Question

下面的代码在教程中运行正常，但是在本地运行时出错。有安装错误或其他错误吗？请帮忙。这是该教程的链接： https://colab.research.google.com/notebooks/mlcc/tensorflow_programming_concepts.ipynb?utm_source=mlcc&utm_campaign=colab-external&utm_medium=referral&utm_content=tfprogconcepts-colab&hl=en#scrollTo=Md8ze8e9geMi
和代码：

import tensorflow as tf

#create a graph 
g = tf.Graph()

#establish the graph as the default graph 
with g.as_default():
 x = tf.constant(8, name = "x_const")
 y = tf.constant(5, name = "y_const")
 my_sum = tf.add(x,y, name = "x_y_sum")

#create the session
#this runs the default graph
with tf.Session() as sess:
 print(my_sum.eval())

下面是发生的错误：

gunjan@gunjan-Inspiron-3558:~/Desktop$ python tf1.py 
/home/gunjan/anaconda3/lib/python3.5/site- 
packages/h5py/__init__.py:34: FutureWarning: Conversion of the second 
argument of issubdtype from `float` to `np.floating` is deprecated. In 
future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
2018-08-20 22:10:41.619062: I 
tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports 
instructions that this TensorFlow binary was not compiled to use: AVX2 
FMA
Traceback (most recent call last):
File "tf1.py", line 15, in <module>
print(my_sum.eval())
File "/home/gunjan/anaconda3/lib/python3.5/site- 
packages/tensorflow/python/framework/ops.py", line 680, in eval
return _eval_using_default_session(self, feed_dict, self.graph, 
session)
File "/home/gunjan/anaconda3/lib/python3.5/site- 
packages/tensorflow/python/framework/ops.py", line 4942, in 
_eval_using_default_session
raise ValueError("Cannot use the default session to evaluate tensor: "
ValueError: Cannot use the default session to evaluate tensor: the 
tensor's graph is different from the session's graph. Pass an explicit 
session to `eval(session=sess)`.

Answer 1

问题是您创建了一个图形（require(reshape2) require(ggplot2) require(dplyr) require(tidyr) #setting up labels -- find out why italics expression isn't working?? Fig.labels<-c(expression(paste(italic("C. ret"), "-0d")), expression(paste(italic("C. ret"), "-4d")), expression(paste(italic("C. ret"), "-14d")), expression(paste(italic("M. pan"), "-4d")), expression(paste(italic("M. pan"), "-14d"))) A1_0d_ret<-rnorm(1:100,20) A2_4d_ret<-rnorm(1:100,18) A3_14d_ret<-rnorm(1:100,30) A4_4d_pan<-rnorm(1:100,7) A5_14d_pan<-rnorm(1:100,40) data<-data.frame(A1_0d_ret, A2_4d_ret, A3_14d_ret, A4_4d_pan, A5_14d_pan) long.data<-melt(data) long.data_<-separate(data = long.data, col = variable, into = c("group", "treatment", "species"), sep = "_", remove=FALSE) ggplot(long.data_, aes(x=treatment, y=log(value), group=variable))+ geom_boxplot(outlier.shape = NA, width=0.2 )+ scale_x_discrete("Never mind weird plot", labels=Fig.labels)+ theme_classic()），并且正在另一个图形（g）中执行代码。如果不需要两个图，则可以使用sess：

sess

Answer 2

要使其正常工作，您可以按照错误消息的建议显式地通过会话：

print(my_sum.eval(session=sess))

要了解为什么它不能完全按照本教程的规定工作，可以先将Python和TensorFlow的版本与本教程中使用的版本进行比较。

import tensorflow as tf
import platform
print("Python version: ", platform.python_version())
print("TensorFlow version", tf.__version__)

对于您链接的colab环境，将打印：

Python version:  2.7.14
TensorFlow version 1.10.0

编辑

再看看您的代码示例，这不是版本兼容性的问题。问题是您的教程副本没有正确保留缩进。第二个with块需要放在第一个块中。

# Establish the graph as the "default" graph.
with g.as_default():
  # ...

  # Now create a session.
  # The session will run the default graph.
  with tf.Session() as sess:
    print(my_sum.eval())

这可确保将g用作会话的默认图形，而不是像MatthewScarpino那样创建一个新图形来指出您的缩进版本。

Answer 3

如果您显式创建/使用Graph对象而不是使用默认图形，则需要（a）将图形对象传递给Session构造函数，或者（b）创建会话在图上下文中。

graph = tf.Graph()
with graph.as_default():
    build_graph()

with tf.Session(graph=graph) as sess:
    do_stuff_with(sess)

或

graph = tf.Graph()
with graph.as_default():
    build_graph()

    with tf.Session() as sess:
        do_stuff_with(sess)

张量评估错误

3 个答案: