

'''simple docstring'''


import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin




class     a			(				SCREAMING_SNAKE_CASE			,			unittest.TestCase       ):






						"""simple docstring"""




						__UpperCAmelCase			     =    CanineTokenizer
						__UpperCAmelCase			     =    False







						def       __magic_name__							(							self					:      List[Any]  ):



								'''simple docstring'''



								super().setUp()
								snake_case__						:       str       						=  CanineTokenizer()
								tokenizer.save_pretrained(self.tmpdirname  )







						@cached_property
						def       __magic_name__							(							self					:      Union[str, Any]  ):



								'''simple docstring'''



								return CanineTokenizer.from_pretrained('''google/canine-s'''  )







						def       __magic_name__							(							self					:      Union[str, Any]			,			**snake_case_					:      Optional[int]  ):



								'''simple docstring'''



								snake_case__						:       Tuple       						=  self.tokenizer_class.from_pretrained(self.tmpdirname			,			**snake_case_  )
								snake_case__						:       Any       						=  1_0_2_4
								return tokenizer







						@require_torch
						def       __magic_name__							(							self					:      str  ):



								'''simple docstring'''



								snake_case__						:       Any       						=  self.canine_tokenizer
								snake_case__						:       Dict       						=  ['''Life is like a box of chocolates.''', '''You never know what you\'re gonna get.''']
								# fmt: off
								snake_case__						:       List[str]       						=  [5_7_3_4_4, 7_6, 1_0_5, 1_0_2, 1_0_1, 3_2, 1_0_5, 1_1_5, 3_2, 1_0_8, 1_0_5, 1_0_7, 1_0_1, 3_2, 9_7, 3_2, 9_8, 1_1_1, 1_2_0, 3_2, 1_1_1, 1_0_2, 3_2, 9_9, 1_0_4, 1_1_1, 9_9, 1_1_1, 1_0_8, 9_7, 1_1_6, 1_0_1, 1_1_5, 4_6, 5_7_3_4_5, 0, 0, 0, 0]
								# fmt: on
								snake_case__						:       Dict       						=  tokenizer(snake_case_			,			padding=snake_case_			,			return_tensors='''pt'''  )
								self.assertIsInstance(snake_case_			,			snake_case_  )

								snake_case__						:       Any       						=  list(batch.input_ids.numpy()[0]  )

								self.assertListEqual(snake_case_			,			snake_case_  )

								self.assertEqual((2, 3_9)			,			batch.input_ids.shape  )
								self.assertEqual((2, 3_9)			,			batch.attention_mask.shape  )







						@require_torch
						def       __magic_name__							(							self					:      Union[str, Any]  ):



								'''simple docstring'''



								snake_case__						:       int       						=  self.canine_tokenizer
								snake_case__						:       int       						=  ['''Once there was a man.''', '''He wrote a test in HuggingFace Tranformers.''']
								snake_case__						:       Dict       						=  tokenizer(snake_case_			,			padding=snake_case_			,			return_tensors='''pt'''  )
								# check if input_ids, attention_mask and token_type_ids are returned
								self.assertIn('''input_ids'''			,			snake_case_  )
								self.assertIn('''attention_mask'''			,			snake_case_  )
								self.assertIn('''token_type_ids'''			,			snake_case_  )







						@require_torch
						def       __magic_name__							(							self					:      int  ):



								'''simple docstring'''



								snake_case__						:       int       						=  self.canine_tokenizer
								snake_case__						:       str       						=  [
								    '''What\'s the weater?''',
								    '''It\'s about 25 degrees.''',
								]
								snake_case__						:       List[Any]       						=  tokenizer(
								    text_target=snake_case_			,			max_length=3_2			,			padding='''max_length'''			,			truncation=snake_case_			,			return_tensors='''pt'''  )
								self.assertEqual(3_2			,			targets['''input_ids'''].shape[1]  )







						def       __magic_name__							(							self					:      Optional[int]  ):



								'''simple docstring'''



								snake_case__						:       List[str]       						=  self.get_tokenizers()
								for tokenizer in tokenizers:
										with self.subTest(F"""{tokenizer.__class__.__name__}"""  ):
												self.assertNotEqual(tokenizer.model_max_length			,			4_2  )

        # Now let's start the test
								snake_case__						:       List[str]       						=  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
												snake_case__						:       str       						=  tempfile.mkdtemp()

												snake_case__						:       Any       						=  ''' He is very happy, UNwant\u00E9d,running'''
												snake_case__						:       str       						=  tokenizer.encode(snake_case_			,			add_special_tokens=snake_case_  )
												tokenizer.save_pretrained(snake_case_  )

												snake_case__						:       Dict       						=  tokenizer.__class__.from_pretrained(snake_case_  )
												snake_case__						:       List[str]       						=  after_tokenizer.encode(snake_case_			,			add_special_tokens=snake_case_  )
												self.assertListEqual(snake_case_			,			snake_case_  )

												shutil.rmtree(snake_case_  )

								snake_case__						:       int       						=  self.get_tokenizers(model_max_length=4_2  )
								for tokenizer in tokenizers:
										with self.subTest(F"""{tokenizer.__class__.__name__}"""  ):
												# Isolate this from the other tests because we save additional tokens/etc
												snake_case__						:       List[str]       						=  tempfile.mkdtemp()

												snake_case__						:       Any       						=  ''' He is very happy, UNwant\u00E9d,running'''

												snake_case__						:       Dict       						=  tokenizer.additional_special_tokens

												# We can add a new special token for Canine as follows:
												snake_case__						:       Tuple       						=  chr(0xE007  )
												additional_special_tokens.append(snake_case_  )
												tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}  )
												snake_case__						:       Tuple       						=  tokenizer.encode(snake_case_			,			add_special_tokens=snake_case_  )
												tokenizer.save_pretrained(snake_case_  )

												snake_case__						:       List[Any]       						=  tokenizer.__class__.from_pretrained(snake_case_  )
												snake_case__						:       str       						=  after_tokenizer.encode(snake_case_			,			add_special_tokens=snake_case_  )
												self.assertListEqual(snake_case_			,			snake_case_  )
												self.assertIn(snake_case_			,			after_tokenizer.additional_special_tokens  )
												self.assertEqual(after_tokenizer.model_max_length			,			4_2  )

												snake_case__						:       List[Any]       						=  tokenizer.__class__.from_pretrained(snake_case_			,			model_max_length=4_3  )
												self.assertEqual(tokenizer.model_max_length			,			4_3  )

												shutil.rmtree(snake_case_  )







						def       __magic_name__							(							self					:      Optional[Any]  ):



								'''simple docstring'''



								snake_case__						:       Dict       						=  self.get_tokenizers(do_lower_case=snake_case_  )
								for tokenizer in tokenizers:
										with self.subTest(F"""{tokenizer.__class__.__name__}"""  ):
												snake_case__						,       snake_case__						:       Dict       						=  self.get_clean_sequence(snake_case_  )

												# a special token for Canine can be defined as follows:
												snake_case__						:       Dict       						=  0xE005
												snake_case__						:       List[str]       						=  chr(snake_case_  )

												tokenizer.add_special_tokens({'''cls_token''': special_token}  )
												snake_case__						:       Optional[Any]       						=  tokenizer.encode(snake_case_			,			add_special_tokens=snake_case_  )
												self.assertEqual(len(snake_case_  )			,			1  )

												snake_case__						:       Any       						=  tokenizer.decode(ids + encoded_special_token			,			clean_up_tokenization_spaces=snake_case_  )
												snake_case__						:       Optional[int]       						=  tokenizer.encode(snake_case_			,			add_special_tokens=snake_case_  )

												snake_case__						:       Dict       						=  tokenizer.encode(snake_case_			,			add_special_tokens=snake_case_  )
												snake_case__						:       int       						=  tokenizer.encode(snake_case_			,			add_special_tokens=snake_case_  )
												self.assertEqual(snake_case_			,			input_encoded + special_token_id  )

												snake_case__						:       Any       						=  tokenizer.decode(snake_case_			,			skip_special_tokens=snake_case_  )
												self.assertTrue(special_token not in decoded  )







						def       __magic_name__							(							self					:      int  ):



								'''simple docstring'''



								snake_case__						:       Any       						=  self.get_tokenizers(do_lower_case=snake_case_  )
								for tokenizer in tokenizers:
										with self.subTest(F"""{tokenizer.__class__.__name__}"""  ):
												snake_case__						:       List[str]       						=  chr(0xE005  )
												snake_case__						:       Optional[int]       						=  chr(0xE006  )

												# `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
												tokenizer.add_tokens([SPECIAL_TOKEN_1]			,			special_tokens=snake_case_  )
												# `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
												# which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
												tokenizer.add_special_tokens({'''additional_special_tokens''': [SPECIAL_TOKEN_2]}  )

												snake_case__						:       List[Any]       						=  tokenizer.tokenize(snake_case_  )
												snake_case__						:       Any       						=  tokenizer.tokenize(snake_case_  )

												self.assertEqual(len(snake_case_  )			,			1  )
												self.assertEqual(len(snake_case_  )			,			1  )
												self.assertEqual(token_a[0]			,			snake_case_  )
												self.assertEqual(token_a[0]			,			snake_case_  )







						@require_tokenizers
						def       __magic_name__							(							self					:      Union[str, Any]  ):



								'''simple docstring'''



								snake_case__						:       Optional[int]       						=  self.get_tokenizers(do_lower_case=snake_case_  )
								for tokenizer in tokenizers:
										with self.subTest(F"""{tokenizer.__class__.__name__}"""  ):
												# a special token for Canine can be defined as follows:
												snake_case__						:       Union[str, Any]       						=  0xE006
												snake_case__						:       Any       						=  chr(snake_case_  )

												snake_case__						:       Any       						=  AddedToken(snake_case_			,			lstrip=snake_case_  )
												tokenizer.add_special_tokens({'''additional_special_tokens''': [new_token]}  )

												with tempfile.TemporaryDirectory() as tmp_dir_name:
														tokenizer.save_pretrained(snake_case_  )
														tokenizer.from_pretrained(snake_case_  )







						def       __magic_name__							(							self					:      Tuple  ):



								'''simple docstring'''



								snake_case__						:       List[str]       						=  []
								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(snake_case_  )

												with open(os.path.join(snake_case_			,			'''special_tokens_map.json'''  )			,			encoding='''utf-8'''  ) as json_file:
														snake_case__						:       Union[str, Any]       						=  json.load(snake_case_  )

												with open(os.path.join(snake_case_			,			'''tokenizer_config.json'''  )			,			encoding='''utf-8'''  ) as json_file:
														snake_case__						:       List[Any]       						=  json.load(snake_case_  )

												# a special token for Canine can be defined as follows:
												snake_case__						:       Optional[Any]       						=  0xE006
												snake_case__						:       List[Any]       						=  chr(snake_case_  )

												snake_case__						:       List[str]       						=  [new_token_a]
												snake_case__						:       int       						=  [new_token_a]

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

												# 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
												snake_case__						:       Dict       						=  tokenizer_class.from_pretrained(snake_case_			,			extra_ids=0  )
												self.assertIn(snake_case_			,			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(
												    [new_token_a]			,			tokenizer_without_change_in_init.convert_ids_to_tokens(
												        tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]  )  )			,			)

												snake_case__						:       str       						=  0xE007
												snake_case__						:       Dict       						=  chr(snake_case_  )
												# Now we test that we can change the value of additional_special_tokens in the from_pretrained
												snake_case__						:       Tuple       						=  [AddedToken(snake_case_			,			lstrip=snake_case_  )]
												snake_case__						:       Optional[int]       						=  tokenizer_class.from_pretrained(
												    snake_case_			,			additional_special_tokens=snake_case_			,			extra_ids=0  )

												self.assertIn(snake_case_			,			tokenizer.additional_special_tokens  )
												# self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
												self.assertEqual(
												    [new_token_a]			,			tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]  )  )  )







						@require_tokenizers
						def       __magic_name__							(							self					:      Optional[Any]  ):



								'''simple docstring'''



								snake_case__						:       Any       						=  self.get_tokenizers(do_lower_case=snake_case_  )
								for tokenizer in tokenizers:
										with self.subTest(F"""{tokenizer.__class__.__name__}"""  ):
												snake_case__						:       str       						=  '''hello world'''
												if self.space_between_special_tokens:
														snake_case__						:       int       						=  '''[CLS] hello world [SEP]'''
												else:
														snake_case__						:       List[str]       						=  input
												snake_case__						:       Optional[Any]       						=  tokenizer.encode(snake_case_			,			add_special_tokens=snake_case_  )
												snake_case__						:       Optional[int]       						=  tokenizer.decode(snake_case_			,			spaces_between_special_tokens=self.space_between_special_tokens  )
												self.assertIn(snake_case_			,			[output, output.lower()]  )







						def       __magic_name__							(							self					:      Optional[Any]  ):



								'''simple docstring'''



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

								snake_case__						:       Tuple       						=  '''a'''
								snake_case__						:       List[str]       						=  ord(snake_case_  )

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

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

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

								snake_case__						:       Any       						=  0xE006
								snake_case__						:       List[Any]       						=  chr(snake_case_  )
								setattr(snake_case_			,			'''additional_special_tokens_ids'''			,			[additional_special_token_id]  )
								self.assertListEqual(getattr(snake_case_			,			'''additional_special_tokens'''  )			,			[additional_special_token]  )
								self.assertListEqual(getattr(snake_case_			,			'''additional_special_tokens_ids'''  )			,			[additional_special_token_id]  )







						def       __magic_name__							(							self					:      str  ):



								'''simple docstring'''



								pass







						def       __magic_name__							(							self					:      str  ):



								'''simple docstring'''



								pass







						def       __magic_name__							(							self					:      List[str]  ):



								'''simple docstring'''



								pass







						def       __magic_name__							(							self					:      List[Any]  ):



								'''simple docstring'''



								pass







						def       __magic_name__							(							self					:      List[Any]  ):



								'''simple docstring'''



								pass







						def       __magic_name__							(							self					:      List[Any]  ):



								'''simple docstring'''



								pass







						def       __magic_name__							(							self					:      Union[str, Any]  ):



								'''simple docstring'''



								pass







						def       __magic_name__							(							self					:      Dict  ):



								'''simple docstring'''



								pass






'''simple docstring'''


def 	_a       (				__lowerCAmelCase		:      int     ):

		"""simple docstring"""

		if p < 2:
				raise ValueError('''p should not be less than 2!'''     )
		elif p == 2:
				return True

		snake_case__						:       Any       						=  4
		snake_case__						:       int       						=  (1 << p) - 1
		for _ in range(p - 2     ):
				snake_case__						:       Tuple       						=  ((s * s) - 2) % m
		return s == 0


if __name__ == "__main__":
					print(lucas_lehmer_test(7))
					print(lucas_lehmer_test(11))



