用TensorFlow搭建cifar10神经网络

好的，下面是使用TensorFlow搭建cifar10神经网络的步骤：

1. 导入必要的库

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers

2. 加载cifar10数据集

(x_train, y_train), (x_test, y_test) = keras.datasets.cifar10.load_data()

3. 对数据进行预处理

x_train = x_train.astype("float32") / 255.0
x_test = x_test.astype("float32") / 255.0

4. 定义模型

model = keras.Sequential(
    [
        layers.Conv2D(32, (3, 3), activation="relu", input_shape=(32, 32, 3)),
        layers.MaxPooling2D(pool_size=(2, 2)),
        layers.Conv2D(64, (3, 3), activation="relu"),
        layers.MaxPooling2D(pool_size=(2, 2)),
        layers.Flatten(),
        layers.Dense(10),
    ]
)

5. 编译模型

model.compile(optimizer='adam',
              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
              metrics=['accuracy'])

6. 训练模型

history = model.fit(x_train, y_train, epochs=10, validation_data=(x_test, y_test))

7. 评估模型

test_loss, test_acc = model.evaluate(x_test, y_test, verbose=2)
print("Test accuracy:", test_acc)

以上就是搭建cifar10神经网络的步骤。