model

model.py

def fun_table(x,output):
    x = Conv2D(128, (1, 1), activation = 'relu', name='conv7_table')(x)
    concatenated = Concatenate()([x, output])
    concatenated = Concatenate()([concatenated, output])
    x = UpSampling2D(size=(2, 2))(concatenated)
    x = UpSampling2D(size=(2, 2))(x)
    x = UpSampling2D(size=(2, 2))(x)
    x = UpSampling2D(size=(2, 2))(x)

    last = tf.keras.layers.Conv2DTranspose(3, 3, strides=2,padding='same', name='table_output')     
    x = last(x)
    return x