import tensorflow.keras.backend as K

import tensorflow.keras as keras

import tensorflow as tf

def dice_loss(y_true, y_pred):

    def dice_coeff():

        smooth = 1

        y_true_f = tf.reshape(y_true, [-1])

        y_pred_f = tf.reshape(y_pred, [-1])

        intersection = tf.reduce_mean(y_true_f * y_pred_f)

        score = (2. * intersection + smooth) / (tf.reduce_mean(y_true_f) + tf.reduce_mean(y_pred_f) + smooth)

        return score

    return 1 - dice_coeff()

def bce_dice_loss(y_true, y_pred):

    losses = keras.losses.binary_crossentropy(y_true, y_pred) + dice_loss(y_true, y_pred)

    return losses