我在使用tensorflow (1.2) 和python 3时遇到了这个错误：

WARNING:tensorflow:Passing a `GraphDef` to the SummaryWriter is deprecated. Pass a `Graph` object instead, such as `sess.graph`.Traceback (most recent call last):  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 267, in __init__    fetch, allow_tensor=True, allow_operation=True))  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 2584, in as_graph_element    return self._as_graph_element_locked(obj, allow_tensor, allow_operation)  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 2673, in _as_graph_element_locked    % (type(obj).__name__, types_str)) TypeError: Can not convert a function into a Tensor or Operation.During handling of the above exception, another exception occurred:Traceback (most recent call last):  File "/home/theshoutingparrot/Desktop/Programming/Python/MachineLearningPY/Tensorflow/NumberClassifier.py", line 54, in <module>    summary_str = sess.run(merged_summary_op, feed_dict={x: batch_xs, y: batch_ys})  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 789, in run    run_metadata_ptr)   File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 984, in _run     self._graph, fetches, feed_dict_string, feed_handles=feed_handles)  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 410, in __init__    self._fetch_mapper = _FetchMapper.for_fetch(fetches)  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 238, in for_fetch    return _ElementFetchMapper(fetches, contraction_fn)  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 271, in __init__    % (fetch, type(fetch), str(e))) TypeError: Fetch argument <function merge_all at 0x7f7d0f3d8620> has invalid type <class 'function'>, must be a string or Tensor. (Can not convert a function    into a Tensor or Operation.)

这是代码：

from tensorflow.examples.tutorials.mnist import input_datamnist = input_data.read_data_sets("/tmp/data/", one_hot=True)import tensorflow as tflearning_rate = 0.01training_iteration = 30batch_size = 100display_step = 2x = tf.placeholder("float", [None, 784])y = tf.placeholder("float", [None, 10])W = tf.Variable(tf.zeros([784, 10]))b = tf.Variable(tf.zeros([10]))with tf.name_scope("Wx_b") as scope:    model = tf.nn.softmax(tf.matmul(x, W) + b)w_h = tf.summary.histogram("weights", W) b_h = tf.summary.histogram("biases", b) with tf.name_scope("cost_function") as scope:   cost_function = -tf.reduce_sum(y*tf.log(model))   tf.summary.scalar("cost_function", cost_function)with tf.name_scope("train") as scope:    optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost_function)init = tf.global_variables_initializer()  #tf.initialize_all_variables()merged_summary_op = tf.summary.merge_all#Launch the graphwith tf.Session() as sess:    sess.run(init)    summary_writer = tf.summary.FileWriter('/home/theshoutingparrot/work/logs', graph_def=sess.graph_def)    for iteration in range(training_iteration):        avg_cost = 0.        total_batch = int(mnist.train.num_examples/batch_size)      for i in range(total_batch):        batch_xs, batch_ys = mnist.train.next_batch(batch_size)        sess.run(optimizer, feed_dict={x: batch_xs, y: batch_ys})        avg_cost += sess.run(cost_function, feed_dict={x: batch_xs, y: batch_ys})/total_batch        summary_str = sess.run(merged_summary_op, feed_dict={x: batch_xs, y: batch_ys})        summary_writer.add_summary(summary_str, iteration*total_batch + i)    if iteration % display_step == 0:        print("Iteration", '%04d' % (iteration + 1), "cost=", "{:.9f}".format(avg_cost))    print("Tuning completed!")    predictions = tf.equal(tf.argmax(model,1), tf.argmax(y, 1))    accuracy = tf.reduce_mean(tf.cast(predictions, "float"))    print("Accuracy:", accuracy.eval({x: mnist.test.images, y: mnist.test.labels}))

我是tensorflow的新手。这段代码是我从这个视频（教程）中获取的 https://www.youtube.com/watch?v=2FmcHiLCwTU&list=PL2-dafEMk2A7EEME489DsI468AB0wQsMV

教程中的那个人（Siraj Raval）使用的是tensorflow的旧版本，所以代码有些不同，比如：

w_h = tf.histogram_summary("weights", W) => w_h = tf.summary.histogram("weights", W)

更多信息：

我尝试用python (2.7) 运行相同的代码（当然我已经下载了适用于Python 2.7的tensorflow），但它仍然显示相同的错误。

任何帮助都将不胜感激，提前谢谢。

回答：

将 merged_summary_op = tf.summary.merge_all 替换为 merged_summary_op = tf.summary.merge_all()

这实际上就是错误信息告诉你的：TypeError: Can not convert a function into a Tensor or Operation -> tf.summary.merge_all 是一个函数，不是张量或操作，你不能用 sess.run() 运行它，而 tf.summary.merge_all() 则可以