用户在CNTK python中定义了图层

时间:2017-05-29 18:11:25

标签: python machine-learning cntk

我正在尝试使用python接口创建一个在CNTK中使用的自定义图层。我正在关注this guide,但是在我班级的__init__中一直抛出一个TypeError异常。请注意,我只是在链接指南中复制粘贴了该示例。

import cntk as C
import numpy as np

class MySigmoid(UserFunction):
    def __init__(self, arg, name='MySigmoid'):
        super(MySigmoid, self).__init__([arg], name=name)

    def forward(self, argument, device=None, outputs_to_retain=None):
        sigmoid_x = 1 / (1 + np.exp(-argument))
        return sigmoid_x, sigmoid_x

    def backward(self, state, root_gradients):
        sigmoid_x = state
        return root_gradients * sigmoid_x * (1 - sigmoid_x)

    def infer_outputs(self):
        return [output_variable(self.inputs[0].shape, self.inputs[0].dtype,
            self.inputs[0].dynamic_axes)]

    @staticmethod
    def deserialize(inputs, name, state):
        return MySigmoid(inputs[0], name)
model = C.layers.Sequential(C.layers.Dense(10), C.user_function(layers_extensions.MySigmoid(3)))

这是我得到的错误:

  File "...\layers_extensions.py", line 30, in __init__
    super(MySigmoid, self).__init__([arg], name=name)
  File "c:\repos\cntk\bindings\python\cntk\ops\functions.py", line 1286, in __init__
    super(UserFunction, self).__init__(inputs, name)
  File "c:\repos\cntk\bindings\python\cntk\ops\functions.py", line 109, in __init__
    super(Function, self).__init__(*args, **kwargs)
  File "c:\repos\cntk\bindings\python\cntk\cntk_py.py", line 1698, in __init__
    this = _cntk_py.new_Function(_self, *args)
TypeError: cannot convert list element to CNTK::Variable

我试图谷歌这个错误但没有出现。你能帮助我吗?

1 个答案:

答案 0 :(得分:1)

出于某种原因,CNTK将argument方法中的forward(...)参数作为列表传递,即使它是单个参数。我最终通过从列表中获取第一个来使其工作。您将找到工作示例here