On Thu, Oct 06, 2016, daniel hernandez wrote:
> I am starting with theano and for the life of me, I can't figure out how to
> define a simple TensorVariable whose eval method returns a constant. theano
> itself defines such variables, for instance
>
> > E = T.eye(2)
> > type(E)
>
> theano.tensor.var.TensorVariable
>
>
> > E.eval()
>
> array([[ 1., 0.],
> [ 0., 1.]])
>
>
>
> So, what is theano doing under the hood here? how do I assign a constant
> value to a dscalar x?
Under the hood, it is doing:
>>> f = theano.function(inputs=[], outputs=E)
>>> f()
In this case it works, because the value of E only depends en constants (here,
2).
> > x = T.dscalar('x')
> > type(x)
>
> theano.tensor.var.TensorVariable
In that case, you can use the explicit version:
>>> f = theano.function(inputs=[x], outputs=x)
>>> f(3)
or the "eval shortcut"
>>> x.eval({x: 3})
> Also, if someone knows of a reference that answers these basic questions that
> are not answered in the docs, I would be grateful.
You can start with http://deeplearning.net/software/theano/tutorial/index.html
>
>
> daniel
>
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Pascal
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