From f77dddc83b7707385d19648a885c5b773c515d48 Mon Sep 17 00:00:00 2001
From: jatin <jatinchowdhury18@gmail.com>
Date: Tue, 12 Nov 2024 18:23:18 -0800
Subject: [PATCH] More tests

---
 models/dense.json                    | 717 ++++++++++++++++-----------
 python/dense.png                     | Bin 17852 -> 16361 bytes
 python/dense.py                      |   3 +
 test_data/dense_y_python.csv         | 200 ++++----
 tests/functional/templated_tests.cpp |   6 +
 5 files changed, 544 insertions(+), 382 deletions(-)

diff --git a/models/dense.json b/models/dense.json
index 3c3e2b5..768ac27 100644
--- a/models/dense.json
+++ b/models/dense.json
@@ -14,25 +14,25 @@
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diff --git a/python/dense.png b/python/dense.png
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zyV~ReM2cjY;7bBSwlBL1pD0{|+Qmm`+P8z!4T>Yk>CUO-0jpLB;GGM06jy*2{eS%*
d_E<k8>Qdq|r@du93&a*BC#7^h@1F6C{|kudtc?Hw

diff --git a/python/dense.py b/python/dense.py
index 46178a2..5c9dfc9 100644
--- a/python/dense.py
+++ b/python/dense.py
@@ -18,6 +18,9 @@
 model.add(keras.layers.Activation('elu'))
 model.add(keras.layers.Dense(8, kernel_initializer='orthogonal', bias_initializer='random_normal'))
 model.add(keras.layers.Activation('softmax'))
+model.add(keras.layers.Dense(1, kernel_initializer='orthogonal'))
+model.add(keras.layers.Dense(8, kernel_initializer='orthogonal', use_bias=False))
+model.add(keras.layers.Dense(8, kernel_initializer='orthogonal', use_bias=False))
 model.add(keras.layers.Dense(1, kernel_initializer='orthogonal', use_bias=False))
 
 # construct signals
diff --git a/test_data/dense_y_python.csv b/test_data/dense_y_python.csv
index ef15642..70e0f2c 100644
--- a/test_data/dense_y_python.csv
+++ b/test_data/dense_y_python.csv
@@ -1,100 +1,100 @@
-1.291836053133010864e-02
--8.473519980907440186e-02
--7.842954993247985840e-02
--7.582875341176986694e-02
--7.484415173530578613e-02
--7.459025830030441284e-02
--7.484415173530578613e-02
--7.582875341176986694e-02
--7.842954993247985840e-02
--8.473519980907440186e-02
-1.291836053133010864e-02
-1.371265947818756104e-02
-1.484059542417526245e-02
-1.539696753025054932e-02
-1.561937481164932251e-02
-1.567736268043518066e-02
-1.561937481164932251e-02
-1.539696753025054932e-02
-1.484059542417526245e-02
-1.371265947818756104e-02
-1.291836053133010864e-02
--8.473519980907440186e-02
--7.842954993247985840e-02
--7.582875341176986694e-02
--7.484415173530578613e-02
--7.459025830030441284e-02
--7.484415173530578613e-02
--7.582875341176986694e-02
--7.842954993247985840e-02
--8.473519980907440186e-02
-1.291836053133010864e-02
-1.371265947818756104e-02
-1.484059542417526245e-02
-1.539696753025054932e-02
-1.561937481164932251e-02
-1.567736268043518066e-02
-1.561937481164932251e-02
-1.539696753025054932e-02
-1.484059542417526245e-02
-1.371265947818756104e-02
-1.291836053133010864e-02
--8.473519980907440186e-02
--7.842954993247985840e-02
--7.582875341176986694e-02
--7.484415173530578613e-02
--7.459025830030441284e-02
--7.484415173530578613e-02
--7.582875341176986694e-02
--7.842954993247985840e-02
--8.473519980907440186e-02
-1.291836053133010864e-02
-1.371265947818756104e-02
-1.484059542417526245e-02
-1.539696753025054932e-02
-1.561937481164932251e-02
-1.567736268043518066e-02
-1.561937481164932251e-02
-1.539696753025054932e-02
-1.484059542417526245e-02
-1.371265947818756104e-02
-1.291836053133010864e-02
--8.473519980907440186e-02
--7.842954993247985840e-02
--7.582875341176986694e-02
--7.484415173530578613e-02
--7.459025830030441284e-02
--7.484415173530578613e-02
--7.582875341176986694e-02
--7.842954993247985840e-02
--8.473519980907440186e-02
-1.291836053133010864e-02
-1.371265947818756104e-02
-1.484059542417526245e-02
-1.539696753025054932e-02
-1.561937481164932251e-02
-1.567736268043518066e-02
-1.561937481164932251e-02
-1.539696753025054932e-02
-1.484059542417526245e-02
-1.371265947818756104e-02
-1.291836053133010864e-02
--8.473519980907440186e-02
--7.842954993247985840e-02
--7.582875341176986694e-02
--7.484415173530578613e-02
--7.459025830030441284e-02
--7.484415173530578613e-02
--7.582875341176986694e-02
--7.842954993247985840e-02
--8.473519980907440186e-02
-1.291836053133010864e-02
-1.371265947818756104e-02
-1.484059542417526245e-02
-1.539696753025054932e-02
-1.561937481164932251e-02
-1.567736268043518066e-02
-1.561937481164932251e-02
-1.539696753025054932e-02
-1.484059542417526245e-02
-1.371265947818756104e-02
+-2.098033204674720764e-02
+-2.608384937047958374e-02
+-2.623894810676574707e-02
+-2.620269358158111572e-02
+-2.619257196784019470e-02
+-2.619054913520812988e-02
+-2.619257196784019470e-02
+-2.620269358158111572e-02
+-2.623894810676574707e-02
+-2.608384937047958374e-02
+-2.098033204674720764e-02
+-1.998519292101264000e-04
+6.356053985655307770e-03
+7.656278088688850403e-03
+7.932090200483798981e-03
+7.984477095305919647e-03
+7.932090200483798981e-03
+7.656278088688850403e-03
+6.356053985655307770e-03
+-1.998519292101264000e-04
+-2.098033204674720764e-02
+-2.608384937047958374e-02
+-2.623894810676574707e-02
+-2.620269358158111572e-02
+-2.619257196784019470e-02
+-2.619054913520812988e-02
+-2.619257196784019470e-02
+-2.620269358158111572e-02
+-2.623894810676574707e-02
+-2.608384937047958374e-02
+-2.098033204674720764e-02
+-1.998519292101264000e-04
+6.356053985655307770e-03
+7.656278088688850403e-03
+7.932090200483798981e-03
+7.984477095305919647e-03
+7.932090200483798981e-03
+7.656278088688850403e-03
+6.356053985655307770e-03
+-1.998519292101264000e-04
+-2.098033204674720764e-02
+-2.608384937047958374e-02
+-2.623894810676574707e-02
+-2.620269358158111572e-02
+-2.619257196784019470e-02
+-2.619054913520812988e-02
+-2.619257196784019470e-02
+-2.620269358158111572e-02
+-2.623894810676574707e-02
+-2.608384937047958374e-02
+-2.098033204674720764e-02
+-1.998519292101264000e-04
+6.356053985655307770e-03
+7.656278088688850403e-03
+7.932090200483798981e-03
+7.984477095305919647e-03
+7.932090200483798981e-03
+7.656278088688850403e-03
+6.356053985655307770e-03
+-1.998519292101264000e-04
+-2.098033204674720764e-02
+-2.608384937047958374e-02
+-2.623894810676574707e-02
+-2.620269358158111572e-02
+-2.619257196784019470e-02
+-2.619054913520812988e-02
+-2.619257196784019470e-02
+-2.620269358158111572e-02
+-2.623894810676574707e-02
+-2.608384937047958374e-02
+-2.098033204674720764e-02
+-1.998519292101264000e-04
+6.356053985655307770e-03
+7.656278088688850403e-03
+7.932090200483798981e-03
+7.984477095305919647e-03
+7.932090200483798981e-03
+7.656278088688850403e-03
+6.356053985655307770e-03
+-1.998519292101264000e-04
+-2.098033204674720764e-02
+-2.608384937047958374e-02
+-2.623894810676574707e-02
+-2.620269358158111572e-02
+-2.619257196784019470e-02
+-2.619054913520812988e-02
+-2.619257196784019470e-02
+-2.620269358158111572e-02
+-2.623894810676574707e-02
+-2.608384937047958374e-02
+-2.098033204674720764e-02
+-1.998519292101264000e-04
+6.356053985655307770e-03
+7.656278088688850403e-03
+7.932090200483798981e-03
+7.984477095305919647e-03
+7.932090200483798981e-03
+7.656278088688850403e-03
+6.356053985655307770e-03
+-1.998519292101264000e-04
diff --git a/tests/functional/templated_tests.cpp b/tests/functional/templated_tests.cpp
index dc363bf..51c7ba0 100644
--- a/tests/functional/templated_tests.cpp
+++ b/tests/functional/templated_tests.cpp
@@ -53,6 +53,9 @@ TEST(TestTemplatedModels, modelOutputMatchesPythonImplementationForDense)
         ELuActivationT<TestType, 8>,
         DenseT<TestType, 8, 8>,
         SoftmaxActivationT<TestType, 8>,
+        DenseT<TestType, 8, 1>,
+        DenseT<TestType, 1, 8, false>,
+        DenseT<TestType, 8, 8, false>,
         DenseT<TestType, 8, 1, false>>;
 
     runTestTemplated<TestType, ModelType>(tests.at("dense"));
@@ -69,6 +72,9 @@ TEST(TestTemplatedModels, modelOutputMatchesPythonImplementationForDenseWithMath
         ELuActivationT<TestType, 8, 1, 1, TestMathsProvider>,
         DenseT<TestType, 8, 8>,
         SoftmaxActivationT<TestType, 8, TestMathsProvider>,
+        DenseT<TestType, 8, 1>,
+        DenseT<TestType, 1, 8, false>,
+        DenseT<TestType, 8, 8, false>,
         DenseT<TestType, 8, 1, false>>;
 
     runTestTemplated<TestType, ModelType>(tests.at("dense"));