7db45bfb7b7486e08faa6c29f1e2600159151c1d,src/models.py,PyTorchUNet,__init__,#PyTorchUNet#Any#Any#Any#,47

Before Change

                                    **architecture_config["optimizer_params"])
        dice_loss = partial(multiclass_dice_loss,
                            excluded_classes=[0])
        loss_function = partial(mixed_dice_cross_entropy_loss,
                                dice_loss=dice_loss,
                                cross_entropy_loss=multiclass_segmentation_loss)
        self.loss_function = [("mask", loss_function, 1.0)]
        self.callbacks = callbacks_unet(self.callbacks_config)

    def fit(self, datagen, validation_datagen=None, meta_valid=None):

After Change

class PyTorchUNet(Model):
    def __init__(self, architecture_config, training_config, callbacks_config):
        super().__init__(architecture_config, training_config, callbacks_config)
        self.activation_func = self.architecture_config["model_params"]["activation"]
        self.set_model()
        self.set_loss()
        self.weight_regularization = weight_regularization_unet
        self.optimizer = optim.Adam(self.weight_regularization(self.model, **architecture_config["regularizer_params"]),

Instances