Difference between revisions of "NaNoGenMo 2019 - GPT-2 Edition"

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(→‎gpt-2: it worked)
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docker build --tag gpt-2 -f Dockerfile.cpu .
 
docker build --tag gpt-2 -f Dockerfile.cpu .
 
docker run -it gpt-2 bash
 
docker run -it gpt-2 bash
export PYTHONIOENCODING=UTF-8
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export PYTHONIOENCODING=UTF-8</nowiki>
</nowiki>
 
  
 
Need to run this on AWS or something:
 
Need to run this on AWS or something:
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2019-11-09 20:43:44.915623: W tensorflow/core/framework/allocator.cc:122] Allocation of 18137088 exceeds 10% of system memory.
 
2019-11-09 20:43:44.915623: W tensorflow/core/framework/allocator.cc:122] Allocation of 18137088 exceeds 10% of system memory.
 
2019-11-09 20:43:45.006514: W tensorflow/core/framework/allocator.cc:122] Allocation of 18210816 exceeds 10% of system memory.
 
2019-11-09 20:43:45.006514: W tensorflow/core/framework/allocator.cc:122] Allocation of 18210816 exceeds 10% of system memory.
2019-11-09 20:43:45.102333: W tensorflow/core/framework/allocator.cc:122] Allocation of 18284544 exceeds 10% of system memory.
+
2019-11-09 20:43:45.102333: W tensorflow/core/framework/allocator.cc:122] Allocation of 18284544 exceeds 10% of system memory.</nowiki>
</nowiki>
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 +
Although it did actually spit out text, so for now I'm working inside this docker.
  
 
===Parl.AI===
 
===Parl.AI===

Revision as of 06:54, 10 November 2019

The Basics

My goal this year was to take some random text, character, and location generators and build a basic recursive quest engine.

Let's unpack that. All I want for now is:

  • locations - a small network of places, with the ability for characters to travel between them
  • characters - a recurring finite set of characters who travel between the locations and interact when they're in the same place
    • stretch goal - interact when they're passing one another!
  • recursive - the idea is that we have a world... it has, say, cities, within cities are places (inns, bars, markets), within those may be rooms... or maybe our recursion is deep enough at two levels

Eh, maybe that's even too much. I work a super lot and in eight days of November so far all I've done is written those bullets. But let's see what's out there...

progress...

So there are some good generators out there that sort of start to do what I want. I may just daisy chain them together... listed a few below. TextWorld world generations is almost exactly what I want, it's just single-character. Hmmm.


Local laptop

gpt-2

This: https://openai.com/blog/better-language-models/ Made this: https://github.com/openai/gpt-2 Which made this: https://colab.research.google.com/drive/1gB03iSnshYcSzSCrS9gPGcoOFCpMhVq_

hit this bug: https://github.com/openai/gpt-2/issues/178

git clone https://github.com/openai/gpt-2.git && cd gpt-2
docker build --tag gpt-2 -f Dockerfile.cpu .
docker run -it gpt-2 bash
export PYTHONIOENCODING=UTF-8

Need to run this on AWS or something:

2019-11-09 20:43:18.919955: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-11-09 20:43:23.418088: W tensorflow/core/framework/allocator.cc:122] Allocation of 154389504 exceeds 10% of system memory.
2019-11-09 20:43:23.722155: W tensorflow/core/framework/allocator.cc:122] Allocation of 154389504 exceeds 10% of system memory.
2019-11-09 20:43:44.915623: W tensorflow/core/framework/allocator.cc:122] Allocation of 18137088 exceeds 10% of system memory.
2019-11-09 20:43:45.006514: W tensorflow/core/framework/allocator.cc:122] Allocation of 18210816 exceeds 10% of system memory.
2019-11-09 20:43:45.102333: W tensorflow/core/framework/allocator.cc:122] Allocation of 18284544 exceeds 10% of system memory.

Although it did actually spit out text, so for now I'm working inside this docker.

Parl.AI

git clone https://github.com/facebookresearch/ParlAI.git
cd ParlAI; python setup.py develop

textworld

From: https://www.microsoft.com/en-us/research/project/textworld/ Yields: https://github.com/microsoft/textworld

hit this bug: https://github.com/authomatic/chromedriver_installer/issues/11

pip install textworld