通常情况下,我们在训练网络时添加summary都是通过如下方式:
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| tf.scalar_summary(tags, values)
summary_op = tf.summary.merge_all() summary_writer = tf.summary.FileWriter(logdir, graph=sess.graph) summary_str = sess.run(summary_op) summary_writer.add_summary(summary_str, global_step)
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当我们自己想添加其他数据到TensorBoard的时候(例如验证时的loss等),这种方式显得太过繁琐,其实我们可以通过如下方式添加自定义数据到TensorBoard内显示。
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| summary_writer = tf.summary.FileWriter(logdir) summary = tf.Summary(value=[ tf.Summary.Value(tag="summary_tag", simple_value=0), tf.Summary.Value(tag="summary_tag2", simple_value=1), ])
summary_writer.add_summary(summary, step)
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或者:
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| summary_writer = tf.summary.FileWriter(LOGDIR) summary = tf.Summary() summary.value.add(tag="summary_tag", simple_value=0) summary.value.add(tag="summary_tag2", simple_value=1)
summary_writer.add_summary(summary, step)
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注意,这里的step只能是整数,如果是小数的话会自动转为整数类型。
下面给出一段完整的示例代码
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| import tensorflow as tf summary_writer = tf.summary.FileWriter('/tmp/test') summary = tf.Summary(value=[ tf.Summary.Value(tag="summary_tag", simple_value=0), tf.Summary.Value(tag="summary_tag2", simple_value=1), ]) summary_writer.add_summary(summary, 1)
summary = tf.Summary(value=[ tf.Summary.Value(tag="summary_tag", simple_value=1), tf.Summary.Value(tag="summary_tag2", simple_value=3), ]) summary_writer.add_summary(summary, 2)
summary_writer.close()
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显示效果如下所示:
参考资料:
[How to manually create a
tf.Summary()](http://stackoverflow.com/questions/37902705/how-to-manually-create-a-tf-summary)
更新记录
2017/3/15 更新标题,修改代码兼容TensorFlow1.0版本...