original_docstring:  Interface to external world. 
          This function does the input checks, preprocesses input and finally applies loss function.
          
          Parameters
          ----------
          scores_pos : tf.Tensor
              A tensor of scores assigned to positive statements.
          scores_neg : tf.Tensor
              A tensor of scores assigned to negative statements.
          
          Returns
          -------
          loss : tf.Tensor
              The loss value that must be minimized.
          
docstring: Interface to external world.
  This function does the input checks, preprocesses input and finally applies loss function.
  
  Parameters
  
  scores_pos : tf.Tensor
  A tensor of scores assigned to positive statements.
  scores_neg : tf.Tensor
  A tensor of scores assigned to negative statements.
  
  Returns
  
  loss : tf.Tensor
  The loss value that must be minimized.
docstring_tokens: Interface to external world . This function does the input checks preprocesses input and finally applies loss function . Parameters scores_pos : tf . Tensor A tensor of scores assigned to positive statements . scores_neg : tf . Tensor A tensor of scores assigned to negative statements . Returns loss : tf . Tensor The loss value that must be minimized .
code: def apply(self, scores_pos, scores_neg):
          """ Interface to external world. 
          This function does the input checks, preprocesses input and finally applies loss function.
          
          Parameters
          ----------
          scores_pos : tf.Tensor
              A tensor of scores assigned to positive statements.
          scores_neg : tf.Tensor
              A tensor of scores assigned to negative statements.
          
          Returns
          -------
          loss : tf.Tensor
              The loss value that must be minimized.
          """
          self._inputs_check(scores_pos, scores_neg)
          with tf.control_dependencies(self._dependencies):
              loss = self._apply(scores_pos, scores_neg)
          return loss
code_tokens: def apply ( self , scores_pos , scores_neg ) : self . _inputs_check ( scores_pos , scores_neg ) with tf . control_dependencies ( self . _dependencies ) : loss = self . _apply ( scores_pos , scores_neg ) return loss
short_docstring: Interface to external world.
short_docstring_tokens: Interface to external world .
comment: """ Interface to external world. 
          This function does the input checks, preprocesses input and finally applies loss function.
          
          Parameters
          ----------
          scores_pos : tf.Tensor
              A tensor of scores assigned to positive statements.
          scores_neg : tf.Tensor
              A tensor of scores assigned to negative statements.
          
          Returns
          -------
          loss : tf.Tensor
              The loss value that must be minimized.
          """