On Fri, 9 Mar 2018 11:38:55, Robert Kern wrote:
> > Sorry for being a bit inaccurate.
> > My Scala code actually mirrors the NumPy based random initialization, so
> > I sample with Gaussian of mean = 0 and std dev = 1, then multiply with
0.01.
>
> Have you verified this? I.e. save out the Scala-in
On Thu, Mar 8, 2018 at 12:44 PM, Marko Asplund
wrote:
>
> On Wed, 7 Mar 2018 13:14:36, Robert Kern wrote:
>
> > > With NumPy I'm simply using the following random initilization code:
> > >
> > > np.random.randn(n_h, n_x) * 0.01
> > >
> > > I'm trying to emulate the same behaviour in my Scala code
On Wed, 7 Mar 2018 13:14:36, Robert Kern wrote:
> > With NumPy I'm simply using the following random initilization code:
> >
> > np.random.randn(n_h, n_x) * 0.01
> >
> > I'm trying to emulate the same behaviour in my Scala code by sampling
> from a
> > Gaussian distribution with mean = 0 and std
On Wed, Mar 7, 2018 at 1:10 PM, Marko Asplund
wrote:
>
> However, the results look very different when using random initialization.
> With respect to exact cost this is course expected, but what I find
troublesome
> is that after N training iterations the cost starts approaching zero
with the Num
On Tue, 6 Mar 2018 12:52:14, Robert Kern wrote:
> I would just recommend using one of the codebases to initialize the
> network, save the network out to disk, and load up the initialized network
> in each of the different codebases for training. That way you are sure
that
> they are both starting f
On Tue, Mar 6, 2018 at 1:39 AM, Marko Asplund
wrote:
>
> I've some neural network code in NumPy that I'd like to compare with a
Scala based implementation.
> My problem is currently random initialization of the neural net
parameters.
> I'd like to be able to get the same results from both implemen
I've some neural network code in NumPy that I'd like to compare with a
Scala based implementation.
My problem is currently random initialization of the neural net parameters.
I'd like to be able to get the same results from both implementations when
using the same random seed.
One approach I've th
