提取Tensorboard直方图数据

import tensorflow as tf

# 指定TensorBoard事件文件路径
log_dir = 'path_to_event_file'

# 创建一个事件文件写入器
writer = tf.summary.FileWriter(log_dir)

# 加载事件文件
writer.add_graph(tf.get_default_graph())

import tensorflow as tf

# 记录直方图数据
with tf.name_scope('histogram_example'):
    weights = tf.Variable(tf.random_normal([100]), name='weights')
    biases = tf.Variable(tf.zeros([100]), name='biases')
    histogram_weights = tf.summary.histogram('weights', weights)
    histogram_biases = tf.summary.histogram('biases', biases)

import tensorflow as tf

# 定义会话
with tf.Session() as sess:
    # 初始化变量
    sess.run(tf.global_variables_initializer())
    
    # 合并所有直方图数据
    merged = tf.summary.merge_all()
    
    # 创建事件文件写入器
    writer = tf.summary.FileWriter(log_dir, sess.graph)
    
    # 运行会话并写入事件文件
    for step in range(num_steps):
        # 执行训练操作
        sess.run(train_op)
        
        # 记录直方图数据
        summary = sess.run(merged)
        writer.add_summary(summary, global_step=step)

import tensorflow as tf

# 加载事件文件
log_dir = 'path_to_event_file'
for summary in tf.train.summary_iterator(log_dir):
    for value in summary.summary.value:
        if value.HasField('histo'):
            print(value.tag)
            print(value.histo)