3ec1dac0608e511d4cf28e93a3fb908bbabceac5,nn/loss.py,LossFunction,set_loss_type,#LossFunction#Any#,15

Before Change

    def set_loss_type(self, type_str):
        // TODO raise an error if type_str is not a supported type of loss
        // and give support for typo error
        if type_str == "CrossEntropy":
            self.data_loss_fun = cross_entropy
        elif type_str == "Dice":
            self.data_loss_fun = dice
        elif type_str == "GDSC":
            self.data_loss_fun = GDSC_loss
        elif type_str == "SensSpec":
            self.data_loss_fun = sensitivity_specificity_loss

    def set_regularisation_type(self, type_str):
        if type_str == "L2":
            self.reg_loss_fun = l2_reg_loss

After Change

                              "Dice": dice,
                              "GDSC": GDSC_loss,
                              "SensSpec": sensitivity_specificity_loss}
        if type_str in accepted_functions.keys():
            self.data_loss_fun = accepted_functions[type_str]
        else:
            edit_distances = {}
            for loss_name in accepted_functions.keys():
                edit_distance = damerau_levenshtein_distance(loss_name, type_str)
                if edit_distance <= 2:
                    edit_distances[loss_name] = edit_distance
            if edit_distances:
                guess_at_correct_spelling = min(edit_distances, key=edit_distances.get)
                raise ValueError(("By "{0}", did you mean "{1}"?\n "
                                  ""{0}" is not a valid loss.").format(type_str, guess_at_correct_spelling))
            else:
                raise ValueError("Loss type "%s" is not found." % type_str)


                // if type_str == "CrossEntropy":
                //     self.data_loss_fun = cross_entropy
                // elif type_str == "Dice":
                //     self.data_loss_fun = dice
                // elif type_str == "GDSC":
                //     self.data_loss_fun = GDSC_loss
                // elif type_str == "SensSpec":
                //     self.data_loss_fun = sensitivity_specificity_loss

    def set_regularisation_type(self, type_str):
        if type_str == "L2":
            self.reg_loss_fun = l2_reg_loss

Instances