TensorFlow主管防止變量賦值：圖形定稿，並且不能被修改

Question

此代碼工作正常：

import tensorflow as tf 
x = tf.Variable(initial_value=0) 

with tf.Session() as session: 
    print session.run(x.assign(1)) 

但這個代碼失敗：

import tensorflow as tf 
x = tf.Variable(initial_value=0) 
supervisor = tf.train.Supervisor(logdir="/tmp") 

with tf.Session() as session: 
    print session.run(x.assign(1)) 

唯一的區別是tf.train.Supervisor的實例。請注意，我們甚至不使用主管創建管理會話。

的錯誤是：保持

python tf_supervisor_freeze.py 
Traceback (most recent call last): 
    File "tf_supervisor_freeze.py", line 6, in <module> 
    print session.run(x.assign(1)) 
    File "<virtual_env_path>/lib/python2.7/site-packages/tensorflow/python/ops/variables.py", line 522, in assign 
    return state_ops.assign(self._variable, value, use_locking=use_locking) 
    File "<virtual_env_path>/lib/python2.7/site-packages/tensorflow/python/ops/gen_state_ops.py", line 47, in assign 
    use_locking=use_locking, name=name) 
    File "<virtual_env_path>/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 491, in apply_op 
    preferred_dtype=default_dtype) 
    File "<virtual_env_path>/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 702, in internal_convert_to_tensor 
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) 
    File "<virtual_env_path>/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 110, in _constant_tensor_conversion_function 
    return constant(v, dtype=dtype, name=name) 
    File "<virtual_env_path>/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 103, in constant 
    attrs={"value": tensor_value, "dtype": dtype_value}, name=name).outputs[0] 
    File "<virtual_env_path>/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2286, in create_op 
    self._check_not_finalized() 
    File "<virtual_env_path>/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2009, in _check_not_finalized 
    raise RuntimeError("Graph is finalized and cannot be modified.") 
RuntimeError: Graph is finalized and cannot be modified. 

Process finished with exit code 1 

錯誤如果tf.train.Supervisor(logdir="/tmp", summary_op=None, saver=None)用於禁用一些主管的服務。

這個問題是由Github上的其他人提出的，但沒有提供答案;該請求改爲在StackOverflow上引發問題。唯一相關的StackOverflow question似乎沒有解決這個特定情況。

Answer 1

就像錯誤說的那樣，當圖形完成時你不能修改圖形。

RuntimeError（ 「圖形被最終確定，並且不能修改。」）

當執行該代碼tf.train.Supervisor()，曲線圖將最終確定。您可以使用版本1.0的tensorflow中的路徑/tensorflow/python/training/supervisor.py檢查它的代碼。

而且你會發現這一點：

# The graph is not allowed to change anymore. 
graph.finalize() 

所以你不能Supervisor()修改後的圖。

Answer 2

我無法解釋爲什麼，但我找到了解決辦法。這工作：

import tensorflow as tf 
x = tf.Variable(initial_value=0) 
a = x.assign(1) 
supervisor = tf.train.Supervisor(logdir="/tmp") 

with tf.Session() as session: 
    print session.run(a) 

所有已做的是創造的導師（即a = x.assign(1)）之前賦值操作創建移動。看起來主管確實會凍結圖表，以防止在創建主管之後創建或更準確地使用新操作。