Thx, it's right.
On Wednesday, December 7, 2016 at 3:55:29 PM UTC+8, Pascal Lamblin wrote:
>
> The error message indicates that the index variable (x_index_true) has
> to have an integer dtype.
>
> The issue in that case is that its dtype is float64, since mask has been
> defined as a dmatrix(). If you define it as imatrix() or lmatrix(), then
> it should work.
>
> On Tue, Dec 06, 2016, Lijun Wu wrote:
> > But when I try to feed in with M.shape[0], it failed, my code is:
> >
> > x = tensor.dmatrix('x')
> > mask = tensor.dmatrix('m')
> > mask_sum = mask.sum(axis=0)
> > mask_sum_gt_1 = tensor.gt(mask_sum, 1)
> > x_index= mask.sum - 2
> > x_index_true = x_index * mask_sum_gt_1
> > one_hot_matrix = tensor.extra_ops.to_one_hot(x_index_true,
> mask.shape[0])
> >
> > then it posted error:
> > raise TypeError('index must be integers')
> >
> > am I doing anything wrong?
> >
> >
> > On Wednesday, December 7, 2016 at 6:47:34 AM UTC+8, Pascal Lamblin
> wrote:
> > >
> > > Theano definitely accepts 'nb_class' as a symbolic scalar in
> to_one_hot().
> > >
> > > >>> a = tensor.ivector()
> > > >>> i = tensor.iscalar()
> > > >>> b = to_one_hot(a, i)
> > > >>> b.eval{a: [3], i: 5})
> > > array([[ 0., 0., 0., 1., 0.]])
> > > >>> b.eval({a: [3], i: 4})
> > > array([[ 0., 0., 0., 1.]])
> > >
> > >
> > > On Tue, Dec 06, 2016, Lijun Wu wrote:
> > > > Hi All,
> > > >
> > > > I want to implement the need of one_hot with variable length, so I
> want
> > > to
> > > > feed in the nb_class with a tensorVariable, but how to do this? Is
> there
> > > > any other way?
> > > >
> > > > What my need is following:
> > > > I have matrix A, example:
> > > > [[0.1, 0.2, 0.3]
> > > > [0.2, 0.1, 0.1]
> > > > [0.1, 0.2, 0.2]]
> > > >
> > > > and one mask matrix M:
> > > > [[1, 1, 1]
> > > > [1, 0, 1]
> > > > [0, 0, 0]]
> > > >
> > > > and I want to get the last one in each column of M, and get the
> > > > corresponding value in A. e.g, here is
> > > > [[0, 0.2, 0]
> > > > [0.2, 0, 0.1]
> > > > [0, 0, 0]]
> > > >
> > > > My solution is first get y=M.sum(axis=0), then feed y to create
> one_hot
> > > > matrix using extra_ops.to_one_hot(), but since my M.shape[0] will be
> > > > different, so I want to feed in np_class as M.shape[0], but I don't
> know
> > > > how to do this, one_hot() can not feed in 'nb_class' as
> tensorvariable.
> > > >
> > > > Can anyone help me work on this? Thanks pretty much.
> > > >
> > > > --
> > > >
> > > > ---
> > > > You received this message because you are subscribed to the Google
> > > Groups "theano-users" group.
> > > > To unsubscribe from this group and stop receiving emails from it,
> send
> > > an email to [email protected] <javascript:>.
> > > > For more options, visit https://groups.google.com/d/optout.
> > >
> > >
> > > --
> > > Pascal
> > >
> >
> > --
> >
> > ---
> > You received this message because you are subscribed to the Google
> Groups "theano-users" group.
> > To unsubscribe from this group and stop receiving emails from it, send
> an email to [email protected] <javascript:>.
> > For more options, visit https://groups.google.com/d/optout.
>
>
> --
> Pascal
>
--
---
You received this message because you are subscribed to the Google Groups
"theano-users" group.
To unsubscribe from this group and stop receiving emails from it, send an email
to [email protected].
For more options, visit https://groups.google.com/d/optout.
