TensorFlow1.x使用

import tensorflow as tf
from sklearn.datasets import load_breast_cancer

tf.reset_default_graph()

bc = load_breast_cancer()

x = tf.placeholder(tf.float32, [None, 30], name="x")
y = tf.placeholder(tf.int32, [None], name="y")
out = tf.layers.dense(x, 32, activation=tf.nn.relu)
out = tf.layers.dense(out, 32, activation=tf.nn.relu)
logits = tf.layers.dense(out, 2)
out = tf.nn.softmax(logits)
out = tf.argmax(out, axis=1, name="output")

loss = tf.losses.sparse_softmax_cross_entropy(y, logits)
loss = tf.identity(loss, "loss")

optimizer = tf.train.AdamOptimizer(0.0001).minimize(loss)

sess = tf.Session()
sess.run(tf.global_variables_initializer())

for i in range(1000):
    sess.run([optimizer], feed_dict={x: bc.data, y: bc.target})

# 保存模型
from aiworks_plugins.tf_plugins import save_tf_model_to_hdfs
save_tf_model_to_hdfs(sess, ["output", "loss"])