
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        SCREAMING_SNAKE_CASE__    (							_UpperCamelCase   ,		unittest.TestCase    ):

							"""simple docstring"""






							_snake_case     		=  CanineTokenizer
							_snake_case     		=  False



							def     A__		(  self			)->   int:





													'''simple docstring'''






													super().setUp()
													__UpperCamelCase       =			CanineTokenizer()
													tokenizer.save_pretrained(self.tmpdirname			)



							@cached_property
							def     A__		(  self			)->   Union[str, Any]:





													'''simple docstring'''






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



							def     A__		(  self     ,	**SCREAMING_SNAKE_CASE_			)->   Optional[Any]:





													'''simple docstring'''






													__UpperCamelCase       =			self.tokenizer_class.from_pretrained(self.tmpdirname     ,	**_UpperCAmelCase			)
													__UpperCamelCase       =			1024
													return tokenizer



							@require_torch
							def     A__		(  self			)->   Optional[Any]:





													'''simple docstring'''






													__UpperCamelCase       =			self.canine_tokenizer
													__UpperCamelCase       =			['''Life is like a box of chocolates.''', '''You never know what you\'re gonna get.''']
													# fmt: off
													__UpperCamelCase       =			[57344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 57345, 0, 0, 0, 0]
													# fmt: on
													__UpperCamelCase       =			tokenizer(_UpperCAmelCase     ,	padding=_UpperCAmelCase     ,	return_tensors='''pt'''			)
													self.assertIsInstance(_UpperCAmelCase     ,	_UpperCAmelCase			)

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

													self.assertListEqual(_UpperCAmelCase     ,	_UpperCAmelCase			)

													self.assertEqual((2, 39)     ,	batch.input_ids.shape			)
													self.assertEqual((2, 39)     ,	batch.attention_mask.shape			)



							@require_torch
							def     A__		(  self			)->   Optional[int]:





													'''simple docstring'''






													__UpperCamelCase       =			self.canine_tokenizer
													__UpperCamelCase       =			['''Once there was a man.''', '''He wrote a test in HuggingFace Tranformers.''']
													__UpperCamelCase       =			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     A__		(  self			)->   Optional[int]:





													'''simple docstring'''






													__UpperCamelCase       =			self.canine_tokenizer
													__UpperCamelCase       =			[
													    '''What\'s the weater?''',
													    '''It\'s about 25 degrees.''',
													]
													__UpperCamelCase       =			tokenizer(
													    text_target=_UpperCAmelCase     ,	max_length=32     ,	padding='''max_length'''     ,	truncation=_UpperCAmelCase     ,	return_tensors='''pt'''			)
													self.assertEqual(32     ,	targets['''input_ids'''].shape[1]			)



							def     A__		(  self			)->   Any:





													'''simple docstring'''






													__UpperCamelCase       =			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
													__UpperCamelCase       =			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
																									__UpperCamelCase       =			tempfile.mkdtemp()

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

																									__UpperCamelCase       =			tokenizer.__class__.from_pretrained(_UpperCAmelCase			)
																									__UpperCamelCase       =			after_tokenizer.encode(_UpperCAmelCase     ,	add_special_tokens=_UpperCAmelCase			)
																									self.assertListEqual(_UpperCAmelCase     ,	_UpperCAmelCase			)

																									shutil.rmtree(_UpperCAmelCase			)

													__UpperCamelCase       =			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
																									__UpperCamelCase       =			tempfile.mkdtemp()

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

																									__UpperCamelCase       =			tokenizer.additional_special_tokens

																									# We can add a new special token for Canine as follows:
																									__UpperCamelCase       =			chr(0xE0_07			)
																									additional_special_tokens.append(_UpperCAmelCase			)
																									tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}			)
																									__UpperCamelCase       =			tokenizer.encode(_UpperCAmelCase     ,	add_special_tokens=_UpperCAmelCase			)
																									tokenizer.save_pretrained(_UpperCAmelCase			)

																									__UpperCamelCase       =			tokenizer.__class__.from_pretrained(_UpperCAmelCase			)
																									__UpperCamelCase       =			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     ,	42			)

																									__UpperCamelCase       =			tokenizer.__class__.from_pretrained(_UpperCAmelCase     ,	model_max_length=43			)
																									self.assertEqual(tokenizer.model_max_length     ,	43			)

																									shutil.rmtree(_UpperCAmelCase			)



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





													'''simple docstring'''






													__UpperCamelCase       =			self.get_tokenizers(do_lower_case=_UpperCAmelCase			)
													for tokenizer in tokenizers:
																			with self.subTest(F"{tokenizer.__class__.__name__}"			):
																									__UpperCamelCase       =			self.get_clean_sequence(_UpperCAmelCase			)

																									# a special token for Canine can be defined as follows:
																									__UpperCamelCase       =			0xE0_05
																									__UpperCamelCase       =			chr(_UpperCAmelCase			)

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

																									__UpperCamelCase       =			tokenizer.decode(ids + encoded_special_token     ,	clean_up_tokenization_spaces=_UpperCAmelCase			)
																									__UpperCamelCase       =			tokenizer.encode(_UpperCAmelCase     ,	add_special_tokens=_UpperCAmelCase			)

																									__UpperCamelCase       =			tokenizer.encode(_UpperCAmelCase     ,	add_special_tokens=_UpperCAmelCase			)
																									__UpperCamelCase       =			tokenizer.encode(_UpperCAmelCase     ,	add_special_tokens=_UpperCAmelCase			)
																									self.assertEqual(_UpperCAmelCase     ,	input_encoded + special_token_id			)

																									__UpperCamelCase       =			tokenizer.decode(_UpperCAmelCase     ,	skip_special_tokens=_UpperCAmelCase			)
																									self.assertTrue(special_token not in decoded			)



							def     A__		(  self			)->   Optional[Any]:





													'''simple docstring'''






													__UpperCamelCase       =			self.get_tokenizers(do_lower_case=_UpperCAmelCase			)
													for tokenizer in tokenizers:
																			with self.subTest(F"{tokenizer.__class__.__name__}"			):
																									__UpperCamelCase       =			chr(0xE0_05			)
																									__UpperCamelCase       =			chr(0xE0_06			)

																									# `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]}			)

																									__UpperCamelCase       =			tokenizer.tokenize(_UpperCAmelCase			)
																									__UpperCamelCase       =			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     A__		(  self			)->   Dict:





													'''simple docstring'''






													__UpperCamelCase       =			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:
																									__UpperCamelCase       =			0xE0_06
																									__UpperCamelCase       =			chr(_UpperCAmelCase			)

																									__UpperCamelCase       =			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     A__		(  self			)->   List[Any]:





													'''simple docstring'''






													__UpperCamelCase       =			[]
													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:
																															__UpperCamelCase       =			json.load(_UpperCAmelCase			)

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

																									# a special token for Canine can be defined as follows:
																									__UpperCamelCase       =			0xE0_06
																									__UpperCamelCase       =			chr(_UpperCAmelCase			)

																									__UpperCamelCase       =			[new_token_a]
																									__UpperCamelCase       =			[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
																									__UpperCamelCase       =			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]			)			)     ,	)

																									__UpperCamelCase       =			0xE0_07
																									__UpperCamelCase       =			chr(_UpperCAmelCase			)
																									# Now we test that we can change the value of additional_special_tokens in the from_pretrained
																									__UpperCamelCase       =			[AddedToken(_UpperCAmelCase     ,	lstrip=_UpperCAmelCase			)]
																									__UpperCamelCase       =			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     A__		(  self			)->   Optional[Any]:





													'''simple docstring'''






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



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





													'''simple docstring'''






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

													__UpperCamelCase       =			'''a'''
													__UpperCamelCase       =			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'''			)     ,	[]			)

													__UpperCamelCase       =			0xE0_06
													__UpperCamelCase       =			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     A__		(  self			)->   List[str]:





													'''simple docstring'''






													pass



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





													'''simple docstring'''






													pass



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





													'''simple docstring'''






													pass



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





													'''simple docstring'''






													pass



							def     A__		(  self			)->   Dict:





													'''simple docstring'''






													pass



							def     A__		(  self			)->   int:





													'''simple docstring'''






													pass



							def     A__		(  self			)->   Optional[Any]:





													'''simple docstring'''






													pass



							def     A__		(  self			)->   Optional[Any]:





													'''simple docstring'''






													pass






def 	A_ (							snake_case							:   int = 10 ,      snake_case							:   int = 1000 ,      snake_case							:   bool = True )      ->    int:



						'''simple docstring'''

						assert (
						    isinstance(snake_case ,      snake_case )
						    and isinstance(snake_case ,      snake_case )
						    and isinstance(snake_case ,      snake_case )
						), "Invalid type of value(s) specified to function!"

						if min_val > max_val:
												raise ValueError('''Invalid value for min_val or max_val (min_value < max_value)''' )
						return min_val if option else max_val




def 	A_ (							snake_case							:   int ,      snake_case							:   int )      ->    int:



						'''simple docstring'''

						return int((number_a + number_a) / 2 )




def 	A_ (							snake_case							:   int ,      snake_case							:   int ,      snake_case							:   int )      ->    None:



						'''simple docstring'''

						assert (
						    isinstance(snake_case ,      snake_case ) and isinstance(snake_case ,      snake_case ) and isinstance(snake_case ,      snake_case )
						), 'argument values must be type of "int"'

						if lower > higher:
												raise ValueError('''argument value for lower and higher must be(lower > higher)''' )

						if not lower < to_guess < higher:
												raise ValueError(
												    '''guess value must be within the range of lower and higher value''' )

						def answer(snake_case							:   int ) -> str:
												if number > to_guess:
																		return "high"
												elif number < to_guess:
																		return "low"
												else:
																		return "same"

						print('''started...''' )

						__UpperCamelCase       =			lower
						__UpperCamelCase       =			higher

						__UpperCamelCase       =			[]

						while True:
												__UpperCamelCase       =			get_avg(snake_case ,      snake_case )
												last_numbers.append(snake_case )

												if answer(snake_case ) == "low":
																		__UpperCamelCase       =			number
												elif answer(snake_case ) == "high":
																		__UpperCamelCase       =			number
												else:
																		break

						print(f"guess the number : {last_numbers[-1]}" )
						print(f"details : {last_numbers!s}" )




def 	A_ (							)      ->    None:



						'''simple docstring'''

						__UpperCamelCase       =			int(input('''Enter lower value : ''' ).strip() )
						__UpperCamelCase       =			int(input('''Enter high value : ''' ).strip() )
						__UpperCamelCase       =			int(input('''Enter value to guess : ''' ).strip() )
						guess_the_number(snake_case ,      snake_case ,      snake_case )


if __name__ == "__main__":
				main()




