
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     UpperCAmelCase						(		unittest.TestCase					):



   def 							_SCREAMING_SNAKE_CASE  (self						:   int					)						->      Dict:


          '''simple docstring'''


          snake_case			:  Any     							= "laion/clap-htsat-unfused"
          snake_case			:  List[str]     							= tempfile.mkdtemp()



   def 							_SCREAMING_SNAKE_CASE  (self						:   List[str]       ,		**snake_case__						:   Dict					)						->      Optional[Any]:


          '''simple docstring'''


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



   def 							_SCREAMING_SNAKE_CASE  (self						:   Any       ,		**snake_case__						:   Union[str, Any]					)						->      Optional[int]:


          '''simple docstring'''


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



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


          '''simple docstring'''


          shutil.rmtree(self.tmpdirname					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   str					)						->      int:


          '''simple docstring'''


          snake_case			:  Optional[int]     							= self.get_tokenizer()
          snake_case			:  Optional[int]     							= self.get_feature_extractor()

          snake_case			:  Tuple     							= ClapProcessor(tokenizer=snake_case__       ,		feature_extractor=snake_case__					)

          processor.save_pretrained(self.tmpdirname					)
          snake_case			:  List[Any]     							= ClapProcessor.from_pretrained(self.tmpdirname					)

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

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



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


          '''simple docstring'''


          snake_case			:  int     							= ClapProcessor(tokenizer=self.get_tokenizer()       ,		feature_extractor=self.get_feature_extractor()					)
          processor.save_pretrained(self.tmpdirname					)

          snake_case			:  Any     							= self.get_tokenizer(bos_token="(BOS)"       ,		eos_token="(EOS)"					)
          snake_case			:  Optional[int]     							= self.get_feature_extractor(do_normalize=snake_case__       ,		padding_value=1.0					)

          snake_case			:  int     							= ClapProcessor.from_pretrained(
              self.tmpdirname       ,		bos_token="(BOS)"       ,		eos_token="(EOS)"       ,		do_normalize=snake_case__       ,		padding_value=1.0					)

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

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



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


          '''simple docstring'''


          snake_case			:  Dict     							= self.get_feature_extractor()
          snake_case			:  Optional[Any]     							= self.get_tokenizer()

          snake_case			:  int     							= ClapProcessor(tokenizer=snake_case__       ,		feature_extractor=snake_case__					)

          snake_case			:  Optional[int]     							= floats_list((3, 10_00)					)

          snake_case			:  Tuple     							= feature_extractor(snake_case__       ,		return_tensors="np"					)
          snake_case			:  int     							= processor(audios=snake_case__       ,		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 							_SCREAMING_SNAKE_CASE  (self						:   str					)						->      List[Any]:


          '''simple docstring'''


          snake_case			:  Optional[Any]     							= self.get_feature_extractor()
          snake_case			:  Optional[Any]     							= self.get_tokenizer()

          snake_case			:  Tuple     							= ClapProcessor(tokenizer=snake_case__       ,		feature_extractor=snake_case__					)

          snake_case			:  int     							= "This is a test string"

          snake_case			:  Any     							= processor(text=snake_case__					)

          snake_case			:  Tuple     							= tokenizer(snake_case__					)

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



   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[Any]					)						->      Dict:


          '''simple docstring'''


          snake_case			:  Tuple     							= self.get_feature_extractor()
          snake_case			:  str     							= self.get_tokenizer()

          snake_case			:  Optional[Any]     							= ClapProcessor(tokenizer=snake_case__       ,		feature_extractor=snake_case__					)

          snake_case			:  Tuple     							= [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

          snake_case			:  List[str]     							= processor.batch_decode(snake_case__					)
          snake_case			:  Optional[Any]     							= tokenizer.batch_decode(snake_case__					)

          self.assertListEqual(snake_case__       ,		snake_case__					)



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


          '''simple docstring'''


          snake_case			:  Tuple     							= self.get_feature_extractor()
          snake_case			:  List[str]     							= self.get_tokenizer()

          snake_case			:  Dict     							= ClapProcessor(tokenizer=snake_case__       ,		feature_extractor=snake_case__					)

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







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


def      UpperCamelCase   (       __lowerCamelCase	:					int = 8       ):
       snake_case			:  int     							= ascii_letters + digits + punctuation
       return "".join(secrets.choice(__lowerCamelCase       ) for _ in range(__lowerCamelCase       )       )


def      UpperCamelCase   (       __lowerCamelCase	:					str							,   __lowerCamelCase	:					int       ):
       # Password Generator = full boot with random_number, random_letters, and
       # random_character FUNCTIONS
       # Put your code here...
       i -= len(__lowerCamelCase       )
       snake_case			:  Any     							= i // 3
       snake_case			:  Optional[int]     							= i % 3
       # chars = chars_incl + random_letters(ascii_letters, i / 3 + remainder) +
       #     random_number(digits, i / 3) + random_characters(punctuation, i / 3)
       snake_case			:  Tuple     							= (
           chars_incl
           + random(__lowerCamelCase							,   quotient + remainder       )
           + random(__lowerCamelCase							,   __lowerCamelCase       )
           + random(__lowerCamelCase							,   __lowerCamelCase       )
       )
       snake_case			:  Optional[Any]     							= list(__lowerCamelCase       )
       shuffle(__lowerCamelCase       )
       return "".join(__lowerCamelCase       )

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


def      UpperCamelCase   (       __lowerCamelCase	:					str							,   __lowerCamelCase	:					int       ):
       return "".join(secrets.choice(__lowerCamelCase       ) for _ in range(__lowerCamelCase       )       )


def      UpperCamelCase   (       __lowerCamelCase	:					List[str]							,   __lowerCamelCase	:					str       ):
       pass  # Put your code here...


def      UpperCamelCase   (       __lowerCamelCase	:					Optional[int]							,   __lowerCamelCase	:					List[str]       ):
       pass  # Put your code here...


def      UpperCamelCase   (       __lowerCamelCase	:					Any							,   __lowerCamelCase	:					List[Any]       ):
       pass  # Put your code here...


def      UpperCamelCase   (       __lowerCamelCase	:					str							,   __lowerCamelCase	:					int = 8       ):

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

       snake_case			:  Dict     							= any(char in ascii_uppercase for char in password       )
       snake_case			:  Optional[int]     							= any(char in ascii_lowercase for char in password       )
       snake_case			:  str     							= any(char in digits for char in password       )
       snake_case			:  str     							= 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      UpperCamelCase   (       ):
       snake_case			:  int     							= int(input("Please indicate the max length of your password: "       ).strip()       )
       snake_case			:  Union[str, Any]     							= input(
           "Please indicate the characters that must be in your password: "       ).strip()
       print("Password generated:"							,   password_generator(__lowerCamelCase       )       )
       print(
           "Alternative Password generated:"							,   alternative_password_generator(__lowerCamelCase							,   __lowerCamelCase       )							,   )
       print("[If you are thinking of using this passsword, You better save it.]"       )


if __name__ == "__main__":
   main()





