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From: | Brayan Impatá |
Subject: | Re: GSOC 17 - Octave - Reutilization of NNET on CNN Project |
Date: | Wed, 22 Mar 2017 19:13:19 +0100 |
On 03/22/2017 09:00 AM, octave-maintainers-request@gnu.org wrote:
Subject:Re: GSOC 17 - Octave - Reutilization of NNET on CNN Project From:Brayan Impatá <address@hidden> Date:03/22/2017 01:07 AM
To:address@hidden
List-Post:<mailto:octave-maintainers@gnu.org> Precedence:list MIME-Version:1.0 References:<HE1PR0601MB2265D69601F28D33B83 <1490090577469-4682488.post@address@hidden eurprd06.prod.outlook.com> n4.nabble.com> <CAMg2hZk_3tGiuhs+tQ=oZMnRbWBD59K9Qq0zjb5uGVtyb6vD6 address@hidden> In-Reply-To:<CAMg2hZk_3tGiuhs+tQ=oZMnRbWBD59K9Qq0zjb5uGVtyb6vD6 address@hidden> Message-ID:<CAMg2hZ=Omw-Wq958hWH9gy-48d6ihhivCt2yETLj-q7ECh-juQ@ mail.gmail.com> Content-Type:multipart/alternative; boundary=001a11422a3c89d27b054b4d3fa1 Message:3
Hi,I've seen we have a strong dependency to the Pytave project if we pretend to use Tensorflow/Keras through its Python interface. Shall we better move to use OCT files to define the CNN module and use the C++ API that Tensorflow exposes? It does not seems to be a good idea depending on another developing project.
I would say that many people overestimate the difficulty of using .oct files. I re-wrote a lot of the documentation on using the external interface so I think the manual is pretty clear now. And there are many usage examples in the libinterp/dldfcn directory to begin an implementation from. Since Tensorflow exposes a C++ API it makes a whole lot of sense to me to use this approach rather than go through a longer path of Octave->Python->Tensorflow->Python->Octave.
The only caveat I see is this, "A word of caution: the APIs in languages other than Python are not yet covered by the API stability promises." However, I doubt they are going to abandon C++ as an API.
---Rik
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