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Update feedforward_network_test.cpp

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I have changed the test network with stochastic option to be off so that randomization was leading to different predictions.
This commit is contained in:
Anmolpreet Singh
2021-01-02 12:39:04 +05:30
committed by GitHub
parent cc85d2035f
commit f29baecfbf
1 changed files with 4 additions and 23 deletions
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src/mlpack/tests/feedforward_network_test.cpp
+4 -23
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@@ -167,36 +167,17 @@ TEST_CASE("CheckCopyMovingReparametrizationNetworkTest", "[FeedForwardNetworkTes
/*
* Construct a feed forward network with trainData.n_rows input nodes,
* hiddenLayerSize hidden nodes and trainLabels.n_rows output nodes. The
* network structure looks like:
*
* Input Hidden Output
* Layer Layer Layer
* +-----+ +-----+ +-----+
* | | | | | |
* | +------>| +------>| |
* | | +>| | +>| |
* +-----+ | +--+--+ | +-----+
* | |
* Bias | Bias |
* Layer | Layer |
* +-----+ | +-----+ |
* | | | | | |
* | +-----+ | +-----+
* | | | |
* +-----+ +-----+
* followed by a linear layer and then a reparametrization layer
*/
FFN<NegativeLogLikelihood<> > *model = new FFN<NegativeLogLikelihood<> >;
model->Add<Linear<> >(trainData.n_rows, 8);
model->Add<SigmoidLayer<> >();
model->Add<Reparametrization<> >();
model1->Add<Linear<> >(trainData.n_rows, 8);
model1->Add<Reparametrization<> >(4,false,true,1);
model->Add<LogSoftMax<> >();
FFN<NegativeLogLikelihood<> > *model1 = new FFN<NegativeLogLikelihood<> >;
model1->Add<Linear<> >(trainData.n_rows, 8);
model1->Add<SigmoidLayer<> >();
model1->Add<Reparametrization<> >();
model1->Add<Reparametrization<> >(4,false,true,1);
model1->Add<LogSoftMax<> >();
// Check whether copy constructor is working or not.