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Modified tests for ann_layer_test

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This commit is contained in:
Sourabh Varshney
2018-03-21 16:30:54 +05:30
parent 77c26b88ac
commit a29be893dc
1 changed files with 12 additions and 17 deletions
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src/mlpack/tests/ann_layer_test.cpp
+12 -17
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@@ -239,8 +239,7 @@ BOOST_AUTO_TEST_CASE(GradientAddLayerTest)
input = arma::randu(10, 1);
target = arma::mat("1");
model = new FFN<NegativeLogLikelihood<>, NguyenWidrowInitialization>(
input, target);
model = new FFN<NegativeLogLikelihood<>, NguyenWidrowInitialization>();
model->Add<IdentityLayer<> >();
model->Add<Add<> >(10);
model->Add<LogSoftMax<> >();
@@ -460,8 +459,7 @@ BOOST_AUTO_TEST_CASE(GradientLinearLayerTest)
input = arma::randu(10, 1);
target = arma::mat("1");
model = new FFN<NegativeLogLikelihood<>, NguyenWidrowInitialization>(
input, target);
model = new FFN<NegativeLogLikelihood<>, NguyenWidrowInitialization>();
model->Add<IdentityLayer<> >();
model->Add<Linear<> >(10, 2);
model->Add<LogSoftMax<> >();
@@ -543,8 +541,7 @@ BOOST_AUTO_TEST_CASE(GradientLinearNoBiasLayerTest)
input = arma::randu(10, 1);
target = arma::mat("1");
model = new FFN<NegativeLogLikelihood<>, NguyenWidrowInitialization>(
input, target);
model = new FFN<NegativeLogLikelihood<>, NguyenWidrowInitialization>();
model->Add<IdentityLayer<> >();
model->Add<LinearNoBias<> >(10, 2);
model->Add<LogSoftMax<> >();
@@ -749,7 +746,7 @@ BOOST_AUTO_TEST_CASE(LSTMRrhoTest)
// Create model with user defined rho parameter.
RNN<NegativeLogLikelihood<>, RandomInitialization> modelA(
input, target, rho, false, NegativeLogLikelihood<>(), init);
rho, false, NegativeLogLikelihood<>(), init);
modelA.Add<IdentityLayer<> >();
modelA.Add<Linear<> >(1, 10);
@@ -759,7 +756,7 @@ BOOST_AUTO_TEST_CASE(LSTMRrhoTest)
// Create model without user defined rho parameter.
RNN<NegativeLogLikelihood<> > modelB(
input, target, rho, false, NegativeLogLikelihood<>(), init);
rho, false, NegativeLogLikelihood<>(), init);
modelB.Add<IdentityLayer<> >();
modelB.Add<Linear<> >(1, 10);
@@ -788,7 +785,7 @@ BOOST_AUTO_TEST_CASE(GradientLSTMLayerTest)
target.ones(1, 1, 5);
const size_t rho = 5;
model = new RNN<NegativeLogLikelihood<> >(input, target, rho);
model = new RNN<NegativeLogLikelihood<> >(rho);
model->Add<IdentityLayer<> >();
model->Add<Linear<> >(1, 10);
model->Add<LSTM<> >(10, 3, rho);
@@ -829,7 +826,7 @@ BOOST_AUTO_TEST_CASE(FastLSTMRrhoTest)
// Create model with user defined rho parameter.
RNN<NegativeLogLikelihood<>, RandomInitialization> modelA(
input, target, rho, false, NegativeLogLikelihood<>(), init);
rho, false, NegativeLogLikelihood<>(), init);
modelA.Add<IdentityLayer<> >();
modelA.Add<Linear<> >(1, 10);
@@ -839,7 +836,7 @@ BOOST_AUTO_TEST_CASE(FastLSTMRrhoTest)
// Create model without user defined rho parameter.
RNN<NegativeLogLikelihood<> > modelB(
input, target, rho, false, NegativeLogLikelihood<>(), init);
rho, false, NegativeLogLikelihood<>(), init);
modelB.Add<IdentityLayer<> >();
modelB.Add<Linear<> >(1, 10);
@@ -868,7 +865,7 @@ BOOST_AUTO_TEST_CASE(GradientFastLSTMLayerTest)
target = arma::ones(1, 1, 5);
const size_t rho = 5;
model = new RNN<NegativeLogLikelihood<> >(input, target, rho);
model = new RNN<NegativeLogLikelihood<> >(rho);
model->Add<IdentityLayer<> >();
model->Add<Linear<> >(1, 10);
model->Add<FastLSTM<> >(10, 3, rho);
@@ -915,7 +912,7 @@ BOOST_AUTO_TEST_CASE(GradientGRULayerTest)
target = arma::ones(1, 1, 5);
const size_t rho = 5;
model = new RNN<NegativeLogLikelihood<> >(input, target, rho);
model = new RNN<NegativeLogLikelihood<> >(rho);
model->Add<IdentityLayer<> >();
model->Add<Linear<> >(1, 10);
model->Add<GRU<> >(10, 3, rho);
@@ -1047,8 +1044,7 @@ BOOST_AUTO_TEST_CASE(GradientConcatLayerTest)
input = arma::randu(10, 1);
target = arma::mat("1");
model = new FFN<NegativeLogLikelihood<>, NguyenWidrowInitialization>(
input, target);
model = new FFN<NegativeLogLikelihood<>, NguyenWidrowInitialization>();
model->Add<IdentityLayer<> >();
concat = new Concat<>();
@@ -1411,8 +1407,7 @@ BOOST_AUTO_TEST_CASE(GradientBatchNormLayerTest)
arma::mat target;
target.ones(1, 256);
model = new FFN<NegativeLogLikelihood<>, NguyenWidrowInitialization>(
input, target);
model = new FFN<NegativeLogLikelihood<>, NguyenWidrowInitialization>();
model->Add<IdentityLayer<> >();
model->Add<BatchNorm<> >(10);
model->Add<Linear<> >(10, 2);