以下兩種方式都不好使用：目前只是找到原因，等我找到方案再來完善。

From your error message, it looks like you are using IPython. One pitfall when using IPython to build a TensorFlow model is that functions like?tf.merge_all_summaries()?will remember every summary created in the current session, including cells that failed with an error. This is a result of TensorFlow using a?default graph?to collect all of the operations, summaries, etc. that are created in a process, unless you specify the graph explicitly. I suspect that your call to?tf.merge_all_summaries()?is returning more than the three histogram summaries that you created in your code, and the older ones will have a dependency on a?previously created?placeholder.

There are two main ways that you could fix that. The simplest is to explicitly merge the summaries, rather than using?tf.merge_all_summaries():

weights_summary = tf.histogram_summary("weights", W)

biases_summary = tf.histogram_summary("biases", b)

y_summary = tf.histogram_summary("y", y)

merged = tf.merge_summary([weights_summary, biases_summary, y_summary])

An alternative would be to set an?explicit default graph?before constructing your model. This is awkward if you want to split your model across multiple IPython cells, but should also work:

# Sets a new default graph, and stores it in `g`.

with tf.Graph().as_default() as g:

x = tf.placeholder(tf.float32, [None, 784])

# ...

# Summaries are added to `g`.

_ = tf.histogram_summary("weights", W)

_ = tf.histogram_summary("biases", b)

_ = tf.histogram_summary("y", y)

# ...

# `merged` contains only summaries from `g`.

merged = tf.merge_all_summaries()

總結(jié)

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