

class 				__lowerCAmelCase  :




  def __init__(       self							,     lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase      )						->				Tuple:
        '''simple docstring'''






        _lowercase			 =name
        _lowercase			 =value
        _lowercase			 =weight




  def __repr__(       self      )						->				Dict:
        '''simple docstring'''






        return F'''{self.__class__.__name__}({self.name}, {self.value}, {self.weight})'''




  def 						A__  (       self      )						->				Optional[int]:
        '''simple docstring'''






        return self.value




  def 						A__  (       self      )						->				Tuple:
        '''simple docstring'''






        return self.name




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






        return self.weight




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






        return self.value / self.weight
def   a   (    A__			:     Dict   ,     A__			:     str   ,     A__			:     Optional[Any]  )					->   Optional[int]:





      """simple docstring"""



      _lowercase			 =[]
      for i in range(len(__lowerCAmelCase  )  ):
            menu.append(Things(name[i]   ,     value[i]   ,     weight[i]  )  )
      return menu
def   a   (    A__			:     Union[str, Any]   ,     A__			:     Optional[Any]   ,     A__			:     Optional[int]  )					->   Any:





      """simple docstring"""



      _lowercase			 =sorted(__lowerCAmelCase   ,     key=__lowerCAmelCase   ,     reverse=__lowerCAmelCase  )
      _lowercase			 =[]
      _lowercase , _lowercase			 =0.0, 0.0
      for i in range(len(__lowerCAmelCase  )  ):
            if (total_cost + items_copy[i].get_weight()) <= max_cost:
                  result.append(items_copy[i]  )
                  total_cost += items_copy[i].get_weight()
                  total_value += items_copy[i].get_value()
      return (result, total_value)
def   a   (    )					->   List[str]:





      """simple docstring"""







if __name__ == "__main__":
 import doctest

 doctest.testmod()





import math

import tensorflow as tf
from packaging import version
def   a   (    A__			:     Tuple  )					->   List[Any]:





      """simple docstring"""



      _lowercase			 =tf.convert_to_tensor(A__  )
      _lowercase			 =0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0  )   ,     x.dtype  )  ))

      return x * cdf
def   a   (    A__			:     Any  )					->   int:





      """simple docstring"""



      _lowercase			 =tf.convert_to_tensor(A__  )
      _lowercase			 =tf.cast(math.pi   ,     x.dtype  )
      _lowercase			 =tf.cast(0.044715   ,     x.dtype  )
      _lowercase			 =0.5 * (1.0 + tf.tanh(tf.sqrt(2.0 / pi  ) * (x + coeff * tf.pow(A__   ,     3  ))  ))

      return x * cdf
def   a   (    A__			:     Optional[int]  )					->   int:





      """simple docstring"""



      _lowercase			 =tf.convert_to_tensor(A__  )

      return x * tf.tanh(tf.math.softplus(A__  )  )
def   a   (    A__			:     Tuple  )					->   List[str]:





      """simple docstring"""



      _lowercase			 =tf.convert_to_tensor(A__  )
      _lowercase			 =tf.cast(0.044715   ,     x.dtype  )
      _lowercase			 =tf.cast(0.7978845608   ,     x.dtype  )

      return 0.5 * x * (1.0 + tf.tanh(x * coeffa * (1.0 + coeffa * x * x)  ))
def   a   (    A__			:     int  )					->   Any:





      """simple docstring"""



      _lowercase			 =tf.convert_to_tensor(A__  )
      _lowercase			 =tf.cast(1.702   ,     x.dtype  )
      return x * tf.math.sigmoid(coeff * x  )
def   a   (    A__			:     int  )					->   Dict:





      """simple docstring"""



      return tf.clip_by_value(_gelu(A__  )   ,     -10   ,     10  )
def   a   (    A__			:     Optional[int]   ,     A__			:     int=-1  )					->   Optional[Any]:





      """simple docstring"""



      _lowercase , _lowercase			 =tf.split(A__   ,     2   ,     axis=A__  )
      return a * tf.math.sigmoid(A__  )


if version.parse(tf.version.VERSION) >= version.parse('2.4'):
  def   a   (    A__			:     Any  )					->   Dict:





        """simple docstring"""



        return tf.keras.activations.gelu(A__   ,     approximate=A__  )

  lowercase_             =     tf.keras.activations.gelu







  lowercase_             =     approximate_gelu_wrap
else:
  lowercase_             =     _gelu
  lowercase_             =     _gelu_new


lowercase_             =     {
    'gelu': gelu,
    'gelu_10': gelu_aa,
    'gelu_fast': gelu_fast,
    'gelu_new': gelu_new,
    'glu': glu,
    'mish': mish,
    'quick_gelu': quick_gelu,
    'relu': tf.keras.activations.relu,
    'sigmoid': tf.keras.activations.sigmoid,
    'silu': tf.keras.activations.swish,
    'swish': tf.keras.activations.swish,
    'tanh': tf.keras.activations.tanh,
}







def   a   (    A__			:     Optional[int]  )					->   str:





      """simple docstring"""



      if activation_string in ACTaFN:
            return ACTaFN[activation_string]
      else:
            raise KeyError(F'''function {activation_string} not found in ACT2FN mapping {list(ACTaFN.keys()  )}'''  )


