TensorFlow图结构解析

import numpy as npimport tensorflow as tfimport osfrom tensorflow
.python.framework import opsops.reset_default_graph()# 创建计算图sess = tf.Session()
# 创建数据x_vals = np.array([1., 3., 5., 7., 9.])# 创建占位符x_data = tf.placeholder(tf.float32)
# 创建参数m = tf.constant(3.)# 创建操作prod = tf.multiply(x_data, m)
# 运行for x_val in x_vals:    print(sess.run(prod, feed_dict={x_data: x_val}))'''
3.09.015.021.027.0'''# 设置tensorboard可视化所需要的数据merged = tf.summary.merge_all()if not os
.path.exists('tensorboard_logs/'):    os.makedirs('tensorboard_logs/')my_writer = tf.summary
.FileWriter('tensorboard_logs/', sess.graph).flush()1.2.3.4.5.6.7.8.9.10.11.12.13.14.15.16.
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