parameters: (self, examples)
return_statement: return result
docstring: Add operations to compute predictions by the model.
  
      If logistic_loss is being used, predicted probabilities are returned.
      Otherwise, (raw) linear predictions (w*x) are returned.
  
      Args:
        examples: Examples to compute predictions on.
  
      Returns:
        An Operation that computes the predictions for examples.
  
      Raises:
        ValueError: if examples are not well defined.
docstring_summary: Add operations to compute predictions by the model.
docstring_tokens: Add operations to compute predictions by the model .
function: def predictions(self, examples):
      """Add operations to compute predictions by the model.
  
      If logistic_loss is being used, predicted probabilities are returned.
      Otherwise, (raw) linear predictions (w*x) are returned.
  
      Args:
        examples: Examples to compute predictions on.
  
      Returns:
        An Operation that computes the predictions for examples.
  
      Raises:
        ValueError: if examples are not well defined.
      """
      self._assertSpecified(
          ['example_weights', 'sparse_features', 'dense_features'], examples)
      self._assertList(['sparse_features', 'dense_features'], examples)
  
      result = self._linear_predictions(examples)
      if self._options['loss_type'] == 'logistic_loss':
        # Convert logits to probability for logistic loss predictions.
        with name_scope('sdca/logistic_prediction'):
          result = math_ops.sigmoid(result)
      return result
function_tokens: def predictions ( self , examples ) : self . _assertSpecified ( [ 'example_weights' , 'sparse_features' , 'dense_features' ] , examples ) self . _assertList ( [ 'sparse_features' , 'dense_features' ] , examples ) result = self . _linear_predictions ( examples ) if self . _options [ 'loss_type' ] == 'logistic_loss' : # Convert logits to probability for logistic loss predictions. with name_scope ( 'sdca/logistic_prediction' ) : result = math_ops . sigmoid ( result ) return result