AttributeError：模塊'tensorflow.keras.models'沒有屬性'sequential'

Question

嗨，我一直在嘗試運行此代碼以進行手寫數字識別，但它給了我這個錯誤AttributeError: module 'tensorflow.keras.models' has no attribute 'sequential'

import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()

x_train = tf.keras.utils.normalize(x_train, axis=1)
x_test = tf.keras.utils.normalize(x_test, axis=1)

model = tf.keras.models.sequential()
model.add(tf.keras.layers.flatten(input_shape=(28, 28)))
model.add(tf.keras.layers.dense(128, activation='relu'))
model.add(tf.keras.layers.dense(128, activation='relu'))
model.add(tf.keras.layers.dense(10, activation='softmax'))

model.compile(optimize='adam', loss='sparse_categorical_crossentropy',metrics =['accuracy'])

model.fit(x_train, y_train, epochs=3)
loss, accuracy = model.evaluate(x_test, y_test)
print(accuracy)
print(loss)```

what should i do?

Answer 1

您擁有的外殼不正確，這應該適用於您想要的 model。

model = tf.keras.models.Sequential()
model.add(tf.keras.layers.Flatten(input_shape=(28, 28)))
model.add(tf.keras.layers.Dense(128, activation='relu'))
model.add(tf.keras.layers.Dense(128, activation='relu'))
model.add(tf.keras.layers.Dense(10, activation='softmax'))