@Test public void when_callingCopyFrom_expect_handlerIsCalled() { setup(false); sut.copyFrom(sut); verify(handlerMock, times(1)).copyFrom(handlerMock); }
public void copyFrom(BaseNetwork from) { reset(); networkHandler.copyFrom(from.networkHandler); }
BaseNetwork implements ITrainableNeuralNet<NET_TYPE> { public void copyFrom(BaseNetwork from) { reset(); networkHandler.copyFrom(from.networkHandler); } }
BaseNetwork implements ITrainableNeuralNet<NET_TYPE> { public void copyFrom(BaseNetwork from) { reset(); networkHandler.copyFrom(from.networkHandler); } protected  BaseNetwork(INetworkHandler networkHandler); }
BaseNetwork implements ITrainableNeuralNet<NET_TYPE> { public void copyFrom(BaseNetwork from) { reset(); networkHandler.copyFrom(from.networkHandler); } protected  BaseNetwork(INetworkHandler networkHandler); boolean isRecurrent(); @Override void fit(FeaturesLabels featuresLabels); @Override Gradients computeGradients(FeaturesLabels featuresLabels); @Override void applyGradients(Gradients gradients); @Override NeuralNetOutput output(Observation observation); NeuralNetOutput output(INDArray batch); @Override void reset(); void copyFrom(BaseNetwork from); abstract NET_TYPE clone(); }
BaseNetwork implements ITrainableNeuralNet<NET_TYPE> { public void copyFrom(BaseNetwork from) { reset(); networkHandler.copyFrom(from.networkHandler); } protected  BaseNetwork(INetworkHandler networkHandler); boolean isRecurrent(); @Override void fit(FeaturesLabels featuresLabels); @Override Gradients computeGradients(FeaturesLabels featuresLabels); @Override void applyGradients(Gradients gradients); @Override NeuralNetOutput output(Observation observation); NeuralNetOutput output(INDArray batch); @Override void reset(); void copyFrom(BaseNetwork from); abstract NET_TYPE clone();  }