Re: [Dclib-devel] [dclib-devel] Implementing a GAN with dlib

[Eloi Du B. <elo...@gm...>]

Ok, thank you for your help. Is there any reshape layer that I could use?


2017-10-22 19:04 GMT-05:00 Davis King <dav...@gm...>:

> Well, I don't know what paper you are following.  Maybe it's the most
> convenient way.  But you probably want to use the dnn_trainer to train
> multiple steps at a time when optimizing each of the subnets.  But maybe
> not.
>
> Anyway, the fc layer outputs are 1 row and 1 columns but k channels.
> That's why you get only 16 outputs.  This is all in the documentation for
> the layers.
>
> On Sun, Oct 22, 2017 at 7:58 PM, Eloi Du Bois <elo...@gm...>
> wrote:
>
>> I'm sorry, I'm not sure I see how I can do using another way.
>> I think I'm almost done training a gaussian function, only problem I have
>> right now is that this network:
>>
>> // A 1 filter; 2x1 transposed conv layer that does 2x upsampling
>> template<class SUBNET>
>> using cont2 = dlib::cont<1, 1, 2, 1, 2, SUBNET>;
>> template<class SUBNET>
>> using GeneratorT = cont2<cont2<cont2<cont2<dlib::fc<8, SUBNET>>>>>; //
>> This will take an input of size 32 and generate an output of 128
>>
>> Is generating vectors of 16, I'm surprised as I put a fully connected
>> layer on the input that outputs 8 values. Then, everything is multiplied by
>> 2 going thru cont layers. It should be 128, no? How can this happen? Is
>> there something I'm missing or is there something else?
>>
>> Thanks,
>>
>>
>> 2017-10-22 7:47 GMT-05:00 Davis King <dav...@gm...>:
>>
>>> It does it for you.  Really though, I don't see why you would need to
>>> call the backward function yourself considering the task you have outlined.
>>>
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