733f571ff1c5297f798d2829bb4a6fc6e3f3170b,deeplift/models.py,Model,_set_scoring_mode_for_target_layer,#Model#,125

Before Change

                      +" layer but it is not an activation layer"
                      +", which seems odd...if doing regression, make"
                      +" sure to set the target layer to the last layer")
            deeplift.util.assert_is_type(final_activation_layer,
                                         layers.Activation,
                                         "final_activation_layer")
            final_activation_type = type(final_activation_layer).__name__

            if (final_activation_type == "Sigmoid"):
                scoring_mode=ScoringMode.OneAndZeros

After Change

                  +" classification)")
        scoring_mode=ScoringMode.OneAndZeros
        if (len(target_layer.get_output_layers())>0):
            if (len(target_layer.get_output_layers())>1):
                print("WARNING: the target layer"
                      +str(target_layer.get_name())
                      +" has multiple output layers"
                      +str(target_layer.get_output_layers()))
            else: 
                final_activation_layer = target_layer.get_output_layers()[0]
                if (deeplift.util.is_type(final_activation_layer,
                                          layers.Activation)==False):
                    print("\n\nWARNING!!! There is a layer after your target"
                          +" layer but it is not an activation layer"
                          +", which is unusual; double check you have set"
                          +" the target layer correctly.\n\n")
                scoring_mode=ScoringMode.OneAndZeros
        target_layer.set_scoring_mode(scoring_mode)    
    
    def save_to_yaml_only(self, file_name):
        raise NotImplementedError()    

Instances