commit 2181d0ac35f30202985a877950c88325ff665f6b
author Isabella Gottardi <isabella.gottardi@arm.com> Wed Apr 07 09:27:38 2021 +0100
committer Isabella Gottardi <isabella.gottardi@arm.com> Fri May 07 12:19:19 2021 +0100
tree e16c50d41d85945e0c2c864323ac1769b02af64f
parent d580eee180be219e118152cedabc9637da8574d6

MLECO-1766: Default build flow helper scripts added
MLECO-1882: Anomaly Detection use-case default model download added 
and tests updated to run with it.

Test data generation cmake logic moved from use-case cmakes to top-level cmake script.

Signed-off-by: Isabella Gottardi <isabella.gottardi@arm.com>
Change-Id: Ifde469e3585c37b9a53810236a92ce52d4fbb407

tests/use_case/ad/InferenceTestAD.cc

diff --git a/tests/use_case/ad/InferenceTestAD.cc b/tests/use_case/ad/InferenceTestAD.cc
index b87699d..d5e21c2 100644
--- a/tests/use_case/ad/InferenceTestAD.cc
+++ b/tests/use_case/ad/InferenceTestAD.cc
@@ -19,7 +19,7 @@
 #include <random>
 
 #include "AdModel.hpp"
-#include "AdGoldenInput.hpp"
+#include "TestData_ad.hpp"
 #include "hal.h"
 #include "TensorFlowLiteMicro.hpp"
 
@@ -27,6 +27,8 @@
 #define AD_IN_FEATURE_VEC_DATA_SIZE (1024)
 #endif /* AD_FEATURE_VEC_DATA_SIZE */
 
+using namespace test;
+
 bool RunInference(arm::app::Model& model, const int8_t vec[])
 {
     TfLiteTensor *inputTensor = model.GetInputTensor(0);
@@ -67,7 +69,7 @@
     TfLiteTensor *outputTensor = model.GetOutputTensor(0);
 
     REQUIRE(outputTensor);
-    REQUIRE(outputTensor->bytes == AD_OUT_FEATURE_VEC_DATA_SIZE);
+    REQUIRE(outputTensor->bytes == OFM_DATA_SIZE);
     auto tensorData = tflite::GetTensorData<T>(outputTensor);
     REQUIRE(tensorData);
 
@@ -77,7 +79,7 @@
     }
 }
 
-TEST_CASE("Running random inference with TensorFlow Lite Micro and AdModel Int8", "[AD][.]")
+TEST_CASE("Running random inference with TensorFlow Lite Micro and AdModel Int8", "[AD]")
 {
     arm::app::AdModel model{};
 
@@ -88,13 +90,22 @@
     REQUIRE(RunInferenceRandom(model));
 }
 
-TEST_CASE("Running golden vector inference with TensorFlow Lite Micro and AdModel Int8", "[AD][.]")
+TEST_CASE("Running golden vector inference with TensorFlow Lite Micro and AdModel Int8", "[AD]")
 {
-    arm::app::AdModel model{};
+    for (uint32_t i = 0 ; i < NUMBER_OF_FM_FILES; ++i) {
+        auto input_goldenFV = get_ifm_data_array(i);;
+        auto output_goldenFV = get_ofm_data_array(i);
 
-    REQUIRE_FALSE(model.IsInited());
-    REQUIRE(model.Init());
-    REQUIRE(model.IsInited());
+        DYNAMIC_SECTION("Executing inference with re-init")
+        {
+            arm::app::AdModel model{};
 
-    TestInference(ad_golden_input, ad_golden_out, model);
+            REQUIRE_FALSE(model.IsInited());
+            REQUIRE(model.Init());
+            REQUIRE(model.IsInited());
+
+            TestInference<int8_t>(input_goldenFV, output_goldenFV, model);
+
+        }
+    }
 }
\ No newline at end of file