无法将函数转换为张量或操作。 Tensorflow错误

Question

所以我得到这个错误tensorflow（1.2）（蟒蛇3）：

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.) 

而这里的代码：

from tensorflow.examples.tutorials.mnist import input_data 
mnist = input_data.read_data_sets("/tmp/data/", one_hot=True) 

import tensorflow as tf 


learning_rate = 0.01 
training_iteration = 30 
batch_size = 100 
display_step = 2 


x = 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 graph 

with 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})) 

我是新来tensorflow。我“得到了” https://www.youtube.com/watch?v=2FmcHiLCwTU&list=PL2-dafEMk2A7EEME489DsI468AB0wQsMV

所以这是他（指人在教程（斯拉吉拉瓦尔））采用tensorflow的旧版本，从这个视频（教程）这段代码为什么有些代码是这样的不同（例如）：

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

更多信息：

我试图运行与Python（2.7相同的代码）（对于Python 2.7），当然我已经下载tensorflow但它给了我同样的错误。

任何帮助都会很好，Thx提前。

Answer 1

更换merged_summary_op = tf.summary.merge_all与merged_summary_op = tf.summary.merge_all()

这实际上什么错误消息告诉你的是：TypeError: Can not convert a function into a Tensor or Operation - >tf.summary.merge_all是一个函数，而不是一个张量或操作，你不能sess.run()运行它，相反tf.summary.merge_all()