Python 2.7 作为变量传递的Tensorflow内置函数不'；不行。我怎样才能让它工作？

当我运行下面的代码时

import numpy as np
import tensorflow as tf

class Config:
    activation = tf.nn.tanh

class Sample:

    def function(self, x):
        return self.config.activation(x)

    def __init__(self, config):
        self.config = config

if __name__ == "__main__":
    with tf.Graph().as_default():
        config = Config()
        sample = Sample(config)
        with tf.Session() as sess:
            a = tf.constant(2.0)
            print sess.run(sample.function(a))

我收到以下错误消息：

Traceback (most recent call last):
  File "test.py", line 27, in <module>
    print sess.run(sample.function(a))
  File "test.py", line 11, in function
    return self.config.activation(x)
  File "/Users/byungwookang/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 2019, in tanh
    with ops.name_scope(name, "Tanh", [x]) as name:
  File "/Users/byungwookang/anaconda/lib/python2.7/contextlib.py", line 17, in __enter__
    return self.gen.next()
  File "/Users/byungwookang/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 4185, in name_scope
    with g.as_default(), g.name_scope(n) as scope:
  File "/Users/byungwookang/anaconda/lib/python2.7/contextlib.py", line 17, in __enter__
    return self.gen.next()
  File "/Users/byungwookang/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2839, in name_scope
    if name:
  File "/Users/byungwookang/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 541, in __nonzero__
    raise TypeError("Using a `tf.Tensor` as a Python `bool` is not allowed. "
TypeError: Using a `tf.Tensor` as a Python `bool` is not allowed. Use `if t is not None:` instead of `if t:` to test if a tensor is defined, and use TensorFlow ops such as tf.cond to execute subgraphs conditioned on the value of a tensor.

它给

0.964027580076
0.964027580076

---

我很好奇为什么不能将tensorflow内置函数作为变量传递（如上面第一段代码中所做的），以及是否有办法避免上述错误。特别是在第二段代码中，numpy函数作为变量很好地传递，我觉得tensorflow不允许这样做似乎很奇怪

你的东西不起作用的原因是因为在你的情况下

print sample.function # <bound method Sample.function of <__main__.Sample instance at 0xXXX>>
print tf.nn.tanh      # <function tanh at 0xXXX>

---

这很奇怪！奇怪的是，该代码在tensorflow中不起作用，但在numpy中起作用。@Salvardor Dali非常感谢您提出的解决方案。我上面的代码是一个玩具代码，用来解释我在一个更大的代码中遇到的问题。虽然您建议的代码确实有效，但我很好奇是否有一种方法可以使我的tensorflow代码以更类似于我的numpy代码的方式工作。而且，我很难理解为什么会收到这样的错误消息。

print sample.function # <bound method Sample.function of <__main__.Sample instance at 0xXXX>>
print tf.nn.tanh      # <function tanh at 0xXXX>

import numpy as np
import tensorflow as tf

def config():
    return {'activation': tf.nn.tanh}

class Sample:
    def function(self, x):
        return self.config['activation'](x)

    def __init__(self, config):
        self.config = config

if __name__ == "__main__":
    with tf.Graph().as_default():  # this is also not needed
        sample = Sample(config())
        with tf.Session() as sess:
            a = tf.constant(2.0)
            print sess.run(sample.function(a))