Tensorflow 分布式张量流张量森林

请告诉我，我是分布式处理的新手，我想知道如何使用分布式tensorforest来训练tensorforest模型？我了解神经网络是如何实现的，但我不了解tensorforest，它是一个使用tensorflow框架的随机林实现，我最近深入研究了这个主题。由于

TensorForestEstimator

源自

tf.contrib.learn.Estimator

，因此应该可以在分布式培训环境中使用它

我遇到的问题是如何正确配置设备分配。

TensorForestEstimator

的构造函数接受一个

设备赋值器

关键字参数

device\u assigner：控制如何将树分配给设备的对象实例。如果没有，将使用tensor_forest.RandomForestDeviceSigner。

文件不准确。默认值实际上是

tf.contrib.framework.VariableDeviceChooser

的一个实例

代码实例化了不带参数的

VariableDeviceChooser

，应该在没有参数服务器的情况下运行。这在单机环境中很好，但在分布式环境中则不然。我已尝试传递一个值

VariableDeviceChooser

，该值实例化为从

TF\u CONFIG

中的数据推断出的参数服务器数

这是我在培训操作期间启动会话时观察到的错误消息

  File "/home/ubuntu/.pyenv/versions/cmle-1_12-py-3_5/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1334, in _do_call
    return fn(*args)
  File "/home/ubuntu/.pyenv/versions/cmle-1_12-py-3_5/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1317, in _run_fn
    self._extend_graph()
  File "/home/ubuntu/.pyenv/versions/cmle-1_12-py-3_5/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1352, in _extend_graph
    tf_session.ExtendSession(self._session)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Cannot assign a device for operation device_dummy_0/Initializer/random_uniform/RandomUniform: Could not satisfy explicit device specification '' because the node {{colocation_node device_dummy_0/Initializer/random_uniform/RandomUniform}} was colocated with a group of nodes that required incompatible device '/job:ps/task:0/device:CPU:0'
Colocation Debug Info:
Colocation group had the following types and devices: 
IsVariableInitialized: CPU 
Assign: CPU 
Identity: CPU XLA_CPU 
VariableV2: CPU  
Mul: CPU XLA_CPU 
Add: CPU XLA_CPU 
Sub: CPU XLA_CPU 
RandomUniform: CPU XLA_CPU 
Const: CPU XLA_CPU 

Colocation members and user-requested devices:
  device_dummy_0/Initializer/random_uniform/shape (Const) 
  device_dummy_0/Initializer/random_uniform/min (Const) 
  device_dummy_0/Initializer/random_uniform/max (Const) 
  device_dummy_0/Initializer/random_uniform/RandomUniform (RandomUniform) 
  device_dummy_0/Initializer/random_uniform/sub (Sub) 
  device_dummy_0/Initializer/random_uniform/mul (Mul) 
  device_dummy_0/Initializer/random_uniform (Add) 
  device_dummy_0 (VariableV2) /job:ps/task:0/device:CPU:0   
  device_dummy_0/Assign (Assign) /job:ps/task:0/device:CPU:0
  device_dummy_0/read (Identity) /job:ps/task:0/device:CPU:0
  report_uninitialized_variables/IsVariableInitialized_1 (IsVariableInitialized) /job:ps/task:0/device:CPU:0  
  report_uninitialized_variables_1/IsVariableInitialized_1 (IsVariableInitialized) /job:ps/task:0/device:CPU:0
  save/Assign_1 (Assign) /job:ps/task:0/device:CPU:0

     [[{{node device_dummy_0/Initializer/random_uniform/RandomUniform}} = RandomUniform[T=DT_INT32, _class=["loc:@device_dummy_0"], dtype=DT_FLOAT, seed=0, seed2=0](device_dummy_0/Initializer/random_uniform/shape)]]```