AI开发平台MODELARTS-TensorFlow:训练模型（keras接口）

时间：2024-09-05 08:29:59

训练模型（keras接口）

  
   
     
     
       from keras.models import Sequential
model = Sequential()
from keras.layers import Dense
import tensorflow as tf

# 导入训练数据集
mnist = tf.keras.datasets.mnist
(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

print(x_train.shape)

from keras.layers import Dense
from keras.models import Sequential
import keras
from keras.layers import Dense, Activation, Flatten, Dropout

# 定义模型网络
model = Sequential()
model.add(Flatten(input_shape=(28,28)))
model.add(Dense(units=5120,activation='relu'))
model.add(Dropout(0.2))

model.add(Dense(units=10, activation='softmax'))

# 定义优化器，损失函数等
model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

model.summary()
# 训练
model.fit(x_train, y_train, epochs=2)
# 评估
model.evaluate(x_test, y_test)

      

    

  
 