Keras nets - #44
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TODO: - test Conv2d layer Theano code
TODO: - Subtract out data mean for training (remove scaling too?)
Seanny123
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Jun 1, 2017
| X_train, X_test = preprocess(X_train), preprocess(X_test) | ||
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| data_mean = np.zeros_like(X_train[0]) | ||
| # data_mean = X_train.mean(axis=0) |
| from __future__ import print_function | ||
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| import os | ||
| os.environ['THEANO_FLAGS'] = 'device=gpu,floatX=float32' |
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Given that Keras is back-end agnostic, are these Theano flags necessary?
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Yes, because I run my Keras with Theano. I'm not sure what the best way to do this is. Maybe comment it out and let people uncomment it if they're using Theano on a GPU.
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| n_presentations = 100 | ||
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| if 0: |
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So this code is never going to be run?
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That's what I do when I have optional things, that myself or others might want to play around with.
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Two of the commits I still have marked WIP. |
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Oh jeez, I'm sorry for bothering you with a premature review. I only realized afterwards the commits were marked WIP. My bad. :( |
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Improvements for networks in Keras.