# Re: [theano-users] theano beginner problem

```I think you are confused about symbolic variables and compiled functions
in Theano, so I would advise reading the tutorials [1].```
```
You have to provide the symbolic variables when calling
theano.function(), and then the numerical values when calling the object
it returns (f()).

Also, you would want to compile (call theano.function()) only once, but
call the compiled function (f()) many times.

[1] http://deeplearning.net/software/theano/tutorial/index.html

On Wed, Nov 30, 2016, Mohammed Rashid Chowdhury wrote:
> thanks for your quick reply.
> in that case do you know how can i solve the problem?. is there any other
> way to compute the dot product of two matrices in theano?
>
> On Wednesday, November 30, 2016 at 6:33:25 PM UTC-6, Pascal Lamblin wrote:
> >
> > Since identity is a numpy array, you should not pass it as an input to
> > function().
> >
> > On Wed, Nov 30, 2016, Mohammed Rashid Chowdhury wrote:
> > > i was trying to simply compute the dot product of two matrices using
> > theano.
> > > my code is very simple.
> > >
> > >
> > > import theano
> > > import theano.tensor as T
> > > import numpy as np
> > > from theano import function
> > >
> > > def covarience(array):
> > >
> > >     input_array=T.matrix('input_array')
> > >     deviation_matrix = T.matrix('deviation_matrix')
> > >     matrix_filled_with_1s=T.matrix('matrix_filled_with_1s')
> > >     z = T.dot(input_array, matrix_filled_with_1s)
> > >
> > >
> > >     identity=np.ones((len(array),len(array)))
> > >
> > >     f=function([array,identity],z)
> > >     # print(f)
> > >
> > >
> > > covarience(np.array([[2,4],[6,8]]))
> > >
> > >
> > >
> > >
> > > but the problem is each time i run this code , i get error message like
> > > "TypeError: Unknown parameter type: <class 'numpy.ndarray'>"
> > >
> > > i am kind of lost here. can anyone tell me whats wrong with my code ?.
> > Any
> > > kind of help from any one of you would be highly appreciated.
> > >
> > > --
> > >
> > > ---
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> >
> >
> > --
> > Pascal
> >
>
> --
>
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--
Pascal

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