Thanks, Fred.
On Thu, Aug 10, 2017 at 6:41 PM, Frédéric Bastien <
frederic.bast...@gmail.com> wrote:
> The problem is smat(x)
>
> It return list of list of Theano variable. This isn't a Theano variable
> itself. You can have Theano contact all of this correctly to make a new
> corresponding Theano variable with:
>
> v,w=nlin.eigh(theano.tensor.stacklists(smat(x)))
>
> Fred
>
> On Tue, Aug 1, 2017 at 7:37 AM Jyotiranjan Beuria <
> jyotiranjan.beu...@gmail.com> wrote:
>
>> Hi All,
>>
>> I am trying to calculate the derivative of a function that
>> depends on eigenvalues of a matrix. I am new to Theano.
>> Here is a snippet of the code.
>> import numpy as np
>>
>> import theano
>> import theano.tensor as T
>> import theano.tensor.nlinalg as nlin
>>
>> def myFun(X,a=2):
>> s=T.dmatrix('s')
>> x=T.dvector('x')
>> a=T.dscalar('a')
>> def smat(x):
>> return [[x[0]**2,x[1],x[2]],
>> [x[1]**2,a*x[1],a*X[0]],
>> [x[2]**2,x[0],a*x[1]]]
>> v,w=nlin.eigh(smat(x))
>> TG=T.grad(v,x)
>> Eigen,Grad = theano.function([x], [v,TG],allow_input_downcast=True )
>>
>> ev=Eigen(X)
>> der=Grad(X)
>> print ev,der
>>
>> myFun([2,3,5])
>>
>> Can anyone help me to solve this problem?
>>
>> Regards,
>> Jyotiranjan
>>
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--
Jyotiranjan Beuria
Ph.D Student, HRI Allahabad
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