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What would you like to do?
experiment with docker and rnn on the programming historian source files

I want to get the computer to generate new Programming Historian tutorials for me. Madness, I know, but.... kinda awesome.

torch-rnn to the rescue!

helpful: http://seankross.com/2017/09/17/Enough-Docker-to-be-Dangerous.html helpful: https://hub.docker.com/r/crisbal/torch-rnn/

So:

  1. download, install docker.
  2. start docker.
  3. get the docker image from https://hub.docker.com/r/crisbal/torch-rnn/
$ docker pull crisbal/torch-rnn:base

Start it up with:

docker run -it crisbal/torch-rnn:base

and exit to get out.

Right. we want to put some new data inside the image. Get the container ID

$ docker ps

docker image, image name... not useful. container id is where it's at. Say the id was 776f3940e045

then you can start it up with docker start -ai 776f3940e045 . Anyway, we need that id for cp purposes etc.

Meanwhile, I wanted all of the source MD files for programming historian. Turns out, very hard to download just a folder from a github repo. So I wget'ed one at a time, forgetting that I'd end up with all of the github shit too. Ah well. I could've just downloaded the whole repo, then grabbed what I wanted, but the repo is really large and I'm on a slow connection.

Anyway, concatenated all the files into a single input.txt file. Now need to get that into my data folder inside the docker image:

$ docker cp input.txt 776f3940e045:/root/torch-rnn/data/

ta da. data is now inside. proceed with usual training etc.

This is also very helpful for understanding what's going on with the rnn: https://github.com/eltiffster/authorFunction#stopping-and-starting-training

.... a day later ....

I resumed with

th train.lua -input_h5 data/proghist.h5 -input_json data/proghist.json -model_type rnn -num_layers 3 -rnn_size 256 -init_from cv/checkpoint_20000.t7 -gpu -1

of course, I didn't specify rnn layers or size last time, so that probably frigs things up. original training was:

th train.lua \
 -input_h5 data/proghist.h5 \
 -input_json data/proghist.json \
 -gpu -1
$ root@776f3940e045:~/torch-rnn# th sample.lua -checkpoint cv/checkpoint_20000.t7 -length 20000 -temperature 0.5 -gpu -1
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