keras-molecules
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maxhodak
Top-level dir is not a module
I've been trying to package up keras-molecules as a module so I can run it on Google Cloud Machine Learning. Unfortunately, the top-level of keras-molecules (with train.py etc) isn't really module ready. The repo name has a "-" in it, and there's no top-level init.py.
What did you end up doing for this? Intuitively it doesn't feel like making the top level a module is the right thing to do but maybe having an invokable module in the molecules dir rather than having the logic in a top level script, so we could do python -m molecules.train and have a shell script or something in the top level as an alias that passes arguments through.
Can you point me to documentation for what Google Cloud Machine Learning expects?
I just renamed the parent dir to keras_molecules, and added an init.py.
The way I usually like to structure this is:
toplevel/
toplevel/src/<all source code such as molecules/ goes here>
toplevel/scripts/
and then no code goes in toplevel/, just README, LICENSE, setup.py.
On Tue, Nov 29, 2016 at 10:59 AM, Max Hodak [email protected] wrote:
What did you end up doing for this? Intuitively it doesn't feel like making the top level a module is the right thing to do but maybe having an invokable module in the molecules dir rather than having the logic in a top level script, so we could do python -m molecules.train and have a shell script or something in the top level as an alias that passes arguments through.
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The docs for Cloud ML aren't great for custom jobs right now. Most of them are here: https://cloud.google.com/ml/docs/how-tos/preparing-models At the bottom it mentions setup.py.
I have a working example for Google Cloud Machine Learning. I could reformat it into a pull request if you want the recipe.
On Tue, Nov 29, 2016 at 10:59 AM, Max Hodak [email protected] wrote:
Can you point me to documentation for what Google Cloud Machine Learning expects?
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