normalization_for_input_of_gan

def normalization(data):
    data = data - 127.5
    data = data / 127.5
    return data

fake = G(z)
def unnormalization(data):
    data = data * 127.5
    data = data + 127.5
    return data
visual_image = unnormalization(fake)

def normalization(self):
        """
        Normalizes our data, to have a mean of 0 and sdt of 1
        """
        self.mean = np.mean(self.x_train)
        self.std = np.std(self.x_train)
        self.x_train = (self.x_train - self.mean) / self.std
        self.x_val = (self.x_val - self.mean) / self.std
        self.x_test = (self.x_test - self.mean) / self.std

def unnormalization(self,fake):
        """
        Normalizes our data, to have a mean of 0 and sdt of 1
        """
        self.mean = np.mean(self.x_train)
        self.std = np.std(self.x_train)
        visual_image = fake*self.std + self.mean