joel-simon / ganbreeder

Breed and share images using biggan
https://ganbreeder.app
GNU General Public License v3.0
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Docker compose implementation #17

Closed SarunasAzna closed 4 years ago

SarunasAzna commented 4 years ago

Docker-compose implementation. These changes allows developer to run the project with one command - docker-compose up.

joel-simon commented 4 years ago

Awesome, thanks!

SarunasAzna commented 4 years ago

;) question is, is it possible to cache tensorflow module? Those few minutes each time is a bit annoying :(

On Sat, 8 Feb 2020, 00:44 Joel Simon, notifications@github.com wrote:

Merged #17 https://github.com/joel-simon/ganbreeder/pull/17 into master.

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joel-simon commented 4 years ago

For downloading or loading into ram? Probably don't want to stick the whole file in the docker, it will get saved locally so as long as you reuse the docker image it should be ok?

SarunasAzna commented 4 years ago

As per docker image reuse - if the file is in shared dir - all fine, if not

On Mon, Feb 10, 2020 at 12:48 AM Joel Simon notifications@github.com wrote:

For downloading or loading into ram? Probably don't want to stick the whole file in the docker, it will get saved locally so as long as you reuse the docker image it should be ok?

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SarunasAzna commented 4 years ago

awesome website btw :)

On Mon, Feb 10, 2020 at 10:01 AM Šarūnas Ažna sarunas.azna@gmail.com wrote:

As per docker image reuse - if the file is in shared dir - all fine, if not - docker will be pretty much in the same state as it is defined on Dockerfile even if you reuse it :( As per first part of the question - I guess downloading, though i am not sure since all of my tensorflow exp is that those few hours with your repo.. But what would be good - cache some of the things done from here https://github.com/joel-simon/ganbreeder/blob/master/gan_server/server.py#L20 to https://github.com/joel-simon/ganbreeder/blob/master/gan_server/server.py#L36 .

On Mon, Feb 10, 2020 at 12:48 AM Joel Simon notifications@github.com wrote:

For downloading or loading into ram? Probably don't want to stick the whole file in the docker, it will get saved locally so as long as you reuse the docker image it should be ok?

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