MLECO-3183: Refactoring application sources

Platform agnostic application sources are moved into application
api module with their own independent CMake projects.

Changes for MLECO-3080 also included - they create CMake projects
individial API's (again, platform agnostic) that dependent on the
common logic. The API for KWS_API "joint" API has been removed and
now the use case relies on individual KWS, and ASR API libraries.

Change-Id: I1f7748dc767abb3904634a04e0991b74ac7b756d
Signed-off-by: Kshitij Sisodia <kshitij.sisodia@arm.com>

2 files changed, 44 insertions, 6 deletions

diff --git a/tests/use_case/asr/InferenceTestWav2Letter.cc b/tests/use_case/asr/InferenceTestWav2Letter.cc
index 53c92ab..643f805 100644
--- a/tests/use_case/asr/InferenceTestWav2Letter.cc
+++ b/tests/use_case/asr/InferenceTestWav2Letter.cc
@@ -17,10 +17,21 @@
 #include "TensorFlowLiteMicro.hpp"
 #include "Wav2LetterModel.hpp"
 #include "TestData_asr.hpp"
+#include "BufAttributes.hpp"
 
 #include <catch.hpp>
 #include <random>
 
+namespace arm {
+namespace app {
+    static uint8_t tensorArena[ACTIVATION_BUF_SZ] ACTIVATION_BUF_ATTRIBUTE;
+    namespace asr {
+        extern uint8_t* GetModelPointer();
+        extern size_t GetModelLen();
+    } /* namespace asr */
+} /* namespace app */
+} /* namespace arm */
+
 using namespace test;
 
 bool RunInference(arm::app::Model& model, const int8_t vec[], const size_t copySz)
@@ -58,7 +69,10 @@ TEST_CASE("Running random inference with TensorFlow Lite Micro and Wav2LetterMod
     arm::app::Wav2LetterModel model{};
 
     REQUIRE_FALSE(model.IsInited());
-    REQUIRE(model.Init());
+    REQUIRE(model.Init(arm::app::tensorArena,
+                    sizeof(arm::app::tensorArena),
+                    arm::app::asr::GetModelPointer(),
+                    arm::app::asr::GetModelLen()));
     REQUIRE(model.IsInited());
 
     REQUIRE(RunInferenceRandom(model));
@@ -96,11 +110,14 @@ TEST_CASE("Running inference with Tflu and Wav2LetterModel Int8", "[Wav2Letter]"
             arm::app::Wav2LetterModel model{};
 
             REQUIRE_FALSE(model.IsInited());
-            REQUIRE(model.Init());
+            REQUIRE(model.Init(arm::app::tensorArena,
+                    sizeof(arm::app::tensorArena),
+                    arm::app::asr::GetModelPointer(),
+                    arm::app::asr::GetModelLen()));
             REQUIRE(model.IsInited());
 
             TestInference<int8_t>(input_goldenFV, output_goldenFV, model);
 
         }
     }
-}
\ No newline at end of file
+}
diff --git a/tests/use_case/asr/Wav2LetterPostprocessingTest.cc b/tests/use_case/asr/Wav2LetterPostprocessingTest.cc
index 11c4919..9c3d658 100644
--- a/tests/use_case/asr/Wav2LetterPostprocessingTest.cc
+++ b/tests/use_case/asr/Wav2LetterPostprocessingTest.cc
@@ -17,11 +17,23 @@
 #include "Wav2LetterPostprocess.hpp"
 #include "Wav2LetterModel.hpp"
 #include "ClassificationResult.hpp"
+#include "BufAttributes.hpp"
 
 #include <algorithm>
 #include <catch.hpp>
 #include <limits>
 
+namespace arm {
+namespace app {
+    static uint8_t tensorArena[ACTIVATION_BUF_SZ] ACTIVATION_BUF_ATTRIBUTE;
+
+    namespace asr {
+        extern uint8_t* GetModelPointer();
+        extern size_t GetModelLen();
+    } /* namespace asr */
+} /* namespace app */
+} /* namespace arm */
+
 template <typename T>
 static TfLiteTensor GetTestTensor(
                         std::vector<int>&      shape,
@@ -51,7 +63,10 @@ TEST_CASE("Checking return value")
         const uint32_t outputCtxLen = 5;
         arm::app::AsrClassifier classifier;
         arm::app::Wav2LetterModel model;
-        model.Init();
+        model.Init(arm::app::tensorArena,
+                    sizeof(arm::app::tensorArena),
+                    arm::app::asr::GetModelPointer(),
+                    arm::app::asr::GetModelLen());
         std::vector<std::string> dummyLabels = {"a", "b", "$"};
         const uint32_t blankTokenIdx = 2;
         std::vector<arm::app::ClassificationResult> dummyResult;
@@ -71,7 +86,10 @@ TEST_CASE("Checking return value")
         const uint32_t outputCtxLen = 5;
         arm::app::AsrClassifier classifier;
         arm::app::Wav2LetterModel model;
-        model.Init();
+        model.Init(arm::app::tensorArena,
+                    sizeof(arm::app::tensorArena),
+                    arm::app::asr::GetModelPointer(),
+                    arm::app::asr::GetModelLen());
         std::vector<std::string> dummyLabels = {"a", "b", "$"};
         const uint32_t blankTokenIdx = 2;
         std::vector<arm::app::ClassificationResult> dummyResult;
@@ -102,7 +120,10 @@ TEST_CASE("Postprocessing - erasing required elements")
     std::vector<int> tensorShape = {1, 1, nRows, nCols};
     arm::app::AsrClassifier classifier;
     arm::app::Wav2LetterModel model;
-    model.Init();
+    model.Init(arm::app::tensorArena,
+                    sizeof(arm::app::tensorArena),
+                    arm::app::asr::GetModelPointer(),
+                    arm::app::asr::GetModelLen());
     std::vector<std::string> dummyLabels = {"a", "b", "$"};
     std::vector<arm::app::ClassificationResult> dummyResult;