Yes, absolutely.
On Apr 25, 2014 11:04 AM, "Bart" <notifications@github.com> wrote:

> In pylearn2/models/mlp.py:
>
> > @@ -3653,6 +3651,28 @@ def set_mlp(self, mlp):
> >          for layer in self.layers:
> >              layer.set_mlp(mlp)
> >
> > +    @wraps(Layer.dropout_fprop)
> > +    def dropout_fprop(self, state_below, default_input_include_prob=0.5,
> > +                      input_include_probs=None, default_input_scale=2.,
> > +                      input_scales=None, per_example=True, theano_rng=None):
> > +
> > +        if theano_rng is None:
> > +            theano_rng = MRG_RandomStreams(max(self.rng.randint(2 ** 15), 1))
>
> I'm not entirely sure about this, but I think you'll want to use a fixed
> seed to make experiments reproducable.
>
> —
> Reply to this email directly or view it on GitHub<https://github.com/lisa-lab/pylearn2/pull/844/files#r12000402>
> .
>