mnist数字识别权重举证获取代码

回答: 下面是获取MNIST数字识别模型权重的代码示例：

import tensorflow as tf
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense

# 加载MNIST数据集
(x_train, y_train), (x_test, y_test) = mnist.load_data()

# 数据预处理
x_train = x_train.reshape(60000, 784)
x_test = x_test.reshape(10000, 784)
x_train = x_train.astype('float32')
x_test = x_test.astype('float32')
x_train /= 255
x_test /= 255

# 将标签进行one-hot编码
y_train = tf.one_hot(y_train, depth=10)
y_test = tf.one_hot(y_test, depth=10)

# 构建模型
model = Sequential()
model.add(Dense(512, activation='relu', input_shape=(784,)))
model.add(Dense(10, activation='softmax'))

# 编译模型
model.compile(optimizer='adam',
              loss='categorical_crossentropy',
              metrics=['accuracy'])

# 训练模型
model.fit(x_train, y_train, epochs=10, batch_size=128, validation_data=(x_test, y_test))

# 获取模型权重
weights = model.get_weights()

以上代码使用TensorFlow来构建一个简单的MNIST数字识别模型并进行训练。最后，我们可以使用`model.get_weights()`来获取模型的权重信息。