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hammerlab / mhcflurry / 558 / 3
75%
master: 73%

Build:
Build:
LAST BUILD BRANCH: 1.0.0
DEFAULT BRANCH: master
Ran 03 Aug 2017 05:43PM UTC
Files 30
Run time 3s
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03 Aug 2017 05:27PM UTC coverage: 75.224%. First build
KERAS_BACKEND=theano

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timodonnell
Reuse Keras models optimization

This should give a substantial prediction speed improvement as identified by @rohanpai

* Add borrow_cached_network() method to Class1NeuralNetwork
* Use cached models at in Class1NeuralNetwork.predict
* Set names for all neural network layers so the model JSON is identical for identical architectures

1257 of 1671 relevant lines covered (75.22%)

0.75 hits per line

Source Files on job 558.3 (KERAS_BACKEND=theano)
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