


import copy
import os
from typing import TYPE_CHECKING, List, Union


if TYPE_CHECKING:
    pass

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase					:       Tuple			    =     logging.get_logger(__name__)

UpperCamelCase					:       str			    =     {
    """kakaobrain/align-base""": """https://huggingface.co/kakaobrain/align-base/resolve/main/config.json""",
}



class A__     ( A__  ):



  """simple docstring"""



  _lowercase									=		'align_text_model'

  def __init__( self			:  Dict				,				lowerCamelCase__			:  Dict=30_522				,				lowerCamelCase__			:  Optional[int]=768				,				lowerCamelCase__			:  Tuple=12				,				lowerCamelCase__			:  Tuple=12				,				lowerCamelCase__			:  List[str]=3_072				,				lowerCamelCase__			:  Union[str, Any]="gelu"				,				lowerCamelCase__			:  str=0.1				,				lowerCamelCase__			:  List[Any]=0.1				,				lowerCamelCase__			:  Any=512				,				lowerCamelCase__			:  Optional[int]=2				,				lowerCamelCase__			:  Optional[int]=0.02				,				lowerCamelCase__			:  Optional[Any]=1E-12				,				lowerCamelCase__			:  Dict=0				,				lowerCamelCase__			:  Optional[int]="absolute"				,				lowerCamelCase__			:  List[Any]=True				,				**lowerCamelCase__			:  Optional[Any]				,				):
        super().__init__(**lowerCamelCase__       )

        a__	:  Optional[Any]     =   vocab_size
        a__	:  Optional[int]     =   hidden_size
        a__	:  str     =   num_hidden_layers
        a__	:  int     =   num_attention_heads
        a__	:  Any     =   hidden_act
        a__	:  str     =   intermediate_size
        a__	:  List[Any]     =   hidden_dropout_prob
        a__	:  str     =   attention_probs_dropout_prob
        a__	:  List[Any]     =   max_position_embeddings
        a__	:  List[Any]     =   type_vocab_size
        a__	:  Optional[int]     =   initializer_range
        a__	:  int     =   layer_norm_eps
        a__	:  Optional[Any]     =   position_embedding_type
        a__	:  Dict     =   use_cache
        a__	:  Optional[int]     =   pad_token_id

  @classmethod
  def    _UpperCamelCase( cls			:  int				,				lowerCamelCase__			:  Union[str, os.PathLike]				,				**lowerCamelCase__			:  List[str]       ):
        cls._set_token_in_kwargs(lowerCamelCase__       )

        a__,	a__	:  Dict     =   cls.get_config_dict(lowerCamelCase__				,				**lowerCamelCase__       )

        # get the text config dict if we are loading from AlignConfig
        if config_dict.get("model_type"       ) == "align":
              a__	:  int     =   config_dict["text_config"]

        if "model_type" in config_dict and hasattr(cls				,				"model_type"       ) and config_dict["model_type"] != cls.model_type:
              logger.warning(
                  f'''You are using a model of type {config_dict['model_type']} to instantiate a model of type '''
                  f'''{cls.model_type}. This is not supported for all configurations of models and can yield errors.'''       )

        return cls.from_dict(lowerCamelCase__				,				**lowerCamelCase__       )




class A__     ( A__  ):



  """simple docstring"""



  _lowercase									=		'align_vision_model'

  def __init__( self			:  List[Any]				,				lowerCamelCase__			:  int = 3				,				lowerCamelCase__			:  int = 600				,				lowerCamelCase__			:  float = 2.0				,				lowerCamelCase__			:  float = 3.1				,				lowerCamelCase__			:  int = 8				,				lowerCamelCase__			:  List[int] = [3, 3, 5, 3, 5, 5, 3]				,				lowerCamelCase__			:  List[int] = [32, 16, 24, 40, 80, 112, 192]				,				lowerCamelCase__			:  List[int] = [16, 24, 40, 80, 112, 192, 320]				,				lowerCamelCase__			:  List[int] = []				,				lowerCamelCase__			:  List[int] = [1, 2, 2, 2, 1, 2, 1]				,				lowerCamelCase__			:  List[int] = [1, 2, 2, 3, 3, 4, 1]				,				lowerCamelCase__			:  List[int] = [1, 6, 6, 6, 6, 6, 6]				,				lowerCamelCase__			:  float = 0.25				,				lowerCamelCase__			:  str = "swish"				,				lowerCamelCase__			:  int = 2_560				,				lowerCamelCase__			:  str = "mean"				,				lowerCamelCase__			:  float = 0.02				,				lowerCamelCase__			:  float = 0.001				,				lowerCamelCase__			:  float = 0.99				,				lowerCamelCase__			:  float = 0.2				,				**lowerCamelCase__			:  List[str]				,				):
        super().__init__(**lowerCamelCase__       )

        a__	:  Union[str, Any]     =   num_channels
        a__	:  List[Any]     =   image_size
        a__	:  int     =   width_coefficient
        a__	:  int     =   depth_coefficient
        a__	:  Union[str, Any]     =   depth_divisor
        a__	:  Optional[Any]     =   kernel_sizes
        a__	:  Union[str, Any]     =   in_channels
        a__	:  Optional[Any]     =   out_channels
        a__	:  Any     =   depthwise_padding
        a__	:  Any     =   strides
        a__	:  int     =   num_block_repeats
        a__	:  List[Any]     =   expand_ratios
        a__	:  int     =   squeeze_expansion_ratio
        a__	:  Optional[Any]     =   hidden_act
        a__	:  List[str]     =   hidden_dim
        a__	:  List[str]     =   pooling_type
        a__	:  List[str]     =   initializer_range
        a__	:  Union[str, Any]     =   batch_norm_eps
        a__	:  int     =   batch_norm_momentum
        a__	:  List[str]     =   drop_connect_rate
        a__	:  Dict     =   sum(lowerCamelCase__       ) * 4

  @classmethod
  def    _UpperCamelCase( cls			:  Dict				,				lowerCamelCase__			:  Union[str, os.PathLike]				,				**lowerCamelCase__			:  Dict       ):
        cls._set_token_in_kwargs(lowerCamelCase__       )

        a__,	a__	:  Union[str, Any]     =   cls.get_config_dict(lowerCamelCase__				,				**lowerCamelCase__       )

        # get the vision config dict if we are loading from AlignConfig
        if config_dict.get("model_type"       ) == "align":
              a__	:  List[str]     =   config_dict["vision_config"]

        if "model_type" in config_dict and hasattr(cls				,				"model_type"       ) and config_dict["model_type"] != cls.model_type:
              logger.warning(
                  f'''You are using a model of type {config_dict['model_type']} to instantiate a model of type '''
                  f'''{cls.model_type}. This is not supported for all configurations of models and can yield errors.'''       )

        return cls.from_dict(lowerCamelCase__				,				**lowerCamelCase__       )




class A__     ( A__  ):



  """simple docstring"""



  _lowercase									=		'align'
  _lowercase									=		True

  def __init__( self			:  str				,				lowerCamelCase__			:  Optional[int]=None				,				lowerCamelCase__			:  Any=None				,				lowerCamelCase__			:  Dict=640				,				lowerCamelCase__			:  Tuple=1.0				,				lowerCamelCase__			:  Any=0.02				,				**lowerCamelCase__			:  Optional[int]				,				):
        super().__init__(**lowerCamelCase__       )

        if text_config is None:
              a__	:  Optional[int]     =   {}
              logger.info("text_config is None. Initializing the AlignTextConfig with default values."       )

        if vision_config is None:
              a__	:  Union[str, Any]     =   {}
              logger.info("vision_config is None. Initializing the AlignVisionConfig with default values."       )

        a__	:  Optional[Any]     =   AlignTextConfig(**lowerCamelCase__       )
        a__	:  str     =   AlignVisionConfig(**lowerCamelCase__       )

        a__	:  Dict     =   projection_dim
        a__	:  List[str]     =   temperature_init_value
        a__	:  Dict     =   initializer_range

  @classmethod
  def    _UpperCamelCase( cls			:  Tuple				,				lowerCamelCase__			:  AlignTextConfig				,				lowerCamelCase__			:  AlignVisionConfig				,				**lowerCamelCase__			:  List[str]       ):
        return cls(text_config=text_config.to_dict()				,				vision_config=vision_config.to_dict()				,				**lowerCamelCase__       )

  def    _UpperCamelCase( self			:  Any       ):
        a__	:  int     =   copy.deepcopy(self.__dict__       )
        a__	:  int     =   self.text_config.to_dict()
        a__	:  Tuple     =   self.vision_config.to_dict()
        a__	:  Optional[Any]     =   self.__class__.model_type
        return output





import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def 							__lowerCamelCase		(					UpperCAmelCase_		:						int = 8		):




      """simple docstring"""





      a		:Optional[int]									=			ascii_letters + digits + punctuation
      return "".join(secrets.choice(UpperCAmelCase_		) for _ in range(UpperCAmelCase_		)		)
def 							__lowerCamelCase		(					UpperCAmelCase_		:						str					,    UpperCAmelCase_		:						int		):




      """simple docstring"""





      i -= len(UpperCAmelCase_		)
      a		:Tuple									=			i // 3
      a		:int									=			i % 3
      # chars = chars_incl + random_letters(ascii_letters, i / 3 + remainder) +
      #     random_number(digits, i / 3) + random_characters(punctuation, i / 3)
      a		:Union[str, Any]									=			(
          chars_incl
          + random(UpperCAmelCase_					,    quotient + remainder		)
          + random(UpperCAmelCase_					,    UpperCAmelCase_		)
          + random(UpperCAmelCase_					,    UpperCAmelCase_		)
      )
      a		:Dict									=			list(UpperCAmelCase_		)
      shuffle(UpperCAmelCase_		)
      return "".join(UpperCAmelCase_		)

      # random is a generalised function for letters, characters and numbers
def 							__lowerCamelCase		(					UpperCAmelCase_		:						str					,    UpperCAmelCase_		:						int		):




      """simple docstring"""





      return "".join(secrets.choice(UpperCAmelCase_		) for _ in range(UpperCAmelCase_		)		)
def 							__lowerCamelCase		(					UpperCAmelCase_		:						Union[str, Any]					,    UpperCAmelCase_		:						Tuple		):




      """simple docstring"""





      pass  # Put your code here...
def 							__lowerCamelCase		(					UpperCAmelCase_		:						Union[str, Any]					,    UpperCAmelCase_		:						str		):




      """simple docstring"""





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




      """simple docstring"""





      pass  # Put your code here...
def 							__lowerCamelCase		(					UpperCAmelCase_		:						str					,    UpperCAmelCase_		:						int = 8		):




      """simple docstring"""





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

      a		:Dict									=			any(char in ascii_uppercase for char in password		)
      a		:Optional[int]									=			any(char in ascii_lowercase for char in password		)
      a		:Tuple									=			any(char in digits for char in password		)
      a		:Any									=			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 							__lowerCamelCase		(					):




      """simple docstring"""





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


if __name__ == "__main__":
     main()





