import random

import torch
from huggingface_hub import HfApi

from diffusers import UNetaDModel


__lowerCamelCase					:	List[str]       =  HfApi()

__lowerCamelCase					:	Union[str, Any]       =  {}
# fmt: off
__lowerCamelCase					:	Any       =  torch.tensor([
    -0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.1743, -3.7467,
    1.2342, -2.2485, 0.4636, 0.8076, -0.7991, 0.3969, 0.8498, 0.9189,
    -1.8887, -3.3522, 0.7639, 0.2040, 0.6271, -2.7148, -1.6316, 3.0839,
    0.3186, 0.2721, -0.9759, -1.2461, 2.6257, 1.3557
])
__lowerCamelCase					:	Dict       =  torch.tensor([
    -2.3639, -2.5344, 0.0054, -0.6674, 1.5990, 1.0158, 0.3124, -2.1436,
    1.8795, -2.5429, -0.1566, -0.3973, 1.2490, 2.6447, 1.2283, -0.5208,
    -2.8154, -3.5119, 2.3838, 1.2033, 1.7201, -2.1256, -1.4576, 2.7948,
    2.4204, -0.9752, -1.2546, 0.8027, 3.2758, 3.1365
])
__lowerCamelCase					:	int       =  torch.tensor([
    -0.6531, -0.6891, -0.3172, -0.5375, -0.9140, -0.5367, -0.1175, -0.7869,
    -0.3808, -0.4513, -0.2098, -0.0083, 0.3183, 0.5140, 0.2247, -0.1304,
    -0.1302, -0.2802, -0.2084, -0.2025, -0.4967, -0.4873, -0.0861, 0.6925,
    0.0250, 0.1290, -0.1543, 0.6316, 1.0460, 1.4943
])
__lowerCamelCase					:	Optional[int]       =  torch.tensor([
    0.0911, 0.1107, 0.0182, 0.0435, -0.0805, -0.0608, 0.0381, 0.2172,
    -0.0280, 0.1327, -0.0299, -0.0255, -0.0050, -0.1170, -0.1046, 0.0309,
    0.1367, 0.1728, -0.0533, -0.0748, -0.0534, 0.1624, 0.0384, -0.1805,
    -0.0707, 0.0642, 0.0220, -0.0134, -0.1333, -0.1505
])
__lowerCamelCase					:	List[Any]       =  torch.tensor([
    0.1321, 0.1337, 0.0440, 0.0622, -0.0591, -0.0370, 0.0503, 0.2133,
    -0.0177, 0.1415, -0.0116, -0.0112, 0.0044, -0.0980, -0.0789, 0.0395,
    0.1502, 0.1785, -0.0488, -0.0514, -0.0404, 0.1539, 0.0454, -0.1559,
    -0.0665, 0.0659, 0.0383, -0.0005, -0.1266, -0.1386
])
__lowerCamelCase					:	Tuple       =  torch.tensor([
    0.1154, 0.1218, 0.0307, 0.0526, -0.0711, -0.0541, 0.0366, 0.2078,
    -0.0267, 0.1317, -0.0226, -0.0193, -0.0014, -0.1055, -0.0902, 0.0330,
    0.1391, 0.1709, -0.0562, -0.0693, -0.0560, 0.1482, 0.0381, -0.1683,
    -0.0681, 0.0661, 0.0331, -0.0046, -0.1268, -0.1431
])
__lowerCamelCase					:	Any       =  torch.tensor([
    0.1192, 0.1240, 0.0414, 0.0606, -0.0557, -0.0412, 0.0430, 0.2042,
    -0.0200, 0.1385, -0.0115, -0.0132, 0.0017, -0.0965, -0.0802, 0.0398,
    0.1433, 0.1747, -0.0458, -0.0533, -0.0407, 0.1545, 0.0419, -0.1574,
    -0.0645, 0.0626, 0.0341, -0.0010, -0.1199, -0.1390
])
__lowerCamelCase					:	Any       =  torch.tensor([
    0.1075, 0.1074, 0.0205, 0.0431, -0.0774, -0.0607, 0.0298, 0.2042,
    -0.0320, 0.1267, -0.0281, -0.0250, -0.0064, -0.1091, -0.0946, 0.0290,
    0.1328, 0.1650, -0.0580, -0.0738, -0.0586, 0.1440, 0.0337, -0.1746,
    -0.0712, 0.0605, 0.0250, -0.0099, -0.1316, -0.1473
])
__lowerCamelCase					:	Optional[Any]       =  torch.tensor([
    -1.4572, -2.0481, -0.0414, -0.6005, 1.4136, 0.5848, 0.4028, -2.7330,
    1.2212, -2.1228, 0.2155, 0.4039, 0.7662, 2.0535, 0.7477, -0.3243,
    -2.1758, -2.7648, 1.6947, 0.7026, 1.2338, -1.6078, -0.8682, 2.2810,
    1.8574, -0.5718, -0.5586, -0.0186, 2.3415, 2.1251])
__lowerCamelCase					:	Tuple       =  torch.tensor([
    -1.3690, -1.9720, -0.4090, -0.6966, 1.4660, 0.9938, -0.1385, -2.7324,
    0.7736, -1.8917, 0.2923, 0.4293, 0.1693, 1.4112, 1.1887, -0.3181,
    -2.2160, -2.6381, 1.3170, 0.8163, 0.9240, -1.6544, -0.6099, 2.5259,
    1.6430, -0.9090, -0.9392, -0.0126, 2.4268, 2.3266
])
__lowerCamelCase					:	List[str]       =  torch.tensor([
    -1.3525, -1.9628, -0.3956, -0.6860, 1.4664, 1.0014, -0.1259, -2.7212,
    0.7772, -1.8811, 0.2996, 0.4388, 0.1704, 1.4029, 1.1701, -0.3027,
    -2.2053, -2.6287, 1.3350, 0.8131, 0.9274, -1.6292, -0.6098, 2.5131,
    1.6505, -0.8958, -0.9298, -0.0151, 2.4257, 2.3355
])
__lowerCamelCase					:	List[str]       =  torch.tensor([
    -2.0585, -2.7897, -0.2850, -0.8940, 1.9052, 0.5702, 0.6345, -3.8959,
    1.5932, -3.2319, 0.1974, 0.0287, 1.7566, 2.6543, 0.8387, -0.5351,
    -3.2736, -4.3375, 2.9029, 1.6390, 1.4640, -2.1701, -1.9013, 2.9341,
    3.4981, -0.6255, -1.1644, -0.1591, 3.7097, 3.2066
])
__lowerCamelCase					:	Any       =  torch.tensor([
    -2.3139, -2.5594, -0.0197, -0.6785, 1.7001, 1.1606, 0.3075, -2.1740,
    1.8071, -2.5630, -0.0926, -0.3811, 1.2116, 2.6246, 1.2731, -0.5398,
    -2.8153, -3.6140, 2.3893, 1.3262, 1.6258, -2.1856, -1.3267, 2.8395,
    2.3779, -1.0623, -1.2468, 0.8959, 3.3367, 3.2243
])
__lowerCamelCase					:	Dict       =  torch.tensor([
    -2.0628, -2.7667, -0.2089, -0.8263, 2.0539, 0.5992, 0.6495, -3.8336,
    1.6025, -3.2817, 0.1721, -0.0633, 1.7516, 2.7039, 0.8100, -0.5908,
    -3.2113, -4.4343, 2.9257, 1.3632, 1.5562, -2.1489, -1.9894, 3.0560,
    3.3396, -0.7328, -1.0417, 0.0383, 3.7093, 3.2343
])
__lowerCamelCase					:	List[str]       =  torch.tensor([
    -1.4574, -2.0569, -0.0473, -0.6117, 1.4018, 0.5769, 0.4129, -2.7344,
    1.2241, -2.1397, 0.2000, 0.3937, 0.7616, 2.0453, 0.7324, -0.3391,
    -2.1746, -2.7744, 1.6963, 0.6921, 1.2187, -1.6172, -0.8877, 2.2439,
    1.8471, -0.5839, -0.5605, -0.0464, 2.3250, 2.1219
])
# fmt: on

__lowerCamelCase					:	str       =  api.list_models(filter='''diffusers''')
for mod in models:
		if "google" in mod.author or mod.modelId == "CompVis/ldm-celebahq-256":
				__lowerCamelCase					:	Optional[int]       =  '''/home/patrick/google_checkpoints/''' + mod.modelId.split('''/''')[-1]

				print(f'''Started running {mod.modelId}!!!''')

				if mod.modelId.startswith('''CompVis'''):
						__lowerCamelCase					:	List[str]       =  UNetaDModel.from_pretrained(local_checkpoint, subfolder='''unet''')
				else:
						__lowerCamelCase					:	Any       =  UNetaDModel.from_pretrained(local_checkpoint)

				torch.manual_seed(0)
				random.seed(0)

				__lowerCamelCase					:	Union[str, Any]       =  torch.randn(1, model.config.in_channels, model.config.sample_size, model.config.sample_size)
				__lowerCamelCase					:	str       =  torch.tensor([10] * noise.shape[0])
				with torch.no_grad():
						__lowerCamelCase					:	List[Any]       =  model(noise, time_step).sample

				assert torch.allclose(
				    logits[0, 0, 0, :30], results['''_'''.join('''_'''.join(mod.modelId.split('''/''')).split('''-'''))], atol=1E-3
				)
				print(f'''{mod.modelId} has passed successfully!!!''')

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  :     Tuple       =  """pt"""
elif is_tf_available():
		__a  :     int       =  """tf"""
else:
		__a  :     Tuple       =  """jax"""




class    _UpperCamelCase      (						_UpperCAmelCase						,unittest.TestCase ):


			"""simple docstring"""






			__a  : List[Any]			 =						ByTaTokenizer
			__a  : str			 =						False





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

							'''simple docstring'''


							super().setUp()
							__lowercase 			=							ByTaTokenizer()
							tokenizer.save_pretrained(self.tmpdirname						)





			@cached_property
			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Any:

							'''simple docstring'''


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





			def        _SCREAMING_SNAKE_CASE			(   self      ,   **lowerCAmelCase__						)     ->					ByTaTokenizer:

							'''simple docstring'''


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





			def        _SCREAMING_SNAKE_CASE			(   self      ,   lowerCAmelCase__      ,   lowerCAmelCase__=False      ,   lowerCAmelCase__=20      ,   lowerCAmelCase__=5						)     ->					Tuple[str, list]:

							'''simple docstring'''


							__lowercase 			=							[]
							for i in range(len(lowerCAmelCase__						)						):
											try:
															__lowercase 			=							tokenizer.decode([i]      ,   clean_up_tokenization_spaces=lowerCAmelCase__						)
											except UnicodeDecodeError:
															pass
											toks.append((i, tok)						)

							__lowercase 			=							list(filter(lambda lowerCAmelCase__						: re.match(R'''^[ a-zA-Z]+$'''      ,   t[1]						)      ,   lowerCAmelCase__						)						)
							__lowercase 			=							list(filter(lambda lowerCAmelCase__						: [t[0]] == tokenizer.encode(t[1]      ,   add_special_tokens=lowerCAmelCase__						)      ,   lowerCAmelCase__						)						)
							if max_length is not None and len(lowerCAmelCase__						) > max_length:
											__lowercase 			=							toks[:max_length]
							if min_length is not None and len(lowerCAmelCase__						) < min_length and len(lowerCAmelCase__						) > 0:
											while len(lowerCAmelCase__						) < min_length:
															__lowercase 			=							toks + toks
        # toks_str = [t[1] for t in toks]
							__lowercase 			=							[t[0] for t in toks]

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





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Tuple:

							'''simple docstring'''


							__lowercase 			=							self.ta_base_tokenizer
							__lowercase 			=							tokenizer(['''hi</s>''', '''I went to the gym</s>''', '''</s>''']						)
							__lowercase 			=							tokenizer(['''hi''', '''I went to the gym''', '''''']						)
							self.assertListEqual(batch_with_eos_added['''input_ids''']      ,   batch_without_eos_added['''input_ids''']						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Dict:

							'''simple docstring'''


							__lowercase 			=							self.ta_base_tokenizer
							__lowercase 			=							'''Unicode €.'''
							__lowercase 			=							tokenizer(lowerCAmelCase__						)
							__lowercase 			=							[88, 1_13, 1_08, 1_02, 1_14, 1_03, 1_04, 35, 2_29, 1_33, 1_75, 49, 1]
							self.assertEqual(encoded['''input_ids''']      ,   lowerCAmelCase__						)

							# decoding
							__lowercase 			=							tokenizer.decode(lowerCAmelCase__						)
							self.assertEqual(lowerCAmelCase__      ,   '''Unicode €.</s>'''						)

							__lowercase 			=							tokenizer('''e è é ê ë'''						)
							__lowercase 			=							[1_04, 35, 1_98, 1_71, 35, 1_98, 1_72, 35, 1_98, 1_73, 35, 1_98, 1_74, 1]
							self.assertEqual(encoded['''input_ids''']      ,   lowerCAmelCase__						)
							# decoding
							__lowercase 			=							tokenizer.decode(lowerCAmelCase__						)
							self.assertEqual(lowerCAmelCase__      ,   '''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        _SCREAMING_SNAKE_CASE			(   self						)     ->					List[Any]:

							'''simple docstring'''


							__lowercase 			=							self.ta_base_tokenizer
							__lowercase 			=							['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
							# fmt: off
							__lowercase 			=							[68, 35, 1_11, 1_14, 1_13, 1_06, 35, 1_15, 1_00, 1_17, 1_00, 1_06, 1_17, 1_00, 1_15, 1_07, 35, 1_05, 1_14, 1_17, 35, 1_18, 1_20, 1_12, 1_12, 1_00, 1_17, 1_08, 1_25, 1_00, 1_19, 1_08, 1_14, 1_13, 49, 1, 0]
							# fmt: on
							__lowercase 			=							tokenizer(lowerCAmelCase__      ,   padding=lowerCAmelCase__      ,   return_tensors=lowerCAmelCase__						)
							self.assertIsInstance(lowerCAmelCase__      ,   lowerCAmelCase__						)

							if FRAMEWORK != "jax":
											__lowercase 			=							list(batch.input_ids.numpy()[0]						)
							else:
											__lowercase 			=							list(batch.input_ids.tolist()[0]						)

							self.assertListEqual(lowerCAmelCase__      ,   lowerCAmelCase__						)

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





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					int:

							'''simple docstring'''


							__lowercase 			=							self.ta_base_tokenizer
							__lowercase 			=							['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
							__lowercase 			=							tokenizer(lowerCAmelCase__      ,   padding=lowerCAmelCase__      ,   return_tensors=lowerCAmelCase__						)
							# check if input_ids are returned and no decoder_input_ids
							self.assertIn('''input_ids'''      ,   lowerCAmelCase__						)
							self.assertIn('''attention_mask'''      ,   lowerCAmelCase__						)
							self.assertNotIn('''decoder_input_ids'''      ,   lowerCAmelCase__						)
							self.assertNotIn('''decoder_attention_mask'''      ,   lowerCAmelCase__						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Tuple:

							'''simple docstring'''


							__lowercase 			=							self.ta_base_tokenizer
							__lowercase 			=							[
							    '''Summary of the text.''',
							    '''Another summary.''',
							]
							__lowercase 			=							tokenizer(
							    text_target=lowerCAmelCase__      ,   max_length=32      ,   padding='''max_length'''      ,   truncation=lowerCAmelCase__      ,   return_tensors=lowerCAmelCase__						)
							self.assertEqual(32      ,   targets['''input_ids'''].shape[1]						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					int:

							'''simple docstring'''


							__lowercase 			=							self.ta_base_tokenizer
							__lowercase 			=							['''A long paragraph for summarization. </s>''']
							__lowercase 			=							['''Summary of the text. </s>''']
							# fmt: off
							__lowercase 			=							[68, 35, 1_11, 1_14, 1_13, 1_06, 35, 1_15, 1_00, 1_17, 1_00, 1_06, 1_17, 1_00, 1_15, 1_07, 35, 1_05, 1_14, 1_17, 35, 1_18, 1_20, 1_12, 1_12, 1_00, 1_17, 1_08, 1_25, 1_00, 1_19, 1_08, 1_14, 1_13, 49, 35, 1]
							__lowercase 			=							[86, 1_20, 1_12, 1_12, 1_00, 1_17, 1_24, 35, 1_14, 1_05, 35, 1_19, 1_07, 1_04, 35, 1_19, 1_04, 1_23, 1_19, 49, 35, 1]
							# fmt: on

							__lowercase 			=							tokenizer(lowerCAmelCase__      ,   text_target=lowerCAmelCase__						)

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





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

							'''simple docstring'''


							__lowercase 			=							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 			=							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 			=							tempfile.mkdtemp()

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

															__lowercase 			=							tokenizer.__class__.from_pretrained(lowerCAmelCase__						)
															__lowercase 			=							after_tokenizer.encode(lowerCAmelCase__      ,   add_special_tokens=lowerCAmelCase__						)
															self.assertListEqual(lowerCAmelCase__      ,   lowerCAmelCase__						)

															shutil.rmtree(lowerCAmelCase__						)

							__lowercase 			=							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 			=							tempfile.mkdtemp()

															__lowercase 			=							''' He is very happy, UNwant\u00E9d,running'''
															tokenizer.add_tokens(['''bim''', '''bambam''']						)
															__lowercase 			=							tokenizer.additional_special_tokens
															additional_special_tokens.append('''new_additional_special_token'''						)
															tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}						)
															__lowercase 			=							tokenizer.encode(lowerCAmelCase__      ,   add_special_tokens=lowerCAmelCase__						)
															tokenizer.save_pretrained(lowerCAmelCase__						)

															__lowercase 			=							tokenizer.__class__.from_pretrained(lowerCAmelCase__						)
															__lowercase 			=							after_tokenizer.encode(lowerCAmelCase__      ,   add_special_tokens=lowerCAmelCase__						)
															self.assertListEqual(lowerCAmelCase__      ,   lowerCAmelCase__						)
															self.assertIn('''new_additional_special_token'''      ,   after_tokenizer.additional_special_tokens						)
															self.assertEqual(after_tokenizer.model_max_length      ,   42						)

															__lowercase 			=							tokenizer.__class__.from_pretrained(lowerCAmelCase__      ,   model_max_length=43						)
															self.assertEqual(tokenizer.model_max_length      ,   43						)

															shutil.rmtree(lowerCAmelCase__						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Dict:

							'''simple docstring'''


							__lowercase 			=							[]
							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(lowerCAmelCase__						)

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

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

															__lowercase 			=							[F"<extra_id_{i}>" for i in range(1_25						)]

															__lowercase 			=							added_tokens_extra_ids + [
															    '''an_additional_special_token'''
															]
															__lowercase 			=							added_tokens_extra_ids + [
															    '''an_additional_special_token'''
															]

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

															# 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 			=							tokenizer_class.from_pretrained(
															    lowerCAmelCase__      ,   )
															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 			=							added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''      ,   lstrip=lowerCAmelCase__						)]
															__lowercase 			=							tokenizer_class.from_pretrained(
															    lowerCAmelCase__      ,   additional_special_tokens=lowerCAmelCase__      ,   )

															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        _SCREAMING_SNAKE_CASE			(   self						)     ->					List[str]:

							'''simple docstring'''


							__lowercase 			=							[]
							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(lowerCAmelCase__						)

															__lowercase 			=							tokenizer_class.from_pretrained(lowerCAmelCase__						)

															self.assertTrue(tokenizer.decode([2_55]						) == ''''''						)





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

							'''simple docstring'''


							pass





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

							'''simple docstring'''


							pass





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					int:

							'''simple docstring'''


							pass





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					str:

							'''simple docstring'''


							pass





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

							'''simple docstring'''


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

															self.assertIsInstance(lowerCAmelCase__      ,   lowerCAmelCase__						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					int:

							'''simple docstring'''


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

															__lowercase 			=							0
															__lowercase 			=							tokenizer.convert_ids_to_tokens(
															    lowerCAmelCase__      ,   skip_special_tokens=lowerCAmelCase__						)

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

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

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

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