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__							(       __snake_case				,						unittest.TestCase		):
			A__    :       Any        =      CanineTokenizer
			A__    :       Optional[Any]        =      False



			def __SCREAMING_SNAKE_CASE							(						self   )			->   List[str]:
								super().setUp()
								__a		 =       CanineTokenizer()
								tokenizer.save_pretrained(self.tmpdirname   )



			@cached_property
			def __SCREAMING_SNAKE_CASE							(						self   )			->   List[Any]:
								return CanineTokenizer.from_pretrained('google/canine-s'   )



			def __SCREAMING_SNAKE_CASE							(						self				,						**UpperCAmelCase   )			->   CanineTokenizer:
								__a		 =       self.tokenizer_class.from_pretrained(self.tmpdirname				,						**UpperCAmelCase   )
								__a		 =       1_0_2_4
								return tokenizer



			@require_torch
			def __SCREAMING_SNAKE_CASE							(						self   )			->   Dict:
								__a		 =       self.canine_tokenizer
								__a		 =       ['Life is like a box of chocolates.', 'You never know what you\'re gonna get.']
								# fmt: off
								__a		 =       [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
								__a		 =       tokenizer(UpperCAmelCase				,						padding=UpperCAmelCase				,						return_tensors='pt'   )
								self.assertIsInstance(UpperCAmelCase				,						UpperCAmelCase   )

								__a		 =       list(batch.input_ids.numpy()[0]   )

								self.assertListEqual(UpperCAmelCase				,						UpperCAmelCase   )

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



			@require_torch
			def __SCREAMING_SNAKE_CASE							(						self   )			->   int:
								__a		 =       self.canine_tokenizer
								__a		 =       ['Once there was a man.', 'He wrote a test in HuggingFace Tranformers.']
								__a		 =       tokenizer(UpperCAmelCase				,						padding=UpperCAmelCase				,						return_tensors='pt'   )
								# check if input_ids, attention_mask and token_type_ids are returned
								self.assertIn('input_ids'				,						UpperCAmelCase   )
								self.assertIn('attention_mask'				,						UpperCAmelCase   )
								self.assertIn('token_type_ids'				,						UpperCAmelCase   )



			@require_torch
			def __SCREAMING_SNAKE_CASE							(						self   )			->   Tuple:
								__a		 =       self.canine_tokenizer
								__a		 =       [
								    'What\'s the weater?',
								    'It\'s about 25 degrees.',
								]
								__a		 =       tokenizer(
								    text_target=UpperCAmelCase				,						max_length=3_2				,						padding='max_length'				,						truncation=UpperCAmelCase				,						return_tensors='pt'   )
								self.assertEqual(3_2				,						targets['input_ids'].shape[1]   )



			def __SCREAMING_SNAKE_CASE							(						self   )			->   Union[str, Any]:
								# safety check on max_len default value so we are sure the test works
								__a		 =       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
								__a		 =       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
																		__a		 =       tempfile.mkdtemp()

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

																		__a		 =       tokenizer.__class__.from_pretrained(UpperCAmelCase   )
																		__a		 =       after_tokenizer.encode(UpperCAmelCase				,						add_special_tokens=UpperCAmelCase   )
																		self.assertListEqual(UpperCAmelCase				,						UpperCAmelCase   )

																		shutil.rmtree(UpperCAmelCase   )

								__a		 =       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
																		__a		 =       tempfile.mkdtemp()

																		__a		 =       ' He is very happy, UNwant\u00E9d,running'

																		__a		 =       tokenizer.additional_special_tokens

																		# We can add a new special token for Canine as follows:
																		__a		 =       chr(0Xe007   )
																		additional_special_tokens.append(UpperCAmelCase   )
																		tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens}   )
																		__a		 =       tokenizer.encode(UpperCAmelCase				,						add_special_tokens=UpperCAmelCase   )
																		tokenizer.save_pretrained(UpperCAmelCase   )

																		__a		 =       tokenizer.__class__.from_pretrained(UpperCAmelCase   )
																		__a		 =       after_tokenizer.encode(UpperCAmelCase				,						add_special_tokens=UpperCAmelCase   )
																		self.assertListEqual(UpperCAmelCase				,						UpperCAmelCase   )
																		self.assertIn(UpperCAmelCase				,						after_tokenizer.additional_special_tokens   )
																		self.assertEqual(after_tokenizer.model_max_length				,						4_2   )

																		__a		 =       tokenizer.__class__.from_pretrained(UpperCAmelCase				,						model_max_length=4_3   )
																		self.assertEqual(tokenizer.model_max_length				,						4_3   )

																		shutil.rmtree(UpperCAmelCase   )



			def __SCREAMING_SNAKE_CASE							(						self   )			->   Optional[Any]:
								__a		 =       self.get_tokenizers(do_lower_case=UpperCAmelCase   )
								for tokenizer in tokenizers:
													with self.subTest(f'''{tokenizer.__class__.__name__}'''   ):
																		__a ,				__a		 =       self.get_clean_sequence(UpperCAmelCase   )

																		# a special token for Canine can be defined as follows:
																		__a		 =       0Xe005
																		__a		 =       chr(UpperCAmelCase   )

																		tokenizer.add_special_tokens({'cls_token': special_token}   )
																		__a		 =       tokenizer.encode(UpperCAmelCase				,						add_special_tokens=UpperCAmelCase   )
																		self.assertEqual(len(UpperCAmelCase   )				,						1   )

																		__a		 =       tokenizer.decode(ids + encoded_special_token				,						clean_up_tokenization_spaces=UpperCAmelCase   )
																		__a		 =       tokenizer.encode(UpperCAmelCase				,						add_special_tokens=UpperCAmelCase   )

																		__a		 =       tokenizer.encode(UpperCAmelCase				,						add_special_tokens=UpperCAmelCase   )
																		__a		 =       tokenizer.encode(UpperCAmelCase				,						add_special_tokens=UpperCAmelCase   )
																		self.assertEqual(UpperCAmelCase				,						input_encoded + special_token_id   )

																		__a		 =       tokenizer.decode(UpperCAmelCase				,						skip_special_tokens=UpperCAmelCase   )
																		self.assertTrue(special_token not in decoded   )



			def __SCREAMING_SNAKE_CASE							(						self   )			->   List[Any]:
								__a		 =       self.get_tokenizers(do_lower_case=UpperCAmelCase   )
								for tokenizer in tokenizers:
													with self.subTest(f'''{tokenizer.__class__.__name__}'''   ):
																		__a		 =       chr(0Xe005   )
																		__a		 =       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=UpperCAmelCase   )
																		# `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]}   )

																		__a		 =       tokenizer.tokenize(UpperCAmelCase   )
																		__a		 =       tokenizer.tokenize(UpperCAmelCase   )

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



			@require_tokenizers
			def __SCREAMING_SNAKE_CASE							(						self   )			->   List[Any]:
								__a		 =       self.get_tokenizers(do_lower_case=UpperCAmelCase   )
								for tokenizer in tokenizers:
													with self.subTest(f'''{tokenizer.__class__.__name__}'''   ):
																		# a special token for Canine can be defined as follows:
																		__a		 =       0Xe006
																		__a		 =       chr(UpperCAmelCase   )

																		__a		 =       AddedToken(UpperCAmelCase				,						lstrip=UpperCAmelCase   )
																		tokenizer.add_special_tokens({'additional_special_tokens': [new_token]}   )

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



			def __SCREAMING_SNAKE_CASE							(						self   )			->   Tuple:
								__a		 =       []
								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:
																							__a		 =       json.load(UpperCAmelCase   )

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

																		# a special token for Canine can be defined as follows:
																		__a		 =       0Xe006
																		__a		 =       chr(UpperCAmelCase   )

																		__a		 =       [new_token_a]
																		__a		 =       [new_token_a]

																		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
																		__a		 =       tokenizer_class.from_pretrained(UpperCAmelCase				,						extra_ids=0   )
																		self.assertIn(UpperCAmelCase				,						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]   )   )				,						)

																		__a		 =       0Xe007
																		__a		 =       chr(UpperCAmelCase   )
																		# Now we test that we can change the value of additional_special_tokens in the from_pretrained
																		__a		 =       [AddedToken(UpperCAmelCase				,						lstrip=UpperCAmelCase   )]
																		__a		 =       tokenizer_class.from_pretrained(
																		    UpperCAmelCase				,						additional_special_tokens=UpperCAmelCase				,						extra_ids=0   )

																		self.assertIn(UpperCAmelCase				,						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 __SCREAMING_SNAKE_CASE							(						self   )			->   Tuple:
								__a		 =       self.get_tokenizers(do_lower_case=UpperCAmelCase   )
								for tokenizer in tokenizers:
													with self.subTest(f'''{tokenizer.__class__.__name__}'''   ):
																		__a		 =       'hello world'
																		if self.space_between_special_tokens:
																							__a		 =       '[CLS] hello world [SEP]'
																		else:
																							__a		 =       input
																		__a		 =       tokenizer.encode(UpperCAmelCase				,						add_special_tokens=UpperCAmelCase   )
																		__a		 =       tokenizer.decode(UpperCAmelCase				,						spaces_between_special_tokens=self.space_between_special_tokens   )
																		self.assertIn(UpperCAmelCase				,						[output, output.lower()]   )



			def __SCREAMING_SNAKE_CASE							(						self   )			->   List[str]:
								__a		 =       self.get_tokenizers()
								for tokenizer in tokenizers:
													with self.subTest(f'''{tokenizer.__class__.__name__}'''   ):
																		__a		 =       [
																		    'bos_token',
																		    'eos_token',
																		    'unk_token',
																		    'sep_token',
																		    'pad_token',
																		    'cls_token',
																		    'mask_token',
																		]

								__a		 =       'a'
								__a		 =       ord(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'   )				,						[]   )

								__a		 =       0Xe006
								__a		 =       chr(UpperCAmelCase   )
								setattr(UpperCAmelCase				,						'additional_special_tokens_ids'				,						[additional_special_token_id]   )
								self.assertListEqual(getattr(UpperCAmelCase				,						'additional_special_tokens'   )				,						[additional_special_token]   )
								self.assertListEqual(getattr(UpperCAmelCase				,						'additional_special_tokens_ids'   )				,						[additional_special_token_id]   )



			def __SCREAMING_SNAKE_CASE							(						self   )			->   List[str]:
								pass



			def __SCREAMING_SNAKE_CASE							(						self   )			->   int:
								pass



			def __SCREAMING_SNAKE_CASE							(						self   )			->   Any:
								pass



			def __SCREAMING_SNAKE_CASE							(						self   )			->   Any:
								pass



			def __SCREAMING_SNAKE_CASE							(						self   )			->   str:
								pass



			def __SCREAMING_SNAKE_CASE							(						self   )			->   str:
								pass



			def __SCREAMING_SNAKE_CASE							(						self   )			->   int:
								pass







			def __SCREAMING_SNAKE_CASE							(						self   )			->   Tuple:
								pass





def 							lowerCAmelCase(     __lowerCamelCase						):
					if not all(char in '01' for char in bin_string						):
										raise ValueError('Non-binary value was passed to the function'						)
					if not bin_string:
										raise ValueError('Empty string was passed to the function'						)
					__a		 =       ''
					while len(__lowerCamelCase						) % 3 != 0:
										__a		 =       '0' + bin_string
					__a		 =       [
					    bin_string[index : index + 3]
					    for index in range(len(__lowerCamelCase						)						)
					    if index % 3 == 0
					]
					for bin_group in bin_string_in_3_list:
										__a		 =       0
										for index, val in enumerate(__lowerCamelCase						):
															oct_val += int(2 ** (2 - index) * int(__lowerCamelCase						)						)
										oct_string += str(__lowerCamelCase						)
					return oct_string


if __name__ == "__main__":
	from doctest import testmod

	testmod()




