实现多层神经网络进行时装分类，遇到AttributeError: type object 'SingleNN' has no attribute 'model'

Question

实现多层神经网络进行时装分类遇到一个问题，不知道怎么解决

from tensorflow import keras
import tensorflow as tf
from tensorflow.keras import datasets, layers, models

# 构建双层神经网络去进行时装模型训练与预测
#  -读取数据集
# # # -建立神经网络模型
# # # -编译模型优化器、损失、准确率
# # # -进行fit训练
# # # -评估模型测试效果


class SingleNN(object):

    # 建立网络模型
    keras.Sequential([
        keras.layers.Flatten(input_shape=(28, 28)),
        keras.layers.Dense(128, activation=tf.nn.relu),
        keras.layers.Dense(10, activation=tf.nn.softmax)
    ])

    def __init__(self):

        # 返回两个元组

        (x_train, y_train), (x_test, y_test) = keras.datasets.fashion_mnist.load_data()

    def singlenn_compile(self):


        SingleNN.model.compile(optimizer=keras.optimizers.SGD(lr=0.01),
                               loss=keras.losses.sparse_categorical_crossentropy,
                               mmetrics=['accuracy'])
        return None

    def singlenn_fit(self):
        SingleNN.model.fit(self.x_train, self.y_train, epochs=5)

        return None

    def single_evalute(self):
        test_loss, test_acc = SingleNN.model.evaluate(self.x_train, self.y_train)

        print(test_loss, test_acc)

        return None

if __name__ == '__main__':

    snn = SingleNN()

    snn.singlenn_compile()

    snn.singlenn_fit()

    snn.singlenn_evalute()

    pass