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

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

Ok, thousand thanks, your lib is very pleasing :)

2017-10-22 19:08 GMT-05:00 Davis King <dav...@gm...>:

> Yes: http://dlib.net/dlib/dnn/layers_abstract.h.html#extract_
>
> On Sun, Oct 22, 2017 at 8:06 PM, Eloi Du Bois <elo...@gm...>
> wrote:
>
>> 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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