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







def  __UpperCamelCase    (						A = 8							):
     UpperCamelCase__										=      ascii_letters + digits + punctuation
     return "".join(secrets.choice(A							) for _ in range(A							)							)







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

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







def  __UpperCamelCase    (						A ,							A							):
     return "".join(secrets.choice(A							) for _ in range(A							)							)







def  __UpperCamelCase    (						A ,							A							):
     pass  # Put your code here...







def  __UpperCamelCase    (						A ,							A							):
     pass  # Put your code here...







def  __UpperCamelCase    (						A ,							A							):
     pass  # Put your code here...







def  __UpperCamelCase    (						A ,							A = 8							):

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

     UpperCamelCase__										=      any(char in ascii_uppercase for char in password							)
     UpperCamelCase__										=      any(char in ascii_lowercase for char in password							)
     UpperCamelCase__										=      any(char in digits for char in password							)
     UpperCamelCase__										=      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    (						):
     UpperCamelCase__										=      int(input('''Please indicate the max length of your password: '''							).strip()							)
     UpperCamelCase__										=      input(
         '''Please indicate the characters that must be in your password: '''							).strip()
     print('''Password generated:''' ,							password_generator(A							)							)
     print(
         '''Alternative Password generated:''' ,							alternative_password_generator(A ,							A							) ,							)
     print('''[If you are thinking of using this passsword, You better save it.]'''							)


if __name__ == "__main__":
     main()




import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel

from ...models.attention import BasicTransformerBlock
from ...utils import logging


__magic_name__								=logging.get_logger(__name__)  # pylint: disable=invalid-name



class     _A   (    __UpperCamelCase							):






  def __init__(self   ,				SCREAMING_SNAKE_CASE_   ,				SCREAMING_SNAKE_CASE_=768	)		->      Dict:





       '''simple docstring'''





       super().__init__(SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      proj_size

       UpperCamelCase__										=      CLIPVisionModel(SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      PaintByExampleMapper(SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      nn.LayerNorm(config.hidden_size	)
       UpperCamelCase__										=      nn.Linear(config.hidden_size   ,				self.proj_size	)

       # uncondition for scaling
       UpperCamelCase__										=      nn.Parameter(torch.randn((1, 1, self.proj_size)	)	)






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_   ,				SCREAMING_SNAKE_CASE_=False	)		->      List[str]:





       '''simple docstring'''





       UpperCamelCase__										=      self.model(pixel_values=SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      clip_output.pooler_output
       UpperCamelCase__										=      self.mapper(latent_states[:, None]	)
       UpperCamelCase__										=      self.final_layer_norm(SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      self.proj_out(SCREAMING_SNAKE_CASE_	)
       if return_uncond_vector:
            return latent_states, self.uncond_vector

       return latent_states



class     _A   (    nn.Module							):






  def __init__(self   ,				SCREAMING_SNAKE_CASE_	)		->      int:





       '''simple docstring'''





       super().__init__()
       UpperCamelCase__										=      (config.num_hidden_layers + 1) // 5
       UpperCamelCase__										=      config.hidden_size
       UpperCamelCase__										=      1
       UpperCamelCase__										=      nn.ModuleList(
           [
               BasicTransformerBlock(SCREAMING_SNAKE_CASE_   ,				SCREAMING_SNAKE_CASE_   ,				SCREAMING_SNAKE_CASE_   ,				activation_fn='''gelu'''   ,				attention_bias=SCREAMING_SNAKE_CASE_	)
               for _ in range(SCREAMING_SNAKE_CASE_	)
           ]	)






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_	)		->      str:





       '''simple docstring'''





       for block in self.blocks:
            UpperCamelCase__										=      block(SCREAMING_SNAKE_CASE_	)

       return hidden_states



