


"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation







def   _a			( _SCREAMING_SNAKE_CASE = 8			)      ->			str:
							snake_case_          =						ascii_letters + digits + punctuation
							return "".join(secrets.choice(_SCREAMING_SNAKE_CASE			) for _ in range(_SCREAMING_SNAKE_CASE			)			)







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			str:
							# Password Generator = full boot with random_number, random_letters, and
							# random_character FUNCTIONS
							# Put your code here...
							i -= len(_SCREAMING_SNAKE_CASE			)
							snake_case_          =						i // 3
							snake_case_          =						i % 3
							# chars = chars_incl + random_letters(ascii_letters, i / 3 + remainder) +
							#     random_number(digits, i / 3) + random_characters(punctuation, i / 3)
							snake_case_          =						(
							    chars_incl
							    + random(_SCREAMING_SNAKE_CASE			,	quotient + remainder			)
							    + random(_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)
							    + random(_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)
							)
							snake_case_          =						list(_SCREAMING_SNAKE_CASE			)
							shuffle(_SCREAMING_SNAKE_CASE			)
							return "".join(_SCREAMING_SNAKE_CASE			)

							# random is a generalised function for letters, characters and numbers







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			str:
							return "".join(secrets.choice(_SCREAMING_SNAKE_CASE			) for _ in range(_SCREAMING_SNAKE_CASE			)			)







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			Any:
							pass  # Put your code here...







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			Optional[int]:
							pass  # Put your code here...







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			List[Any]:
							pass  # Put your code here...







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE = 8			)      ->			bool:

							if len(_SCREAMING_SNAKE_CASE			) < min_length:
														# Your Password must be at least 8 characters long
														return False

							snake_case_          =						any(char in ascii_uppercase for char in password			)
							snake_case_          =						any(char in ascii_lowercase for char in password			)
							snake_case_          =						any(char in digits for char in password			)
							snake_case_          =						any(char in punctuation for char in password			)

							return upper and lower and num and spec_char
							# Passwords should contain UPPERCASE, lowerase
							# numbers, and special characters







def   _a			( )      ->			Union[str, Any]:
							snake_case_          =						int(input("""Please indicate the max length of your password: """			).strip()			)
							snake_case_          =						input(
							    """Please indicate the characters that must be in your password: """			).strip()
							print("""Password generated:"""			,	password_generator(_SCREAMING_SNAKE_CASE			)			)
							print(
							    """Alternative Password generated:"""			,	alternative_password_generator(_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)			,	)
							print("""[If you are thinking of using this passsword, You better save it.]"""			)


if __name__ == "__main__":
							main()







"""simple docstring"""
import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list





@require_torchaudio
@require_sentencepiece
class        __A       (unittest.TestCase):





							'''simple docstring'''

							def 						lowerCAmelCase    (			self							: Dict    )   ->List[Any]:



														"""simple docstring"""



														snake_case_          =						"""laion/clap-htsat-unfused"""
														snake_case_          =						tempfile.mkdtemp()



							def 						lowerCAmelCase    (			self							: List[str]						,    **UpperCAmelCase_							: Tuple    )   ->str:



														"""simple docstring"""



														return RobertaTokenizer.from_pretrained(self.checkpoint						,    **UpperCAmelCase_    )



							def 						lowerCAmelCase    (			self							: Optional[Any]						,    **UpperCAmelCase_							: Any    )   ->Optional[Any]:



														"""simple docstring"""



														return ClapFeatureExtractor.from_pretrained(self.checkpoint						,    **UpperCAmelCase_    )



							def 						lowerCAmelCase    (			self							: str    )   ->Any:



														"""simple docstring"""



														shutil.rmtree(self.tmpdirname    )



							def 						lowerCAmelCase    (			self							: Tuple    )   ->Optional[int]:



														"""simple docstring"""



														snake_case_          =						self.get_tokenizer()
														snake_case_          =						self.get_feature_extractor()

														snake_case_          =						ClapProcessor(tokenizer=UpperCAmelCase_						,    feature_extractor=UpperCAmelCase_    )

														processor.save_pretrained(self.tmpdirname    )
														snake_case_          =						ClapProcessor.from_pretrained(self.tmpdirname    )

														self.assertEqual(processor.tokenizer.get_vocab()						,    tokenizer.get_vocab()    )
														self.assertIsInstance(processor.tokenizer						,    UpperCAmelCase_    )

														self.assertEqual(processor.feature_extractor.to_json_string()						,    feature_extractor.to_json_string()    )
														self.assertIsInstance(processor.feature_extractor						,    UpperCAmelCase_    )



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



														"""simple docstring"""



														snake_case_          =						ClapProcessor(tokenizer=self.get_tokenizer()						,    feature_extractor=self.get_feature_extractor()    )
														processor.save_pretrained(self.tmpdirname    )

														snake_case_          =						self.get_tokenizer(bos_token="""(BOS)"""						,    eos_token="""(EOS)"""    )
														snake_case_          =						self.get_feature_extractor(do_normalize=UpperCAmelCase_						,    padding_value=1.0    )

														snake_case_          =						ClapProcessor.from_pretrained(
														    self.tmpdirname						,    bos_token="""(BOS)"""						,    eos_token="""(EOS)"""						,    do_normalize=UpperCAmelCase_						,    padding_value=1.0    )

														self.assertEqual(processor.tokenizer.get_vocab()						,    tokenizer_add_kwargs.get_vocab()    )
														self.assertIsInstance(processor.tokenizer						,    UpperCAmelCase_    )

														self.assertEqual(processor.feature_extractor.to_json_string()						,    feature_extractor_add_kwargs.to_json_string()    )
														self.assertIsInstance(processor.feature_extractor						,    UpperCAmelCase_    )



							def 						lowerCAmelCase    (			self							: str    )   ->Dict:



														"""simple docstring"""



														snake_case_          =						self.get_feature_extractor()
														snake_case_          =						self.get_tokenizer()

														snake_case_          =						ClapProcessor(tokenizer=UpperCAmelCase_						,    feature_extractor=UpperCAmelCase_    )

														snake_case_          =						floats_list((3, 1_000)    )

														snake_case_          =						feature_extractor(UpperCAmelCase_						,    return_tensors="""np"""    )
														snake_case_          =						processor(audios=UpperCAmelCase_						,    return_tensors="""np"""    )

														for key in input_feat_extract.keys():
																					self.assertAlmostEqual(input_feat_extract[key].sum()						,    input_processor[key].sum()						,    delta=1E-2    )



							def 						lowerCAmelCase    (			self							: Union[str, Any]    )   ->Optional[int]:



														"""simple docstring"""



														snake_case_          =						self.get_feature_extractor()
														snake_case_          =						self.get_tokenizer()

														snake_case_          =						ClapProcessor(tokenizer=UpperCAmelCase_						,    feature_extractor=UpperCAmelCase_    )

														snake_case_          =						"""This is a test string"""

														snake_case_          =						processor(text=UpperCAmelCase_    )

														snake_case_          =						tokenizer(UpperCAmelCase_    )

														for key in encoded_tok.keys():
																					self.assertListEqual(encoded_tok[key]						,    encoded_processor[key]    )



							def 						lowerCAmelCase    (			self							: Optional[int]    )   ->Tuple:



														"""simple docstring"""



														snake_case_          =						self.get_feature_extractor()
														snake_case_          =						self.get_tokenizer()

														snake_case_          =						ClapProcessor(tokenizer=UpperCAmelCase_						,    feature_extractor=UpperCAmelCase_    )

														snake_case_          =						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

														snake_case_          =						processor.batch_decode(UpperCAmelCase_    )
														snake_case_          =						tokenizer.batch_decode(UpperCAmelCase_    )

														self.assertListEqual(UpperCAmelCase_						,    UpperCAmelCase_    )



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



														"""simple docstring"""



														snake_case_          =						self.get_feature_extractor()
														snake_case_          =						self.get_tokenizer()

														snake_case_          =						ClapProcessor(tokenizer=UpperCAmelCase_						,    feature_extractor=UpperCAmelCase_    )

														self.assertListEqual(
														    processor.model_input_names[2:]						,    feature_extractor.model_input_names						,    msg="""`processor` and `feature_extractor` model input names do not match"""						,    )



