如何从共享变量支持的theano张量变量中获取值? [英] How to get value from a theano tensor variable backed by a shared variable?

问题描述

我有一个通过转换共享变量创建的theano张量变量.如何提取原始值或强制转换值? (我需要这样做，因此不必携带原始的shared/numpy值.)

I have a theano tensor variable created from casting a shared variable. How can I extract the original or casted values? (I need that so I don't have to carry the original shared/numpy values around.)

>>> x = theano.shared(numpy.asarray([1, 2, 3], dtype='float'))
>>> y = theano.tensor.cast(x, 'int32')
>>> y.get_value(borrow=True)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'TensorVariable' object has no attribute 'get_value'
# whereas I can do this against the original shared variable
>>> x.get_value(borrow=True)
array([ 1.,  2.,  3.])

推荐答案

get_value仅适用于共享变量. TensorVariables是通用表达式，因此可能需要额外的输入才能确定其值(假设您设置了y = x + z，其中z是另一个张量变量.您需要先指定z才能计算y).您可以创建一个函数来提供此输入，也可以使用eval方法在字典中提供它.

get_value only works for shared variables. TensorVariables are general expressions and thus potentially need extra input in order to be able to determine their value (Imagine you set y = x + z, where z is another tensor variable. You would need to specify z before being able to calculate y). You can either create a function to provide this input or provide it in a dictionary using the eval method.

根据您的情况，y仅取决于x，因此您可以这样做

In your case, y only depends on x, so you can do

import theano
import theano.tensor as T

x = theano.shared(numpy.asarray([1, 2, 3], dtype='float32'))
y = T.cast(x, 'int32')
y.eval()

您应该会看到结果

array([1, 2, 3], dtype=int32)

(例如，在y = x + z情况下，您必须执行y.eval({z : 3.}))

(And in the case y = x + z, you would have to do y.eval({z : 3.}), for example)

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