowercase					:       Any       =		tokenizer('e è é ê ë'					)
						_lowercase					:       Optional[int]       =		[104, 35, 198, 171, 35, 198, 172, 35, 198, 173, 35, 198, 174, 1]
						self.assertEqual(encoded['input_ids']     ,  UpperCamelCase_					)
						# decoding
						_lowercase					:       Tuple       =		tokenizer.decode(UpperCamelCase_					)
						self.assertEqual(UpperCamelCase_     ,  'e è é ê ë</s>'					)

						# encode/decode, but with `encode` instead of `__call__`
						self.assertEqual(tokenizer.decode(tokenizer.encode('e è é ê ë'					)					)     ,  'e è é ê ë</s>'					)




					def 						__UpperCAmelCase     (  self				:	Tuple					)  ->       List[str]:



						'''simple docstring'''





						_lowercase					:       List[Any]       =		self.ta_base_tokenizer
						_lowercase					:       int       =		['A long paragraph for summarization.', 'Another paragraph for summarization.']
						# fmt: off
						_lowercase					:       Any       =		[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 1, 0]
						# fmt: on
						_lowercase					:       Dict       =		tokenizer(UpperCamelCase_     ,  padding=UpperCamelCase_     ,  return_tensors=UpperCamelCase_					)
						self.assertIsInstance(UpperCamelCase_     ,  UpperCamelCase_					)

						if FRAMEWORK != "jax":
							_lowercase					:       Optional[Any]       =		list(batch.input_ids.numpy()[0]					)
						else:
							_lowercase					:       List[str]       =		list(batch.input_ids.tolist()[0]					)

						self.assertListEqual(UpperCamelCase_     ,  UpperCamelCase_					)

						self.assertEqual((2, 37)     ,  batch.input_ids.shape					)
						self.assertEqual((2, 37)     ,  batch.attention_mask.shape					)




					def 						__UpperCAmelCase     (  self				:	Optional[int]					)  ->       str:



						'''simple docstring'''





						_lowercase					:       Union[str, Any]       =		self.ta_base_tokenizer
						_lowercase					:       List[str]       =		['A long paragraph for summarization.', 'Another paragraph for summarization.']
						_lowercase					:       str       =		tokenizer(UpperCamelCase_     ,  padding=UpperCamelCase_     ,  return_tensors=UpperCamelCase_					)
						# check if input_ids are returned and no decoder_input_ids
						self.assertIn('input_ids'     ,  UpperCamelCase_					)
						self.assertIn('attention_mask'     ,  UpperCamelCase_					)
						self.assertNotIn('decoder_input_ids'     ,  UpperCamelCase_					)
						self.assertNotIn('decoder_attention_mask'     ,  UpperCamelCase_					)




					def 						__UpperCAmelCase     (  self				:	Any					)  ->       int:



						'''simple docstring'''





						_lowercase					:       Tuple       =		self.ta_base_tokenizer
						_lowercase					:       Optional[Any]       =		[
						    'Summary of the text.',
						    'Another summary.',
						]
						_lowercase					:       str       =		tokenizer(
						    text_target=UpperCamelCase_     ,  max_length=32     ,  padding='max_length'     ,  truncation=UpperCamelCase_     ,  return_tensors=UpperCamelCase_					)
						self.assertEqual(32     ,  targets['input_ids'].shape[1]					)




					def 						__UpperCAmelCase     (  self				:	Dict					)  ->       Tuple:



						'''simple docstring'''





						_lowercase					:       str       =		self.ta_base_tokenizer
						_lowercase					:       str       =		['A long paragraph for summarization. </s>']
						_lowercase					:       Optional[int]       =		['Summary of the text. </s>']
						# fmt: off
						_lowercase					:       Optional[Any]       =		[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 35, 1]
						_lowercase					:       Optional[Any]       =		[86, 120, 112, 112, 100, 117, 124, 35, 114, 105, 35, 119, 107, 104, 35, 119, 104, 123, 119, 49, 35, 1]
						# fmt: on

						_lowercase					:       Any       =		tokenizer(UpperCamelCase_     ,  text_target=UpperCamelCase_					)

						self.assertEqual(UpperCamelCase_     ,  batch['input_ids'][0]					)
						self.assertEqual(UpperCamelCase_     ,  batch['labels'][0]					)




					def 						__UpperCAmelCase     (  self				:	List[str]					)  ->       int:



						'''simple docstring'''





						_lowercase					:       Dict       =		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
						_lowercase					:       List[Any]       =		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
								_lowercase					:       List[Any]       =		tempfile.mkdtemp()

								_lowercase					:       Any       =		' He is very happy, UNwant\u00E9d,running'
								_lowercase					:       Union[str, Any]       =		tokenizer.encode(UpperCamelCase_     ,  add_special_tokens=UpperCamelCase_					)
								tokenizer.save_pretrained(UpperCamelCase_					)

								_lowercase					:       Optional[int]       =		tokenizer.__class__.from_pretrained(UpperCamelCase_					)
								_lowercase					:       Tuple       =		after_tokenizer.encode(UpperCamelCase_     ,  add_special_tokens=UpperCamelCase_					)
								self.assertListEqual(UpperCamelCase_     ,  UpperCamelCase_					)

								shutil.rmtree(UpperCamelCase_					)

						_lowercase					:       str       =		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
								_lowercase					:       Dict       =		tempfile.mkdtemp()

								_lowercase					:       List[Any]       =		' He is very happy, UNwant\u00E9d,running'
								tokenizer.add_tokens(['bim', 'bambam']					)
								_lowercase					:       Optional[int]       =		tokenizer.additional_special_tokens
								additional_special_tokens.append('new_additional_special_token'					)
								tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens}					)
								_lowercase					:       Optional[Any]       =		tokenizer.encode(UpperCamelCase_     ,  add_special_tokens=UpperCamelCase_					)
								tokenizer.save_pretrained(UpperCamelCase_					)

								_lowercase					:       List[str]       =		tokenizer.__class__.from_pretrained(UpperCamelCase_					)
								_lowercase					:       Dict       =		after_tokenizer.encode(UpperCamelCase_     ,  add_special_tokens=UpperCamelCase_					)
								self.assertListEqual(UpperCamelCase_     ,  UpperCamelCase_					)
								self.assertIn('new_additional_special_token'     ,  after_tokenizer.additional_special_tokens					)
								self.assertEqual(after_tokenizer.model_max_length     ,  42					)

								_lowercase					:       Dict       =		tokenizer.__class__.from_pretrained(UpperCamelCase_     ,  model_max_length=43					)
								self.assertEqual(tokenizer.model_max_length     ,  43					)

								shutil.rmtree(UpperCamelCase_					)




					def 						__UpperCAmelCase     (  self				:	List[str]					)  ->       Tuple:



						'''simple docstring'''





						_lowercase					:       List[Any]       =		[]
						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(UpperCamelCase_					)

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

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

								_lowercase					:       List[Any]       =		[F'''<extra_id_{i}>''' for i in range(125					)]

								_lowercase					:       Any       =		added_tokens_extra_ids + [
								    'an_additional_special_token'
								]
								_lowercase					:       int       =		added_tokens_extra_ids + [
								    'an_additional_special_token'
								]

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

								# 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
								_lowercase					:       Optional[Any]       =		tokenizer_class.from_pretrained(
								    UpperCamelCase_     ,  )
								self.assertIn(
								    'an_additional_special_token'     ,  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(
								    ['an_additional_special_token']     ,  tokenizer_without_change_in_init.convert_ids_to_tokens(
								        tokenizer_without_change_in_init.convert_tokens_to_ids(['an_additional_special_token']					)					)     ,  )

								# Now we test that we can change the value of additional_special_tokens in the from_pretrained
								_lowercase					:       List[str]       =		added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'     ,  lstrip=UpperCamelCase_					)]
								_lowercase					:       Tuple       =		tokenizer_class.from_pretrained(
								    UpperCamelCase_     ,  additional_special_tokens=UpperCamelCase_     ,  )

								self.assertIn('a_new_additional_special_token'     ,  tokenizer.additional_special_tokens					)
								self.assertEqual(
								    ['a_new_additional_special_token']     ,  tokenizer.convert_ids_to_tokens(
								        tokenizer.convert_tokens_to_ids(['a_new_additional_special_token']					)					)     ,  )




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



						'''simple docstring'''





						_lowercase					:       Union[str, Any]       =		[]
						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(UpperCamelCase_					)

								_lowercase					:       str       =		tokenizer_class.from_pretrained(UpperCamelCase_					)

								self.assertTrue(tokenizer.decode([255]					) == ''					)




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



						'''simple docstring'''





						pass




					def 						__UpperCAmelCase     (  self				:	str					)  ->       Tuple:



						'''simple docstring'''





						pass




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



						'''simple docstring'''





						pass




					def 						__UpperCAmelCase     (  self				:	List[Any]					)  ->       int:



						'''simple docstring'''





						pass




					def 						__UpperCAmelCase     (  self				:	List[str]					)  ->       Optional[Any]:



						'''simple docstring'''





						_lowercase					:       Optional[Any]       =		self.get_tokenizers(fast=UpperCamelCase_     ,  do_lower_case=UpperCamelCase_					)
						for tokenizer in tokenizers:
							with self.subTest(F'''{tokenizer.__class__.__name__}'''					):
								_lowercase					:       Any       =		['t', 'h', 'i', 's', ' ', 'i', 's', ' ', 'a', ' ', 't', 'e', 'x', 't', '</s>']
								_lowercase					:       Tuple       =		tokenizer.convert_tokens_to_string(UpperCamelCase_					)

								self.assertIsInstance(UpperCamelCase_     ,  UpperCamelCase_					)




					def 						__UpperCAmelCase     (  self				:	List[Any]					)  ->       str:



						'''simple docstring'''





						_lowercase					:       Dict       =		self.get_tokenizers()
						for tokenizer in tokenizers:
							with self.subTest(F'''{tokenizer.__class__.__name__}'''					):
								_lowercase					:       Optional[int]       =		[
								    'bos_token',
								    'eos_token',
								    'unk_token',
								    'sep_token',
								    'pad_token',
								    'cls_token',
								    'mask_token',
								]

								_lowercase					:       Optional[int]       =		0
								_lowercase					:       int       =		tokenizer.convert_ids_to_tokens(
								    UpperCamelCase_     ,  skip_special_tokens=UpperCamelCase_					)

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

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

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

								setattr(UpperCamelCase_     ,  'additional_special_tokens_ids'     ,  [token_id_to_test_setters]					)
								self.assertListEqual(getattr(UpperCamelCase_     ,  'additional_special_tokens'					)     ,  [token_to_test_setters]					)
								self.assertListEqual(getattr(UpperCamelCase_     ,  'additional_special_tokens_ids'					)     ,  [token_id_to_test_setters]					)
