Opensource ML embedded evaluation kit
Change-Id: I12e807f19f5cacad7cef82572b6dd48252fd61fd
diff --git a/tests/common/AppContextTest.cc b/tests/common/AppContextTest.cc
new file mode 100644
index 0000000..42b142d
--- /dev/null
+++ b/tests/common/AppContextTest.cc
@@ -0,0 +1,63 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "AppContext.hpp"
+
+#include <catch.hpp>
+
+TEST_CASE("Common: Application context")
+{
+ SECTION("Add primitive type Parameter")
+ {
+ arm::app::ApplicationContext context;
+ context.Set<uint32_t>("imgIndex", 0);
+ auto data = context.Get<uint32_t>("imgIndex");
+
+ REQUIRE(0 == data);
+
+ }
+
+ SECTION("Add object parameter")
+ {
+ arm::app::ApplicationContext context;
+ std::vector <std::string> vect{"a"};
+ context.Set<std::vector <std::string>>("vect", vect);
+ auto data = context.Get<std::vector <std::string>>("vect");
+
+ REQUIRE(vect == data);
+ }
+
+ SECTION("Add reference object parameter")
+ {
+ arm::app::ApplicationContext context;
+ std::vector <std::string> vect{"a"};
+ context.Set<std::vector <std::string>&>("vect", vect);
+ auto data = context.Get<std::vector <std::string>&>("vect");
+
+ REQUIRE(vect == data);
+ }
+
+ SECTION("Add object pointer parameter")
+ {
+ arm::app::ApplicationContext context;
+ std::vector <std::string>* vect = new std::vector <std::string>{"a"};
+ context.Set<std::vector <std::string>*>("vect", vect);
+ auto data = context.Get<std::vector <std::string>*>("vect");
+
+ REQUIRE(vect == data);
+ delete(vect);
+ }
+}
\ No newline at end of file
diff --git a/tests/common/ClassifierTests.cc b/tests/common/ClassifierTests.cc
new file mode 100644
index 0000000..f08a09a
--- /dev/null
+++ b/tests/common/ClassifierTests.cc
@@ -0,0 +1,76 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "Classifier.hpp"
+
+#include <catch.hpp>
+
+TEST_CASE("Common classifier")
+{
+ SECTION("Test invalid classifier")
+ {
+ TfLiteTensor* outputTens = nullptr;
+ std::vector <arm::app::ClassificationResult> resultVec;
+ arm::app::Classifier classifier;
+ REQUIRE(!classifier.GetClassificationResults(outputTens, resultVec, {}, 5));
+ }
+
+ SECTION("Test valid classifier UINT8")
+ {
+ const int dimArray[] = {1, 1001};
+ std::vector <std::string> labels(1001);
+ std::vector <uint8_t> outputVec(1001);
+ TfLiteIntArray* dims= tflite::testing::IntArrayFromInts(dimArray);
+ TfLiteTensor tfTensor = tflite::testing::CreateQuantizedTensor(
+ outputVec.data(), dims, 1, 0, "test");
+ TfLiteTensor* outputTensor = &tfTensor;
+ std::vector <arm::app::ClassificationResult> resultVec;
+ arm::app::Classifier classifier;
+ REQUIRE(classifier.GetClassificationResults(outputTensor, resultVec, labels, 5));
+ REQUIRE(5 == resultVec.size());
+ }
+
+ SECTION("Get classification results")
+ {
+ const int dimArray[] = {1, 1001};
+ std::vector <std::string> labels(1001);
+ std::vector<uint8_t> outputVec(1001, static_cast<uint8_t>(5));
+ TfLiteIntArray* dims= tflite::testing::IntArrayFromInts(dimArray);
+ TfLiteTensor tfTensor = tflite::testing::CreateQuantizedTensor(
+ outputVec.data(), dims, 1, 0, "test");
+ TfLiteTensor* outputTensor = &tfTensor;
+
+ std::vector <arm::app::ClassificationResult> resultVec;
+
+ /* Set the top five results. */
+ std::vector<std::pair<uint32_t, uint8_t>> selectedResults {
+ {0, 8}, {20, 7}, {10, 7}, {15, 9}, {1000, 10}};
+
+ for (size_t i = 0; i < selectedResults.size(); ++i) {
+ outputVec[selectedResults[i].first] = selectedResults[i].second;
+ }
+
+ arm::app::Classifier classifier;
+ REQUIRE(classifier.GetClassificationResults(outputTensor, resultVec, labels, 5));
+ REQUIRE(5 == resultVec.size());
+
+ REQUIRE(resultVec[0].m_labelIdx == 1000);
+ REQUIRE(resultVec[1].m_labelIdx == 15);
+ REQUIRE(resultVec[2].m_labelIdx == 0);
+ REQUIRE(resultVec[3].m_labelIdx == 20);
+ REQUIRE(resultVec[4].m_labelIdx == 10);
+ }
+}
diff --git a/tests/common/ProfilerTests.cc b/tests/common/ProfilerTests.cc
new file mode 100644
index 0000000..caf492b
--- /dev/null
+++ b/tests/common/ProfilerTests.cc
@@ -0,0 +1,61 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "Profiler.hpp"
+
+#include "AppContext.hpp"
+#include "TensorFlowLiteMicro.hpp"
+
+#include <catch.hpp>
+#include <iostream>
+
+
+TEST_CASE("Common: Test Profiler")
+{
+ hal_platform platform;
+ data_acq_module data_acq {};
+ data_psn_module data_psn {};
+ platform_timer timer {};
+
+ /* Initialise the HAL and platform. */
+ hal_init(&platform, &data_acq, &data_psn, &timer);
+ hal_platform_init(&platform);
+
+ /* An invalid profiler shouldn't be of much use. */
+ arm::app::Profiler profilerInvalid {nullptr, "test_invalid"};
+ REQUIRE(false == profilerInvalid.StartProfiling());
+ REQUIRE(false == profilerInvalid.StopProfiling());
+
+ arm::app::Profiler profilerValid{&platform, "test_valid"};
+ REQUIRE(true == profilerValid.StartProfiling());
+ REQUIRE(true == profilerValid.StopProfiling());
+
+ std::string strProfile = profilerValid.GetResultsAndReset();
+ REQUIRE(std::string::npos != strProfile.find("test_valid"));
+
+#if defined(CPU_PROFILE_ENABLED)
+ /* We should have milliseconds elapsed. */
+ REQUIRE(std::string::npos != strProfile.find("ms"));
+#endif /* defined(CPU_PROFILE_ENABLED) */
+
+ /* Abuse should fail: */
+ REQUIRE(false == profilerValid.StopProfiling()); /* We need to start it first. */
+ REQUIRE(true == profilerValid.StartProfiling()); /* Should be able to start it fine. */
+ REQUIRE(false == profilerValid.StartProfiling()); /* Can't restart it without resetting. */
+ profilerValid.Reset(); /* Reset. */
+ REQUIRE(true == profilerValid.StartProfiling()); /* Can start it again now. */
+ REQUIRE(true == profilerValid.StopProfiling()); /* Can start it again now. */
+}
diff --git a/tests/common/SlidingWindowTests.cc b/tests/common/SlidingWindowTests.cc
new file mode 100644
index 0000000..bfdb5b7
--- /dev/null
+++ b/tests/common/SlidingWindowTests.cc
@@ -0,0 +1,266 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "AudioUtils.hpp"
+#include "catch.hpp"
+
+TEST_CASE("Common: Slide long data")
+{
+ std::vector<int> test{1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
+
+ SECTION("Fit the data")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 1, 1);
+
+ for (int i = 0 ; i < 10; ++i) {
+ REQUIRE(slider.HasNext());
+ REQUIRE(*slider.Next() == i + 1);
+ }
+
+ REQUIRE(!slider.HasNext());
+ REQUIRE(nullptr == slider.Next());
+ }
+
+ SECTION("Fit the data stride> window")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 2, 3);
+
+ REQUIRE(slider.HasNext());
+ REQUIRE(*slider.Next() == 1);
+
+ REQUIRE(slider.HasNext());
+ REQUIRE(*slider.Next() == 4);
+
+ REQUIRE(slider.HasNext());
+ REQUIRE(*slider.Next() == 7);
+
+ REQUIRE(!slider.HasNext());
+ REQUIRE(nullptr == slider.Next());
+ }
+
+ SECTION("Fit the data stride < window")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 5, 1);
+
+ for (int i = 0 ; i < 6; i++) {
+ REQUIRE(slider.HasNext());
+ REQUIRE(*slider.Next() == i + 1);
+ }
+
+ REQUIRE(!slider.HasNext());
+ REQUIRE(nullptr == slider.Next());
+ }
+}
+
+
+TEST_CASE("Common: Slide data size 1")
+{
+ std::vector<int> test{1};
+
+ SECTION("Fit the data")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 1, 1);
+
+ REQUIRE(slider.HasNext());
+ REQUIRE(*slider.Next() == 1);
+ REQUIRE(!slider.HasNext());
+ REQUIRE(nullptr == slider.Next());
+ }
+
+ SECTION("Does not Fit the data because of big window")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 2, 1);
+
+ REQUIRE(!slider.HasNext());
+ REQUIRE(nullptr == slider.Next());
+ }
+
+ SECTION("Does not Fit the data because of big stride")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 1, 2);
+
+ REQUIRE(slider.HasNext());
+ REQUIRE(*slider.Next() == 1);
+ REQUIRE(!slider.HasNext());
+ REQUIRE(nullptr == slider.Next());
+ }
+
+}
+
+
+TEST_CASE("Common: Slide reset")
+{
+ SECTION("current range")
+ {
+ std::vector<int> test{1};
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 1, 1);
+ int *saved = slider.Next();
+ slider.Reset();
+
+ REQUIRE(slider.Next() == saved);
+ }
+
+ SECTION("new range")
+ {
+ std::vector<int> test{1};
+ std::vector<int> test2{100};
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 1, 1);
+ slider.Next();
+ slider.Reset(test2.data());
+
+ REQUIRE(*slider.Next() == 100);
+ }
+}
+
+
+TEST_CASE("Common: Slide fast forward")
+{
+ std::vector<int> test{1, 2, 3, 4, 5};
+
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 1, 1);
+ SECTION("at the beginning") {
+ slider.FastForward(3);
+
+ REQUIRE(slider.HasNext());
+ REQUIRE(*slider.Next() == 4);
+ }
+
+ SECTION("in the middle")
+ {
+ slider.Next();
+ slider.FastForward(3);
+
+ REQUIRE(slider.HasNext());
+ REQUIRE(*slider.Next() == 4);
+ }
+
+ SECTION("at the end")
+ {
+ while(slider.HasNext()) {
+ slider.Next();
+ }
+ slider.FastForward(3);
+
+ REQUIRE(slider.HasNext());
+ REQUIRE(*slider.Next() == 4);
+ }
+
+ SECTION("out of the range")
+ {
+ slider.FastForward(100);
+
+ REQUIRE(!slider.HasNext());
+ REQUIRE(slider.Next() == nullptr);
+ }
+}
+
+
+TEST_CASE("Common: Slide Index")
+{
+ std::vector<int> test{1, 2, 3, 4, 5};
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 1, 1);
+ REQUIRE(slider.Index() == 0);
+ for (int i = 0; i < 5; i++) {
+ slider.Next();
+ REQUIRE(slider.Index() == i);
+ }
+}
+
+
+TEST_CASE("Common: Total strides")
+{
+ std::vector<int> test{1, 2, 3, 4, 5};
+
+ SECTION("Element by element")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 1, 1);
+ REQUIRE(slider.TotalStrides() == 4 );
+ }
+
+ SECTION("Step through element")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 1, 2);
+ REQUIRE(slider.TotalStrides() == 2 );
+ }
+
+ SECTION("Window = data")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 5, 2);
+ REQUIRE(slider.TotalStrides() == 0 );
+ }
+
+ SECTION("Window > data")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 6, 2);
+ REQUIRE(slider.TotalStrides() == 0 );
+ }
+
+ SECTION("Window < data, not enough for the next stride")
+ {
+ auto slider = arm::app::audio::SlidingWindow<int>(test.data(), test.size(), 4, 2);
+ REQUIRE(slider.TotalStrides() == 0 );
+ }
+}
+
+
+TEST_CASE("Common: Next window data index")
+{
+ std::vector<int> test{1, 2, 3, 4, 5};
+
+ /* Check we get the correct index returned */
+ SECTION("Stride 1")
+ {
+ auto slider = arm::app::audio::ASRSlidingWindow<int>(test.data(), test.size(), 1, 1);
+ REQUIRE(slider.NextWindowStartIndex() == 0);
+ slider.Next();
+ REQUIRE(slider.NextWindowStartIndex() == 1);
+ slider.Next();
+ REQUIRE(slider.NextWindowStartIndex() == 2);
+ slider.Next();
+ REQUIRE(slider.NextWindowStartIndex() == 3);
+ slider.Next();
+ REQUIRE(slider.NextWindowStartIndex() == 4);
+ slider.Next();
+ REQUIRE(slider.NextWindowStartIndex() == 5);
+ slider.Next();
+ REQUIRE(slider.NextWindowStartIndex() == 5);
+ }
+
+ SECTION("Stride 2")
+ {
+ auto slider = arm::app::audio::ASRSlidingWindow<int>(test.data(), test.size(), 1, 2);
+ REQUIRE(slider.NextWindowStartIndex() == 0);
+ slider.Next();
+ REQUIRE(slider.NextWindowStartIndex() == 2);
+ REQUIRE(slider.NextWindowStartIndex() == 2);
+ slider.Next();
+ REQUIRE(slider.NextWindowStartIndex() == 4);
+ }
+
+ SECTION("Stride 3")
+ {
+ auto slider = arm::app::audio::ASRSlidingWindow<int>(test.data(), test.size(), 1, 3);
+ REQUIRE(slider.NextWindowStartIndex() == 0);
+ slider.Next();
+ REQUIRE(slider.NextWindowStartIndex() == 3);
+ REQUIRE(slider.NextWindowStartIndex() == 3);
+ slider.Next();
+ REQUIRE(slider.NextWindowStartIndex() == 6);
+ REQUIRE(!slider.HasNext());
+ REQUIRE(slider.Next() == nullptr);
+ REQUIRE(slider.NextWindowStartIndex() == 6);
+ }
+}
diff --git a/tests/resources/golden_fv/AdGoldenInput.hpp b/tests/resources/golden_fv/AdGoldenInput.hpp
new file mode 100644
index 0000000..41d1a89
--- /dev/null
+++ b/tests/resources/golden_fv/AdGoldenInput.hpp
@@ -0,0 +1,132 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef AD_GOLDEN_OUTPUTS_HPP
+#define AD_GOLDEN_OUTPUTS_HPP
+
+#include "Model.hpp"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+#include <stdint.h>
+
+#ifndef AD_FEATURE_VEC_DATA_SIZE
+#define AD_IN_FEATURE_VEC_DATA_SIZE (1024)
+#define AD_OUT_FEATURE_VEC_DATA_SIZE (8)
+#endif /* AD_FEATURE_VEC_DATA_SIZE */
+
+/* Golden input. */
+uint8_t ad_golden_input[AD_IN_FEATURE_VEC_DATA_SIZE] = {
+ 0x7a, 0x7c, 0x7f, 0x7c, 0x7b, 0x61, 0x7f, 0x75, 0x7f, 0x6b, 0x6d, 0x71,
+ 0x7f, 0x6e, 0x7a, 0x76, 0x7f, 0x7f, 0x65, 0x7f, 0x7f, 0x6f, 0x5d, 0x67,
+ 0x7f, 0x5b, 0x7a, 0x43, 0x65, 0x69, 0x4e, 0x63, 0x5f, 0x56, 0x4e, 0x64,
+ 0x36, 0x4a, 0x3c, 0x56, 0x3a, 0x61, 0x71, 0x74, 0x72, 0x6f, 0x71, 0x71,
+ 0x66, 0x7b, 0x68, 0x62, 0x44, 0x5f, 0x2f, 0x3d, 0x56, 0x5b, 0x5b, 0x4d,
+ 0x5f, 0x59, 0x58, 0x6e, 0x4f, 0x3d, 0x48, 0x5f, 0x46, 0x38, 0x48, 0x4f,
+ 0x46, 0x74, 0x6d, 0x61, 0x60, 0x63, 0x6a, 0x68, 0x62, 0x69, 0x63, 0x5c,
+ 0x6e, 0x4d, 0x4c, 0x3c, 0x5a, 0x55, 0x4a, 0x5d, 0x59, 0x66, 0x67, 0x6c,
+ 0x55, 0x40, 0x49, 0x47, 0x56, 0x61, 0x48, 0x4d, 0x64, 0x61, 0x77, 0x7e,
+ 0x37, 0x63, 0x52, 0x3e, 0x57, 0x4d, 0x54, 0x4f, 0x3b, 0x4c, 0x54, 0x50,
+ 0x55, 0x4c, 0x57, 0x58, 0x45, 0x7b, 0x74, 0x58, 0x39, 0x34, 0x3c, 0x38,
+ 0x3e, 0x1e, 0x22, 0x46, 0x2c, 0x7a, 0x6e, 0x74, 0x72, 0x70, 0x61, 0x7d,
+ 0x69, 0x79, 0x66, 0x3c, 0x33, 0x20, 0x3a, 0x20, 0x34, 0x29, 0x3c, 0x4e,
+ 0x47, 0x5b, 0x78, 0x47, 0x36, 0x30, 0x18, 0x45, 0x24, 0x25, 0x2c, 0x75,
+ 0x71, 0x70, 0x7f, 0x73, 0x6c, 0x6c, 0x77, 0x6a, 0x6d, 0x6b, 0x6d, 0x5b,
+ 0x36, 0x43, 0x34, 0x2b, 0x2e, 0x3b, 0x32, 0x67, 0x2a, 0x5b, 0x7f, 0x66,
+ 0x32, 0x24, 0x28, 0x29, 0x2d, 0x31, 0x2b, 0x1d, 0x0d, 0x40, 0x3a, 0x49,
+ 0x3b, 0x42, 0x37, 0x43, 0x40, 0x44, 0x4f, 0x40, 0x25, 0x1b, 0x33, 0x32,
+ 0x15, 0x3b, 0x22, 0x33, 0x45, 0x4e, 0x45, 0x3a, 0x2a, 0x10, 0x19, 0x3a,
+ 0x27, 0x25, 0x18, 0x0d, 0x0d, 0x3a, 0x36, 0x2d, 0x21, 0x34, 0x25, 0x38,
+ 0x26, 0x33, 0x2f, 0x33, 0x2a, 0x21, 0x36, 0x1e, 0x2b, 0x28, 0x29, 0x31,
+ 0x25, 0x2e, 0x4d, 0x32, 0x42, 0x1b, 0x37, 0x1a, 0x34, 0x36, 0x23, 0x25,
+ 0x2b, 0x3f, 0x46, 0x41, 0x4c, 0x35, 0x39, 0x2d, 0x37, 0x4d, 0x42, 0x46,
+ 0x27, 0x36, 0x20, 0x34, 0x10, 0x32, 0x19, 0x21, 0x33, 0x3b, 0x39, 0x46,
+ 0x10, 0xf3, 0x26, 0x13, 0x24, 0x1f, 0x28, 0x18, 0x29, 0x20, 0x20, 0x14,
+ 0x1f, 0x17, 0x27, 0x34, 0x38, 0x3e, 0x26, 0x37, 0x20, 0x33, 0x16, 0x26,
+ 0x0e, 0x1c, 0x31, 0x1d, 0x23, 0x2e, 0x44, 0x38, 0x25, 0x2f, 0x27, 0x39,
+ 0x3b, 0x2b, 0x36, 0x3c, 0x35, 0x3f, 0x2d, 0x3f, 0x42, 0x32, 0x43, 0x4e,
+ 0x55, 0x3d, 0x17, 0x2e, 0x39, 0x20, 0x31, 0x41, 0x38, 0x2b, 0x31, 0x38,
+ 0x46, 0x3f, 0x1e, 0x2d, 0x0a, 0x07, 0x18, 0xfc, 0x1a, 0x14, 0xec, 0x25,
+ 0x1e, 0x30, 0x3c, 0x37, 0x2a, 0x47, 0x3c, 0x3b, 0x3b, 0x37, 0x2b, 0x22,
+ 0x18, 0x1b, 0x31, 0x1e, 0x0e, 0x22, 0x13, 0x11, 0x10, 0x10, 0x14, 0x22,
+ 0x0c, 0x0e, 0x18, 0x03, 0x0e, 0x03, 0x03, 0x08, 0x26, 0x0c, 0x1a, 0x0a,
+ 0x06, 0x2d, 0x1e, 0x1e, 0x14, 0x1a, 0x26, 0x1d, 0x06, 0x06, 0x1c, 0x0e,
+ 0x16, 0x06, 0x09, 0x13, 0x1c, 0x21, 0x25, 0x0d, 0x1c, 0x00, 0xfa, 0xfd,
+ 0x13, 0xfa, 0x18, 0xff, 0x0d, 0x08, 0x23, 0x2e, 0x26, 0x1d, 0x14, 0x10,
+ 0x14, 0x28, 0x14, 0x1b, 0x05, 0x0a, 0xff, 0xfa, 0x1a, 0x18, 0x11, 0x13,
+ 0x16, 0x0f, 0x07, 0x12, 0x05, 0x00, 0x13, 0xf3, 0x05, 0x01, 0x01, 0x01,
+ 0x1a, 0x16, 0x2b, 0x26, 0x1e, 0x21, 0x15, 0x13, 0x12, 0x28, 0x19, 0x1c,
+ 0xff, 0xf8, 0xf0, 0x02, 0x01, 0x05, 0x04, 0x19, 0x11, 0x14, 0x1b, 0x15,
+ 0xea, 0x19, 0x12, 0x02, 0x0f, 0x11, 0xee, 0xfe, 0x1c, 0x2f, 0x19, 0x38,
+ 0x2a, 0x30, 0x26, 0x1e, 0x28, 0x29, 0x24, 0x12, 0x01, 0x12, 0xff, 0x0c,
+ 0x09, 0x0b, 0x26, 0x24, 0x21, 0x24, 0x11, 0x21, 0x13, 0x17, 0xf8, 0x0c,
+ 0xfd, 0x03, 0xf9, 0xfc, 0x03, 0x20, 0x14, 0x34, 0x1e, 0x30, 0x2e, 0x25,
+ 0x23, 0x29, 0x16, 0x01, 0xf4, 0x05, 0x15, 0x05, 0xf9, 0x02, 0xea, 0x32,
+ 0x38, 0x28, 0x28, 0x18, 0xf6, 0xfa, 0xfb, 0xff, 0xf9, 0xee, 0xff, 0x01,
+ 0xfc, 0x41, 0x40, 0x2b, 0x2f, 0x1f, 0x1c, 0x20, 0x21, 0x28, 0x2b, 0x17,
+ 0xfd, 0xf9, 0x07, 0xf5, 0x01, 0xf8, 0xfe, 0xfe, 0x11, 0x14, 0x27, 0x0e,
+ 0xf5, 0xfd, 0xe7, 0x05, 0xef, 0xee, 0xe9, 0xf6, 0xff, 0x10, 0x0c, 0x16,
+ 0x15, 0x16, 0x0d, 0x1c, 0x15, 0x1c, 0x09, 0xf6, 0x00, 0xfe, 0xf4, 0xf8,
+ 0xe1, 0x0a, 0xfa, 0x05, 0x0b, 0x1b, 0x19, 0x05, 0xf0, 0xec, 0xec, 0x02,
+ 0xf0, 0xec, 0xf4, 0xec, 0xe7, 0x30, 0x47, 0x2d, 0x31, 0x2a, 0x24, 0x31,
+ 0x1f, 0x31, 0x2c, 0x07, 0xe4, 0xfa, 0xef, 0xee, 0xfe, 0xf5, 0xf1, 0x1a,
+ 0x18, 0x33, 0x1c, 0x10, 0xf5, 0xce, 0xeb, 0xe3, 0xf1, 0xec, 0xe7, 0xed,
+ 0xde, 0x19, 0x2e, 0x11, 0x1f, 0x17, 0x19, 0x23, 0x17, 0x1d, 0x1b, 0x01,
+ 0xef, 0xed, 0xeb, 0xf8, 0xe9, 0xf0, 0xf3, 0x1c, 0x19, 0x2a, 0x0d, 0x19,
+ 0xe3, 0xe1, 0xee, 0xe0, 0xe7, 0xee, 0xe7, 0xee, 0xea, 0x30, 0x2e, 0x2f,
+ 0x32, 0x11, 0x29, 0x38, 0x0f, 0x1a, 0x29, 0x24, 0xe6, 0xfa, 0xfc, 0xf0,
+ 0xed, 0xec, 0xe1, 0x2e, 0x13, 0x29, 0x22, 0x16, 0xd4, 0xee, 0xeb, 0xee,
+ 0xd3, 0xe4, 0xe4, 0xe5, 0xee, 0x23, 0x08, 0x10, 0x15, 0x17, 0x1b, 0x2b,
+ 0x1b, 0x1d, 0x17, 0x03, 0xf8, 0xdd, 0xe3, 0xe8, 0xe5, 0xd8, 0xdb, 0x09,
+ 0xf5, 0x10, 0x16, 0x14, 0xd9, 0xde, 0xd0, 0xd7, 0xd7, 0xda, 0xe0, 0xe1,
+ 0xe4, 0x0f, 0x17, 0x04, 0x10, 0x0c, 0x14, 0x1d, 0x1d, 0x17, 0x15, 0xfa,
+ 0xd9, 0xd6, 0xe1, 0xdf, 0xd7, 0xdf, 0xd5, 0x18, 0xf5, 0x14, 0x08, 0x0b,
+ 0xd0, 0xd6, 0xd4, 0xd7, 0xc6, 0xda, 0xc5, 0xda, 0xdc, 0x14, 0x26, 0x15,
+ 0x19, 0x0d, 0x0b, 0x0f, 0x07, 0x09, 0x1b, 0x03, 0xdc, 0xda, 0xd6, 0xd8,
+ 0xc0, 0xc5, 0xdc, 0x08, 0xfb, 0x10, 0x0d, 0x13, 0xd8, 0xde, 0xcb, 0xd6,
+ 0xd0, 0xc7, 0xcd, 0xdc, 0xc3, 0x0c, 0x0f, 0x08, 0x13, 0x13, 0x25, 0x25,
+ 0x13, 0x1f, 0x11, 0xee, 0xd0, 0xd0, 0xd2, 0xcd, 0xbf, 0xca, 0xd2, 0x0a,
+ 0xeb, 0x04, 0x03, 0x10, 0xd0, 0xcd, 0xb1, 0xc7, 0xca, 0xbf, 0xe1, 0xdd,
+ 0xce, 0x2b, 0x19, 0x20, 0x20, 0x14, 0x24, 0x34, 0x27, 0x2c, 0x25, 0xf8,
+ 0xd5, 0xc7, 0xcb, 0xba, 0xc0, 0xcf, 0xc4, 0x14, 0x06, 0x1f, 0x28, 0x10,
+ 0xc9, 0xc9, 0xc3, 0xbf, 0xc4, 0xcd, 0xd2, 0xcc, 0xd4, 0x15, 0x27, 0x1e,
+ 0x19, 0x05, 0x18, 0x1d, 0x24, 0x1a, 0x1f, 0xf9, 0xcc, 0xd3, 0xc3, 0xcd,
+ 0xcc, 0xc1, 0xd5, 0x10, 0xe7, 0x1d, 0x12, 0x04, 0xb4, 0xb9, 0xb0, 0xb9,
+ 0xb1, 0xb1, 0xbb, 0xd2, 0xb0, 0xff, 0x22, 0x06, 0xff, 0xf7, 0xfb, 0x07,
+ 0xf8, 0xfa, 0x03, 0xef, 0xc2, 0xc7, 0xb9, 0xbb, 0xb4, 0xb2, 0xb5, 0xf2,
+ 0xcc, 0x05, 0xf1, 0xea, 0xb0, 0xb1, 0xa7, 0xab, 0xa9, 0xa6, 0xb2, 0xbf,
+ 0xb4, 0x04, 0x0f, 0x02, 0x0e, 0x0a, 0x05, 0x07, 0xff, 0x04, 0x0a, 0xe2,
+ 0xac, 0xad, 0xa9, 0xa0, 0xa8, 0xa3, 0x9a, 0xef, 0xd3, 0xf5, 0x03, 0xfd,
+ 0x9c, 0x99, 0x99, 0x9c, 0x96, 0x99, 0xaf, 0xa8, 0xaa, 0xfd, 0x09, 0x0e,
+ 0xf5, 0xed, 0xe7, 0xf4, 0xec, 0xf4, 0xf1, 0xd5, 0xa5, 0x9a, 0x9e, 0x98,
+ 0xa7, 0x99, 0xa2, 0xd9, 0xc2, 0xf1, 0xee, 0xec, 0x8a, 0x86, 0x8c, 0x8d,
+ 0x84, 0x88, 0xa0, 0xad, 0xa2, 0xe5, 0x02, 0xff, 0xf5, 0xe4, 0xee, 0xf1,
+ 0xf2, 0xec, 0xf0, 0xc9, 0x9e, 0x97, 0x98, 0x89, 0x8f, 0x88, 0x93, 0xd9,
+ 0xd1, 0xf8, 0xeb, 0xde
+};
+
+/* Golden output */
+uint8_t ad_golden_out[AD_OUT_FEATURE_VEC_DATA_SIZE] = {
+ 0x3a, 0x7f, 0x36, 0x76, 0x80, 0x80, 0x80, 0x80
+};
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif /* AD_GOLDEN_OUTPUTS_HPP */
diff --git a/tests/resources/golden_fv/AsrGoldenFeatures.hpp b/tests/resources/golden_fv/AsrGoldenFeatures.hpp
new file mode 100644
index 0000000..a230a52
--- /dev/null
+++ b/tests/resources/golden_fv/AsrGoldenFeatures.hpp
@@ -0,0 +1,931 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef ASR_F_GOLDEN_HPP
+#define ASR_F_GOLDEN_HPP
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+#include <stdint.h>
+
+size_t golden_asr_mfcc_len = 13U * 296U;
+size_t golden_diff1_len = golden_asr_mfcc_len;
+size_t golden_diff2_len = golden_asr_mfcc_len;
+
+static const float golden_asr_mfcc[] = {
+/* 13 features, 296 time samples */
+-739.77203, 4.43339, 4.14916, 3.94062, 3.75471, 3.36722, 2.75536, 2.15424, 1.70661, 1.26036, 0.63381, -0.07275, -0.61404,
+-741.22699, 2.43739, 2.19547, 1.81668, 1.33471, 0.79128, 0.23156, -0.30073, -0.76779, -1.14135, -1.40496, -1.55474, -1.59852,
+-740.28369, 3.77706, 3.55944, 3.23880, 2.85630, 2.43850, 1.98858, 1.49232, 0.93505, 0.31964, -0.32507, -0.95050, -1.50613,
+-737.92542, 7.08773, 6.79751, 6.36016, 5.82753, 5.24427, 4.63403, 3.99524, 3.30806, 2.54938, 1.70949, 0.80348, -0.12769,
+-737.88190, 7.17392, 6.94397, 6.56755, 6.05465, 5.41886, 4.67691, 3.84815, 2.95400, 2.01727, 1.06150, 0.11023, -0.81362,
+-740.40613, 3.61488, 3.41837, 3.10070, 2.67607, 2.16330, 1.58483, 0.96553, 0.33144, -0.29155, -0.87899, -1.40899, -1.86323,
+-738.04297, 6.88258, 6.47138, 5.82175, 4.98088, 4.00386, 2.94619, 1.85797, 0.78088, -0.25189, -1.21348, -2.08038, -2.83026,
+-739.10394, 5.01142, 4.08197, 3.61993, 3.46862, 2.79344, 1.53009, 0.59595, 0.51155, 0.61026, 0.09230, -0.73804, -0.99980,
+-738.93628, 5.04577, 3.92978, 3.86487, 4.45355, 4.15855, 2.83126, 1.97671, 2.32735, 2.63497, 1.63883, 0.06747, -0.52301,
+-742.09735, 1.27576, 1.23579, 1.17278, 1.08758, 0.97981, 0.85158, 0.70800, 0.55358, 0.39015, 0.21937, 0.04588, -0.12424,
+-740.26038, 3.81065, 3.58432, 3.22149, 2.74267, 2.17462, 1.54851, 0.89788, 0.25634, -0.34453, -0.87725, -1.32006, -1.65818,
+-738.87238, 5.63912, 5.15087, 4.61127, 4.02923, 3.28429, 2.43234, 1.70882, 1.20934, 0.76495, 0.22197, -0.31741, -0.67138,
+-738.80823, 5.85002, 5.58049, 5.14473, 4.56218, 3.85858, 3.06471, 2.21470, 1.34432, 0.48918, -0.31712, -1.04458, -1.66828,
+-737.43085, 7.76511, 7.40725, 6.84653, 6.11416, 5.24155, 4.27151, 3.25613, 2.23841, 1.24139, 0.27895, -0.63012, -1.46581,
+-737.83099, 7.12094, 6.58481, 5.70745, 4.61185, 3.33776, 2.02636, 0.73143, -0.42896, -1.41877, -2.17289, -2.68819, -2.96023,
+-738.05359, 6.74544, 6.00377, 4.91264, 3.64911, 2.39284, 1.28308, 0.39052, -0.28846, -0.81449, -1.27167, -1.72931, -2.21198,
+-733.09210, 11.21165, 6.83860, 6.50434, 8.39739, 6.62222, 1.12450, -2.07976, -0.50446, 1.11805, -1.27790, -4.70090, -4.26429,
+-729.61566, 10.02992, -1.95083, 1.63069, 11.62741, 8.21267, -4.95377, -8.36486, 0.19372, 4.14391, -3.06428, -8.99785, -4.47088,
+-723.47961, 10.17970, -9.74782, -1.55895, 11.08994, 8.48012, -0.16512, -6.58712, -3.57666, 7.86839, 7.80519, -4.68555, -5.37104,
+-703.88519, 18.29580, -21.44657, -6.79528, 12.08492, 8.75593, 2.90998, -1.51398, -1.36442, 6.59666, 1.81764, -9.89391, -4.18426,
+-678.76422, 19.09791, -33.17283, 1.54777, 14.24737, 8.83076, 2.65867, -3.69481, -3.60083, -0.10980, 0.55969, -1.57821, -3.58482,
+-597.23285, 37.85891, -60.26614, -0.12251, 14.22423, -0.90098, 0.90394, 0.41278, -4.10125, 6.44201, 6.07266, 11.16191, -6.44330,
+-487.76270, 29.97835, -62.39044, -5.40837, 11.29997, 6.95592, -5.83144, 0.48654, -11.59783, 10.14861, 7.22627, 12.45544, -14.93312,
+-468.18643, 32.67844, -46.44635, -7.10132, 3.99336, 12.08127, -4.66342, 4.15338, -17.32649, -4.82752, -10.19122, -2.54350, -13.77276,
+-469.04898, 37.73291, -47.50086, 5.52127, 3.27568, 6.41865, -13.02156, -3.75707, -4.57083, 0.00712, -10.25383, -10.10860, -8.79650,
+-468.63696, 42.29890, -48.59408, 5.51896, 12.85027, 3.59784, -19.76094, -5.88601, -5.34028, 3.93530, -8.92158, -14.67978, -14.06335,
+-484.16913, 47.05151, -50.70958, -3.16510, 6.97707, 11.57512, -4.71207, 10.11598, 7.59590, 11.88781, -5.98053, -3.78069, -1.87512,
+-513.99847, 38.55527, -58.36864, -3.13968, 5.45301, 10.91985, -3.15140, -0.44534, 0.41920, 15.86110, 3.14245, -0.24400, -10.29185,
+-525.34448, 53.88523, -61.43047, -6.67531, 16.82977, 18.57971, 1.81502, 6.59831, 3.63511, 16.62849, -6.21790, -0.93611, -10.05373,
+-543.47412, 67.34111, -53.03713, -11.67502, 16.99445, 17.41154, 10.10119, 9.28551, -2.13365, 15.32820, -4.74680, 3.89862, 1.69543,
+-543.86810, 95.82130, -44.91877, -27.12481, 7.24652, 9.93297, 2.24394, 8.90679, 3.20333, 9.80860, -13.70252, -9.32810, -1.20880,
+-540.39093, 118.15536, -39.92270, -31.31052, 8.73977, 20.39213, 2.70147, -6.48235, -11.14444, 2.80034, -5.70351, -9.33047, -3.82105,
+-559.33344, 113.90231, -45.61569, -36.66971, 11.51530, 18.66145, 5.43105, -5.79920, -15.95238, 11.71870, 3.30188, -17.29617, -0.12055,
+-611.22729, 92.45084, -33.29684, -45.60332, -0.57918, 19.67272, 18.25746, 2.54525, -1.95916, 10.47044, 0.64767, -23.26884, -10.61353,
+-673.00159, 63.06639, 4.17435, -13.07201, 15.45242, 36.55398, 28.04820, 6.53190, -2.03077, -4.86843, -10.15063, -7.98050, 11.46151,
+-685.77118, 60.38826, 23.26720, 5.49815, 14.32310, 24.30405, 22.31143, 14.91874, 12.03119, 8.62008, 2.74104, 0.13998, 4.97190,
+-614.80969, 123.72738, 24.36467, -23.45894, -9.78909, 12.62901, 13.46521, 0.35274, -5.22431, 3.50167, 1.96512, -11.65986, -19.05206,
+-570.55817, 138.50626, 23.04182, -24.43203, -6.62432, 8.97017, -1.10296, -6.29671, -15.93489, 5.53342, -1.25716, -13.43966, -28.57895,
+-445.96667, 164.02409, 5.72825, -52.08717, -16.37173, 10.28557, 10.33937, -2.31468, -20.52966, 15.33060, -3.55347, -16.33257, -28.28063,
+-363.43756, 175.12576, -3.31680, -66.65984, -19.85510, 7.41258, 11.93293, -0.79320, -16.91802, 20.56325, -0.02419, -12.53419, -39.70355,
+-348.60983, 154.19067, 7.74570, -50.03997, -22.13355, 9.42086, 9.85655, 9.36244, -5.75583, 21.20298, -6.69417, -8.00366, -43.66351,
+-299.13873, 152.12788, -11.62845, -42.77829, -31.78709, -0.61493, -5.46732, 9.17835, -5.86130, 9.14817, -5.92584, -9.86393, -49.09785,
+-279.24234, 134.64542, -43.43766, -36.45545, -21.69882, -16.28008, -5.64642, 13.52591, -1.48913, 11.07259, -13.52461, -16.82686, -39.25970,
+-260.71298, 136.22865, -44.57975, -29.85570, -0.64486, -38.38213, -18.33903, 5.89145, -3.89952, 12.23704, -3.22323, -23.71099, -20.92175,
+-244.48389, 133.28445, -43.79402, -22.31293, 4.11721, -55.92643, -25.76093, 17.25046, -9.47253, 0.42447, -5.67624, -16.34599, -8.27315,
+-258.41626, 114.99637, -39.90332, 1.50976, 8.22684, -57.25970, -31.64858, 1.77440, -21.77207, -4.49708, -6.35045, -1.23350, -9.94049,
+-293.08508, 99.34319, -16.11116, 17.69371, 15.47070, -62.74282, -27.08352, 4.12698, -20.45372, -10.08534, -17.34487, -5.33286, -20.24701,
+-322.00287, 94.11205, -0.92652, 37.83418, 21.11624, -52.57660, -18.44728, 4.90179, -30.57641, -17.70811, -27.24849, -12.71308, -22.68225,
+-360.38376, 87.69393, 15.29972, 68.40858, 17.43580, -39.63292, -1.59294, 1.32824, -37.38486, -21.12629, -25.94076, -13.80269, -27.75978,
+-401.70505, 90.96419, 29.30173, 78.28263, 3.20327, -36.78372, 6.16998, -7.54714, -28.99337, -21.18590, -14.36380, 4.06708, -33.08428,
+-533.28723, 137.39876, 49.16436, 72.20885, 7.80102, -24.72589, -3.93477, -15.49783, -23.35331, -18.65767, -14.67795, -4.94262, -18.59274,
+-559.62939, 99.69369, 62.95110, 83.08356, 7.80114, 13.37880, -17.57888, -7.87949, -14.74117, -25.68275, -16.59367, -13.87330, -6.59394,
+-555.69965, 67.18806, 52.50816, 79.44274, 2.79971, 21.60576, -20.30817, -11.56905, -17.36839, -27.29060, -18.14963, -12.88813, -10.80527,
+-659.99139, 90.88692, 74.82683, 53.60613, 17.83161, 7.39822, -9.09811, -16.35573, -20.83104, -22.41822, -18.70988, -18.33362, -14.70294,
+-679.79871, 83.09547, 68.24111, 49.89501, 30.46873, 14.45928, 3.91992, -3.76449, -8.50756, -9.65265, -10.31525, -11.33202, -11.55049,
+-694.87091, 62.41616, 49.22509, 35.81430, 26.22110, 19.58934, 13.44967, 6.70528, -0.06228, -5.94130, -10.83276, -15.16693, -18.84751,
+-704.53339, 49.78053, 40.19272, 32.00471, 26.16905, 21.18073, 16.54406, 11.00089, 3.29591, -4.95220, -11.12703, -14.73515, -16.49860,
+-704.69830, 50.06087, 41.28493, 33.35400, 26.99703, 20.23875, 13.06462, 6.38402, -0.09129, -5.92407, -9.17170, -9.74002, -10.29155,
+-711.46802, 42.55208, 37.13642, 29.97435, 22.53142, 15.76887, 10.13004, 5.37198, 0.79322, -3.90029, -8.15694, -11.21932, -12.86519,
+-723.13409, 27.21255, 24.66596, 20.84755, 16.27658, 11.48368, 6.89734, 2.77970, -0.77472, -3.78793, -6.32338, -8.42078, -10.06509,
+-443.93698, -1.74865, -9.79181, 7.66294, -18.64954, -5.27232, 4.84549, -8.48673, -2.54492, 2.67439, -6.86648, 9.85871, -8.21330,
+-298.20532, -12.81320, 17.29125, 6.56532, -15.89673, -1.43100, 8.31953, -10.98549, 9.37294, 0.49440, -3.70998, 7.79895, -6.09313,
+-305.63287, -56.60079, 37.23157, 15.93787, -16.12873, 4.72155, 3.36984, -4.53316, 12.89923, -6.25745, -5.42213, 9.98214, -5.26571,
+-316.28519, -90.52562, 34.93086, 42.75752, 6.76751, 3.31615, -5.30959, 6.70043, 21.56020, -10.07466, -6.29718, 21.09662, 2.53661,
+-329.53720, -94.12029, 6.18531, 40.50994, 4.35451, -12.12563, -13.27101, 7.24133, 15.15652, -10.72804, -3.78922, 17.08343, 4.88286,
+-356.77383, -52.07880, -15.00291, 42.41784, -2.45872, -20.72002, -19.36626, 7.91365, 4.72626, -4.90424, 3.93229, 13.72323, 3.81743,
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+-424.59906, -86.83882, -22.08900, 53.29281, 19.05461, -7.95386, -2.32602, 19.13455, -19.69125, 8.10068, -6.92678, 10.93707, -16.15567,
+-428.36624, -67.50560, -24.48224, 50.47601, 18.74273, -20.39020, -20.49356, 16.66978, -11.89109, 1.08991, -8.05492, 5.10515, -8.56974,
+-443.08276, -8.88845, -10.48011, 66.38592, 49.91155, 0.86849, -0.34684, 22.84564, -2.74701, 0.58778, -17.34853, 5.22805, -11.46131,
+-435.82764, 95.80535, 13.62339, 80.46363, 55.52112, -7.25954, -1.67090, 10.80670, -10.50134, -8.81252, -25.66192, -3.25990, -20.18513,
+-381.94879, 131.20715, -16.48029, 87.01087, 53.16800, -45.39627, 11.92146, 9.28672, -14.34239, -15.28063, -32.94108, 3.39632, -20.16990,
+-374.69403, 118.91750, -17.20040, 82.15328, 56.67689, -41.36109, 23.95814, 13.94576, -15.61728, -15.42536, -38.30678, 13.34375, -29.81994,
+-369.38788, 124.81142, -24.51602, 89.74030, 48.55617, -41.11355, 18.53158, 8.42735, -15.37730, -14.26523, -28.02233, 9.68363, -36.25220,
+-386.45721, 118.97467, -22.82434, 96.50023, 47.94357, -37.79622, 16.12708, 1.16924, -14.44053, -24.05315, -24.62144, 17.51671, -29.46925,
+-421.42725, 115.36848, -14.01150, 98.95058, 45.11883, -34.03223, 18.23173, 2.81380, -6.00298, -30.70661, -15.66134, 8.52229, -39.76482,
+-468.87555, 111.35516, 16.96186, 108.35189, 44.64090, -28.17288, 8.54648, 1.14605, -1.83844, -36.53164, -6.91851, 17.54620, -42.04927,
+-544.56995, 101.10758, 43.59412, 97.50617, 41.32880, -20.49871, 6.59254, 11.98400, 13.62090, -35.46710, -5.78840, 22.58328, -32.60872,
+-616.66064, 102.26636, 52.12772, 74.47034, 45.83502, 0.88920, 13.82385, 27.56186, 4.32556, -31.13667, -0.50148, 8.55910, -24.87976,
+-655.08875, 92.81599, 66.07819, 64.82114, 50.34473, 17.12009, 7.09327, 7.61381, 1.25385, -12.30105, -2.86482, -1.24810, -11.74414,
+-667.78241, 79.23113, 64.03854, 57.02592, 57.56951, 27.23013, 9.59921, 5.18198, 7.68584, -4.19990, -8.00458, -7.87641, -6.57486,
+-642.40674, 94.75227, 25.83233, 5.45235, 27.99678, 28.74962, 15.73191, 4.30192, 4.12479, 2.92348, 2.88622, -2.28952, -9.06624,
+-451.78699, 99.16212, -27.62571, -31.75214, 31.80745, -16.08509, 11.18785, -14.27908, -21.10685, 7.97357, -0.75501, -2.21972, -6.87012,
+-401.80478, 109.05980, -40.16762, -28.47931, 26.69852, -14.71886, 13.88773, -17.41035, -25.91043, 4.41777, -1.47560, -4.54047, -9.88411,
+-368.46060, 117.97938, -37.87859, -40.05217, 16.11098, -17.78066, 33.12175, -9.39918, -22.65516, -2.05613, 5.48190, 3.70603, -14.99805
+};
+
+static const float golden_diff1_features[] = {
+-123.11830, 0.99917, 0.95805, 0.89408, 0.81248, 0.71794, 0.61364, 0.50104, 0.38071, 0.25359, 0.12199, -0.01007, -0.13747,
+-110.86054, 0.82501, 0.79184, 0.73540, 0.66041, 0.57449, 0.48119, 0.37892, 0.26721, 0.15073, 0.03548, -0.07627, -0.18402,
+ -86.10514, 0.80844, 0.77220, 0.70644, 0.61741, 0.51769, 0.41308, 0.30020, 0.17814, 0.05537, -0.05868, -0.16374, -0.26398,
+ -49.11975, 0.55242, 0.48541, 0.43367, 0.39057, 0.31347, 0.20146, 0.10639, 0.05811, 0.02169, -0.04557, -0.12705, -0.17475,
+ 0.19521, 0.21516, 0.12044, 0.11689, 0.17158, 0.15369, 0.05109, -0.00531, 0.05060, 0.11282, 0.06911, -0.02435, -0.03706,
+ -0.03262, -0.08807, -0.14386, -0.11539, -0.03314, -0.00671, -0.04884, -0.05501, 0.02827, 0.11541, 0.11466, 0.06971, 0.08476,
+ -0.22049, -0.33602, -0.36584, -0.34196, -0.28473, -0.26232, -0.28089, -0.27253, -0.20086, -0.11662, -0.07589, -0.05276, 0.01411,
+ -0.25332, -0.37332, -0.39287, -0.38077, -0.34722, -0.32975, -0.32956, -0.30655, -0.24162, -0.16621, -0.11195, -0.06195, 0.01795,
+ -0.10887, -0.15171, -0.14795, -0.14679, -0.14613, -0.13917, -0.12300, -0.10187, -0.08020, -0.05580, -0.02353, 0.01600, 0.05628,
+ 0.14574, 0.22539, 0.25125, 0.23819, 0.19844, 0.18125, 0.19373, 0.18966, 0.14405, 0.09475, 0.08440, 0.09461, 0.07662,
+ 0.15581, 0.25311, 0.29410, 0.25368, 0.16032, 0.10641, 0.10988, 0.08252, -0.01615, -0.11151, -0.11978, -0.07825, -0.07926,
+ 0.30504, 0.46966, 0.49986, 0.39949, 0.21782, 0.10238, 0.08256, 0.03093, -0.11686, -0.25540, -0.27020, -0.22181, -0.24756,
+ 0.69681, 0.83032, 0.56994, 0.48308, 0.48805, 0.30629, -0.04563, -0.26607, -0.23658, -0.18923, -0.31124, -0.45747, -0.41045,
+ 1.23411, 1.01172, -0.00456, 0.21409, 0.97355, 0.66618, -0.46384, -0.82240, -0.14151, 0.23893, -0.31966, -0.84641, -0.49297,
+ 1.76171, 0.80587, -1.22535, -0.45464, 1.02315, 0.71143, -0.59803, -1.19359, -0.41006, 0.70317, 0.35665, -0.79858, -0.53647,
+ 3.43839, 1.20394, -2.84728, -1.25620, 1.11030, 0.74963, -0.45219, -1.08916, -0.48705, 0.89677, 0.41597, -1.13295, -0.54123,
+ 6.29922, 1.56643, -4.70324, -1.21880, 1.29313, 0.77561, -0.27214, -1.02235, -0.60671, 0.62004, 0.43811, -0.68649, -0.38170,
+ 13.59902, 2.97291, -7.69089, -1.19724, 1.34852, 0.10822, -0.16015, -0.54947, -0.66831, 0.77170, 0.77724, 0.56974, -0.44725,
+ 25.95202, 3.48014, -9.57049, -1.29846, 1.17726, 0.15919, -0.36061, 0.04513, -1.06441, 1.13393, 1.13645, 1.74329, -0.98233,
+ 35.41563, 3.74347, -9.29239, -1.40323, 0.30726, 0.36464, -0.50191, 0.71997, -1.83411, 0.12763, 0.01438, 1.52732, -1.34014,
+ 40.30910, 3.88652, -8.24915, -0.51924, -0.68049, -0.03190, -1.15086, 0.78199, -1.46009, -0.44920, -0.90312, 0.88450, -1.12363,
+ 41.16010, 4.18969, -6.31749, 0.48709, -0.62803, -0.33113, -2.02391, 0.56536, -1.08399, -0.61680, -1.58262, -0.17104, -1.31953,
+ 36.85773, 4.19310, -4.33543, 0.52477, -0.77216, 0.08440, -2.05214, 0.95521, 0.29329, -0.04903, -2.08752, -0.69174, -0.55677,
+ 26.98730, 3.02555, -2.70108, 0.37827, -0.98518, 0.42249, -1.58129, 0.48110, 0.75456, 0.96493, -1.02983, -0.70425, -0.47341,
+ 14.50198, 3.08342, -1.43540, -0.41395, -0.26288, 1.25355, -0.47332, 0.79696, 1.54798, 1.79086, -1.01742, -1.27096, -0.19327,
+ -0.07425, 3.51203, 0.07904, -0.84623, 0.57152, 1.84925, 1.18436, 0.97503, 1.68712, 1.80404, -0.87783, -0.97168, 1.01794,
+ -10.13729, 6.59868, 0.20801, -2.22731, 0.70834, 0.99239, 2.04797, 1.25381, 2.11591, 1.73793, -0.78743, -0.58378, 1.70931,
+ -11.73542, 9.55152, 0.23723, -3.87789, 0.81732, 1.30697, 2.35846, 0.37123, 0.84172, 1.45737, 0.26195, 0.25325, 1.43181,
+ -12.08789, 10.97621, 0.84113, -5.59512, 0.54512, 1.70936, 2.80604, -0.04408, -1.23794, 0.64584, 0.67573, -0.32758, 1.31251,
+ -14.45271, 10.03827, 2.16457, -6.36324, -0.71855, 1.59761, 3.24396, -0.39643, -1.34466, -0.12180, 0.68246, -1.69113, 0.68083,
+ -18.53185, 6.60991, 5.65825, -4.11071, -0.05131, 2.15530, 3.25167, -0.76546, -1.56379, -1.75907, -0.10137, -2.19705, 1.11219,
+ -21.35056, 3.05293, 9.36903, -1.03400, 0.00783, 2.01184, 3.33418, 0.55118, 0.17739, -1.68767, 0.23982, -1.36500, 1.70118,
+ -18.56425, 2.78826, 11.28176, -0.03004, -1.78994, 0.82329, 2.50660, -0.06341, 0.09623, -1.57193, 1.14418, -1.09023, -0.12693,
+ -12.09316, 3.36681, 11.47227, 0.95308, -2.17463, 0.00065, 0.84474, -0.54763, -0.33692, -1.05079, 1.07330, -0.80153, -2.42432,
+ 1.92679, 5.35752, 9.80011, -0.02818, -2.80453, -0.67148, 0.68485, -0.32753, -1.23095, 0.20005, 0.88925, -0.09440, -3.41398,
+ 19.79073, 8.85031, 7.22205, -2.59490, -3.92287, -2.03960, -0.02755, 0.15578, -1.13285, 1.33972, 0.17429, 0.10092, -4.90758,
+ 35.92577, 11.48686, 5.10447, -3.74352, -4.61698, -2.36022, -1.00173, 0.19538, -1.15090, 1.75878, -0.54673, 0.65150, -6.24128,
+ 50.58400, 13.03088, 0.42639, -4.54247, -5.20881, -3.31127, -2.88928, 0.01554, -1.66646, 1.81067, -0.44956, 0.39215, -6.96486,
+ 57.90758, 10.98468, -5.91219, -5.56255, -5.41425, -4.90112, -3.53827, 0.57130, -0.89262, 1.92968, -0.92637, -0.95299, -7.09069,
+ 55.78551, 5.89209, -9.03530, -3.58417, -2.52814, -5.95845, -3.81914, 0.76729, -0.29327, 0.83804, -1.38007, -1.59041, -3.67697,
+ 46.80977, -0.83933, -9.70238, 0.72430, 0.84962, -7.95729, -4.29974, 2.43014, 1.13752, -0.20215, -1.03846, -0.79795, 0.57891,
+ 35.46388, -4.72663, -8.90094, 4.67138, 2.66211, -9.68076, -5.10884, 1.80854, 0.66877, -1.86039, -0.66617, 0.29346, 2.94240,
+ 19.55447, -8.28039, -5.55247, 9.20015, 4.92099, -10.90987, -6.07571, 0.76598, -0.32883, -3.58855, -1.15677, 0.78949, 3.67301,
+ 7.47528, -9.40369, -1.98193, 12.06493, 6.37570, -10.15639, -5.08030, -0.06683, -2.30887, -4.74815, -2.23084, 0.41731, 4.12727,
+ -2.35128, -8.86452, 2.02752, 14.25492, 6.66997, -7.73172, -2.34869, -1.13136, -4.27439, -5.14893, -2.52870, 0.22870, 3.19781,
+ -13.74784, -8.39473, 7.58204, 16.23704, 5.20402, -4.16565, 0.95284, -1.97663, -4.40917, -4.80555, -2.17866, 1.63009, 1.38432,
+ -28.90904, -3.94742, 12.48695, 16.28066, 2.81784, 0.13804, 2.36518, -3.08546, -3.78945, -4.59171, -1.65770, 2.07464, -0.09225,
+ -40.26587, -3.22518, 14.64699, 15.65972, 0.61256, 6.07845, 2.82745, -2.91284, -1.93971, -4.22240, -1.75182, 1.26154, -0.45747,
+ -45.14349, -3.95551, 14.24252, 13.35371, -0.66332, 10.23118, 2.24892, -3.26564, -0.24511, -3.25066, -1.04008, -0.10879, -0.11971,
+ -50.70501, -2.20058, 13.77331, 8.13219, -0.59765, 10.97492, 1.83205, -2.69995, 0.97870, -2.27968, -0.32133, -1.40878, 0.84365,
+ -51.82294, -1.78247, 11.21226, 3.38317, 0.42440, 11.02288, 1.51470, -2.02442, 2.18843, -0.48708, 1.11811, -0.94949, 1.98539,
+ -49.81170, -3.51574, 7.56374, -1.76232, 1.39623, 9.76060, 1.62028, -0.36254, 3.84997, 1.17318, 1.67293, -0.91917, 1.80862,
+ -44.15802, -5.91185, 3.48952, -5.78543, 2.65587, 8.07939, 1.97629, 1.60731, 4.55197, 2.19508, 1.27429, -1.31118, 1.56218,
+ -35.33823, -8.08526, 0.15498, -7.07355, 3.57980, 6.18474, 2.92167, 2.86992, 3.89624, 2.65474, 0.84629, -1.42729, 1.20335,
+ -24.67462, -9.85952, -2.72238, -7.17991, 2.86062, 3.23167, 4.07403, 3.24118, 3.37722, 2.99099, 1.17120, -0.22057, -0.06190,
+ -20.59121, -7.97999, -4.90647, -7.59573, 1.78547, 0.12186, 4.10282, 2.56175, 2.72723, 3.25732, 1.48873, 0.67668, -0.26983,
+ 3.07428, -9.33687, -7.83053, -7.12828, -1.75935, -1.53312, 2.67727, 1.46145, 2.30059, 3.12121, 1.47116, 2.10630, 0.50347,
+ 34.85448, -12.44948, -8.60693, -5.78039, -5.09658, -1.93558, 0.88214, -0.10276, 2.24627, 2.23317, 1.37225, 3.08518, 1.09415,
+ 53.15696, -15.17300, -5.60713, -4.74609, -6.88502, -2.72789, -0.78592, -1.64544, 1.69279, 0.83795, 0.87184, 3.41102, 1.33665,
+ 63.19269, -18.34933, -2.68293, -1.60527, -5.52794, -2.98085, -2.15557, -1.58699, 2.18150, -0.01729, 0.79118, 4.58937, 2.20473,
+ 65.03039, -20.59490, -2.70460, 0.33127, -4.29067, -3.65004, -3.10802, -0.79441, 2.44594, -0.59979, 0.76763, 4.64011, 2.38635,
+ 58.15821, -18.48174, -4.17419, 1.99928, -3.14752, -4.23100, -3.76360, 0.39203, 2.04124, -0.63182, 1.11693, 3.96532, 2.29718,
+ 43.36550, -12.39132, -5.47534, 3.43893, -0.83615, -3.45579, -4.07687, 1.14879, 1.74518, -0.71960, 1.67511, 3.23933, 2.07236,
+ 22.79780, -1.72378, -3.69967, 4.69732, 2.31691, -2.70338, -3.56008, 2.56122, 0.69024, -1.13102, 1.02780, 1.32513, 0.84953,
+ -2.38226, 11.01462, -1.65994, 4.38537, 5.09022, -2.44627, -3.58302, 2.97971, -0.93223, -1.13723, -0.36051, -1.66610, -0.48844,
+ -9.15842, 20.82118, -2.51988, 1.32690, 4.36041, -3.41942, -4.40026, 1.89496, -2.22513, -0.65096, -2.51034, -3.45496, -2.17831,
+ -4.90597, 28.78299, -1.34937, -2.74360, 3.06130, -3.39814, -4.09993, -0.45970, -2.64830, 0.34129, -2.67252, -4.07549, -3.01268,
+ 1.74398, 30.06878, -0.49164, -6.57672, 1.29566, -1.78235, -3.59079, -2.52400, -1.89671, 0.78753, -2.28603, -4.38701, -3.96275,
+ 7.34338, 24.49593, 1.15951, -8.19852, 0.27615, -0.33721, -3.73858, -3.92873, -0.98650, 0.85332, -2.07667, -3.93494, -3.94029,
+ 10.45519, 16.79375, 1.48509, -8.80962, -1.72076, 0.61703, -3.47419, -5.23513, -0.78920, 1.18348, -1.49720, -3.53585, -3.28705,
+ 11.18580, 10.93569, 0.14163, -8.22567, -3.87385, 0.79017, -2.48016, -6.75811, -1.56071, 1.77140, -0.15130, -2.39039, -2.57756,
+ 8.62314, 5.68633, -2.59710, -7.38330, -6.12817, 1.58600, -0.15663, -7.56769, -1.31918, 2.21425, 1.82699, -0.07501, -1.56627,
+ 4.85575, 3.24181, -2.64459, -5.65921, -7.05089, 2.54483, 2.62323, -6.91991, -2.33872, 2.04650, 2.49293, 1.78403, -1.23099,
+ 2.03701, 3.38577, -1.08578, -3.92688, -7.34940, 2.89644, 4.55796, -6.29122, -3.56426, 1.25358, 1.90528, 2.64444, -0.91498,
+ -0.80505, 3.42489, 1.32204, -2.31205, -7.14935, 2.82134, 5.29194, -5.34071, -4.25586, 0.13365, -0.09624, 2.46993, -1.29939,
+ -2.81361, 3.51945, 4.71937, -0.32877, -5.78644, 2.50150, 5.30680, -4.09004, -4.64764, 0.12808, -0.99124, 2.73573, -1.09987,
+ -2.27606, 2.49080, 4.82849, 0.98120, -3.68185, 2.29999, 4.26559, -2.39404, -4.11005, 0.06532, -1.48285, 2.32967, -1.51072,
+ -0.89890, -0.35663, 4.83242, 2.02812, -0.00512, 0.71252, 2.83080, -0.13655, -2.87700, -0.21353, -2.20828, 0.14064, -1.50410,
+ -1.32203, -3.28788, 4.86801, 3.59329, 3.33925, -0.65978, 1.17374, 2.83331, -1.87445, -0.51870, -2.48739, -2.75273, -0.93531,
+ -2.95602, -4.93940, 4.74206, 6.03304, 6.66710, -2.46849, -0.35298, 5.41546, -1.11451, -1.58884, -2.44900, -4.84549, -0.13159,
+ -5.67693, -6.20691, 4.26896, 8.38822, 8.77156, -4.73230, -0.31846, 7.51461, -0.41656, -2.93236, -1.65841, -5.44101, 0.14973,
+ -9.32123, -6.92015, 3.96077, 9.64051, 8.42496, -5.98046, 0.60400, 8.73328, -1.11180, -4.11314, -0.57883, -5.09402, 0.24460,
+ -14.18911, -7.83175, 4.75672, 10.62509, 7.19545, -5.97903, 1.25377, 8.04866, -1.43700, -5.43428, 0.82436, -4.04638, 0.94682,
+ -20.77600, -8.30645, 7.26155, 11.64701, 5.45212, -3.94525, 2.49760, 6.01494, -1.69385, -6.71214, 1.11581, -2.55983, 1.50917,
+ -25.60518, -8.60620, 10.57376, 11.97685, 3.51226, -0.93216, 2.64148, 3.62231, -1.49824, -6.03131, 1.73962, -0.48087, 1.12084,
+ -28.48710, -8.54384, 11.43639, 10.75773, 1.08724, 2.34973, 2.50412, 0.15479, -1.55349, -4.62047, 1.82277, 1.66091, 0.56405,
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+ 0.06926, 0.10713, 0.11903, 0.11316, 0.10068, 0.11070, 0.14570, 0.17547, 0.17976, 0.17390, 0.17916, 0.18638, 0.17058,
+ 0.26443, 0.37722, 0.38035, 0.37451, 0.36403, 0.36042, 0.36336, 0.35838, 0.33535, 0.29982, 0.26079, 0.21541, 0.15515,
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+ 10.74878, -3.11310, -5.34238, 2.26307, 3.04804, -1.68683, -1.57190, 2.02328, -0.35717, 0.00393, -0.15863, 1.01564, -1.07620,
+ 22.70843, -6.61746, -7.86647, 3.81820, 4.88015, -2.06069, -2.43454, 2.49714, -0.36634, 0.39582, -0.85246, 1.67405, -2.18834,
+ 32.18055, -10.68944, -8.76175, 5.36425, 5.02639, -2.41739, -2.50591, 2.78143, -0.67211, 0.73401, -1.31273, 2.36673, -2.74303,
+ 39.08526, -14.58456, -8.16102, 6.57589, 4.26688, -2.79942, -2.70583, 2.63534, -1.05410, 1.76937, -1.43361, 1.55572, -3.38997,
+ 42.88630, -17.70767, -7.25725, 6.54728, 2.44002, -3.06865, -3.13514, 1.98477, -1.18996, 2.21320, -1.35169, 1.13674, -2.86322,
+ 43.75336, -17.89537, -5.42091, 6.19822, 0.36815, -3.06211, -3.01817, 1.11116, -1.11147, 2.06109, -1.39334, 0.24111, -2.88191,
+ 39.96351, -15.94618, -2.38062, 5.83421, -1.14522, -1.73270, -1.48879, 0.83592, -1.51866, 1.71870, -1.36848, -0.22345, -2.14575,
+ 31.45315, -11.09490, 1.79407, 4.30672, -2.58627, -0.17169, 0.32247, -0.08480, -2.12540, 1.29164, -0.93414, -0.57769, -0.99019,
+ 18.59060, -3.90034, 4.51498, 2.55389, -3.25637, -0.47962, 0.40670, -0.29496, -1.78026, -0.62591, -0.17699, -0.85637, 0.57991,
+ 10.99932, 5.01000, 4.48573, 2.56734, -0.08985, 0.69420, 1.14445, 0.44501, -1.14982, -1.17057, -0.50301, -0.86144, 1.36458,
+ 7.27482, 18.54009, 5.61949, 3.31578, 3.53790, 1.19695, 1.36667, -0.11593, -0.76783, -2.51154, -1.72880, -1.06676, 0.78223,
+ 7.49068, 30.12584, 4.73965, 4.73910, 5.80762, -0.88405, 3.03583, -0.41851, -0.74616, -3.91174, -3.07679, -0.19967, 0.40673,
+ 7.94285, 35.63343, 4.15385, 5.54752, 7.28455, -2.47315, 4.79059, -0.36822, -0.76962, -3.83732, -4.03237, 0.22894, -0.91120,
+ 8.58590, 36.59988, 2.41544, 5.77743, 6.68436, -3.89020, 4.89490, -1.00768, -0.56777, -3.55960, -3.76792, 0.58118, -1.70878,
+ 8.57344, 34.03123, 0.61296, 5.92270, 5.05179, -5.00299, 4.20648, -2.23552, -0.11940, -3.99699, -3.23494, 0.89732, -2.60078,
+ 5.78229, 27.64637, -0.36020, 6.15170, 3.17174, -4.57662, 4.25798, -2.29137, 0.27880, -4.44962, -1.97717, 0.88484, -3.60586,
+ 0.23718, 18.80261, 1.23752, 6.06667, 1.15746, -3.21039, 3.56837, -2.37208, 0.35882, -4.56392, 0.27678, 1.79146, -4.22465,
+ -9.93021, 7.58356, 3.76043, 4.10620, -1.53005, -2.03193, 1.05332, -1.63585, 1.82193, -4.44761, 2.51193, 2.43774, -3.15035,
+ -24.19330, -1.48371, 6.88449, 1.15200, -1.69619, 2.34576, 0.24782, 0.73166, 3.00216, -3.47517, 4.28729, 1.86801, -1.40110,
+ -37.52070, -4.30909, 11.90375, -1.40707, -1.02627, 7.12782, -1.35290, 0.68745, 3.21353, -1.50163, 4.93153, -0.11838, 0.72051,
+ -43.55009, -5.04015, 13.40414, -3.67952, 0.01548, 8.99950, -1.79994, 0.40766, 3.33770, 0.53111, 4.24657, -2.02550, 3.04733,
+ -42.51932, -4.89435, 10.95545, -9.29525, -0.69523, 10.09831, -0.79636, 0.52587, 2.75109, 2.84201, 3.42491, -2.54333, 4.17730,
+ -23.87650, -3.56064, 3.61606, -15.48069, -1.35062, 7.06025, -0.41084, -0.89379, 0.17333, 5.28044, 2.53100, -3.10096, 4.57176,
+ -1.95067, -1.62599, -4.36667, -18.85973, -2.11852, 3.97257, 0.07670, -2.74860, -2.55112, 6.29552, 1.41799, -2.96217, 4.84084,
+ 19.53974, 0.76802, -11.17333, -20.72311, -3.47356, 0.60982, 2.05922, -3.62263, -4.16425, 5.85003, 1.12973, -2.65552, 3.58460,
+ 60.75739, -5.08121, -12.47585, -16.81619, -5.45903, -1.35013, 0.77835, -3.80548, -3.64245, 4.57869, 0.85220, -1.76367, 2.72508,
+ 87.85258, -9.92849, -11.27633, -12.00721, -6.97649, -3.14012, -0.52290, -3.06606, -1.86302, 2.78719, 0.55353, -0.15964, 1.95145,
+ 99.86404, -12.99408, -8.63910, -7.49278, -7.42962, -3.48943, -1.11168, -0.82875, -0.63118, 0.76545, 0.59896, 0.65211, 1.27843,
+ 98.39548, -15.14276, -3.97054, -2.54129, -6.74303, -2.47134, -2.03093, 0.20558, 0.41677, -0.20560, 0.43909, 0.78924, 1.28537
+};
+
+static const float golden_diff2_features[] = {
+ 16.21731, 0.19516, 0.20180, 0.20088, 0.19413, 0.19077, 0.19143, 0.18572, 0.16733, 0.14279, 0.12012, 0.09567, 0.06024,
+ 43.27348, -0.20258, -0.18401, -0.16553, -0.14803, -0.12548, -0.09792, -0.07352, -0.05640, -0.03998, -0.01733, 0.00732, 0.02418,
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+ -1.28988, 9.33262, -4.66195, -2.01650, 1.35927, -1.85700, -1.28144, -1.31423, -2.01477, -0.89281, -0.53515, 0.94998, -1.38835,
+ -1.61862, 12.59195, -5.25156, -1.35804, 0.88209, -1.47722, -2.90052, -1.59517, -2.67036, -1.73913, -1.15066, -0.53627, -0.70888,
+ -2.16144, 13.02065, -4.71302, -0.60855, -0.72887, -2.12651, -3.29260, -1.59289, -2.94301, -1.37787, -1.51249, -1.28468, -0.93711,
+ -2.48996, 10.08527, -3.78712, 0.59486, -0.44427, -1.56782, -1.47537, -0.50152, -1.54615, -2.45176, -0.88758, -0.79308, -1.51723,
+ -3.37114, 5.22081, -2.15569, -0.03493, 0.84560, -2.38960, 0.53854, 0.20923, 0.41152, -3.03330, 0.90126, 0.83144, -0.27947,
+ -3.66135, 1.14919, -1.63629, 0.48386, 0.79058, -1.71151, 1.97203, 0.70343, 1.67358, -1.25116, 1.09744, 0.91605, -0.61355,
+ -5.64232, -1.37539, 0.53593, 0.65117, 1.02433, -0.42820, 2.06895, 1.76367, 0.83862, 0.82207, 1.50662, 0.67475, -0.27118,
+ -8.30937, -3.99281, 4.73570, 1.26622, 2.33311, 0.37241, 1.69835, 2.00754, -1.43329, 1.18721, 0.58491, 0.79643, 1.20485,
+ -6.45230, -5.18484, 6.87114, 1.22436, 2.44002, 1.83408, 1.04069, 1.26849, -1.87028, 2.25718, -0.53987, -0.57861, 2.23996,
+ -2.87819, -5.12779, 6.66136, 1.42515, 1.59922, 2.15331, 0.51503, 1.04683, -2.14922, 2.96057, -0.44765, -1.20753, 2.45751,
+ 2.55963, -4.19373, 3.12443, 0.91964, 0.52124, 1.39843, -0.03413, 0.92559, -0.64958, 2.35276, -0.75760, -0.70371, 1.40571,
+ 7.60430, -3.98521, -1.01852, -0.25229, 0.11536, 0.85281, -0.07025, 0.61516, 1.19230, 0.59239, -0.08972, 0.04696, 0.24487,
+ 10.16228, -4.02588, -2.57450, -0.84913, -1.32936, -0.70299, -0.18757, 0.13752, 2.50470, -0.35897, 0.59181, 1.03806, -0.46586,
+ 9.22936, -2.40744, -4.14243, 0.19192, -2.82431, -1.14219, -0.35091, -0.02258, 2.76954, -0.70597, 1.19266, 0.96075, -1.51163,
+ 4.69089, -1.23410, -3.08633, 0.74810, -1.74740, -1.17424, -0.94292, 0.43392, 1.91493, -1.01433, 1.01194, 0.40200, -1.16780,
+ -0.40179, -1.07478, -0.30931, 0.43293, -0.26438, -0.77071, -0.91637, -0.11969, 0.27763, -0.48280, -0.05405, 0.49262, 0.44182,
+ -1.30888, -0.39406, 0.54836, -0.45560, -0.50473, 0.52426, -0.20709, -0.85935, 0.01156, 0.10719, -0.85375, -0.44064, 0.40290,
+ -2.51316, -0.30038, 2.24405, 0.04567, -1.06727, 0.87352, 0.45662, -0.89379, -0.20271, 0.05209, -1.62835, -1.47750, -0.11997,
+ -3.21890, -0.63541, 2.74252, 0.08231, -1.48443, 0.81144, 1.01067, -0.51558, -0.33487, -0.18637, -1.36021, -1.25547, -0.81002,
+ -3.33979, -1.25056, 2.29572, 0.46226, -1.03928, 0.60282, 1.02832, -0.26747, -0.32177, -0.29693, -1.01177, -0.69273, -0.40967,
+ 3.83003, -0.05123, -2.80682, -0.09836, -2.32190, -2.24635, 0.68250, 0.84364, 0.16497, -0.45109, -0.16244, 0.38569, 0.48638,
+ 7.31336, 0.54444, -5.62951, -0.63746, -1.75873, -3.84618, -0.14022, 1.48527, 0.40388, -0.55469, 0.84476, 1.14843, 0.98476,
+ 4.41448, 0.17238, -4.92365, -1.43925, 0.26561, -2.63845, -1.26464, 1.46021, 1.35545, 0.86784, 1.07002, 0.40436, 0.32996,
+ -0.36896, -0.82490, -2.96900, -2.93555, 0.88918, -0.55652, -1.99362, 0.58595, 1.62409, 1.75007, 0.80250, -0.38241, -0.81236,
+ -5.98791, -2.45780, -0.14485, -2.59323, 1.54421, 1.62512, -2.02780, -0.97582, 0.64449, 0.93279, 0.13137, -0.73216, -1.27276,
+ -10.65201, -3.67712, 4.00352, -0.89261, 1.51217, 3.81264, -0.42121, -1.77168, -0.46698, 0.01170, -0.70166, -0.99424, -1.27991,
+ -11.50435, -4.47949, 5.00780, -0.00562, 0.40033, 3.46732, 0.00612, -2.73054, -2.14512, -1.20490, -0.54356, 0.31733, -0.26649,
+ -6.66438, -2.96093, 3.70358, 1.25327, -0.10438, 2.13594, 0.59832, -2.27570, -2.58900, -1.88680, -0.33843, 1.45507, 1.25116,
+ 3.46550, 0.51885, -0.84675, 0.86400, -1.94527, -0.89987, 1.09293, -0.71812, -2.02673, -1.76489, 0.42939, 2.23159, 1.83621,
+ 5.75795, 2.37091, -1.18967, 0.53958, -1.52071, -1.74541, 0.81437, 0.14279, -1.20862, -0.84202, 0.89451, 1.63559, 1.28508,
+ 5.89360, 3.85243, -0.66250, 0.40889, 0.37277, -0.73996, 0.74387, 1.29072, 0.38874, 0.70585, 0.82826, 0.10710, 0.19355,
+ 5.84407, 3.89011, -1.06566, -0.28079, 0.54319, -0.79726, -0.10010, 1.10425, 0.99781, 0.80465, 0.30735, -0.84430, -0.65162,
+ 4.15440, 2.84123, -0.60409, 0.25845, 0.92166, -0.71915, -0.95923, 0.35210, 0.91047, 0.49826, -0.35318, -0.94804, -0.42840,
+ 2.92589, 2.50807, 0.45630, 0.74996, 1.16122, 0.25525, -0.30100, 0.21691, 0.62228, 0.34482, -0.39568, -0.85899, -0.66905,
+ 1.59452, 1.46675, 0.42945, 0.58506, 0.71894, 0.06417, -0.42137, -0.13321, 0.04791, -0.18779, -0.51909, -0.55866, -0.39290,
+ 0.65455, 0.85218, 0.66460, 0.61843, 0.56772, 0.43565, 0.20614, 0.15363, 0.13117, 0.04038, -0.14326, -0.17633, -0.17159,
+ 0.10242, 0.15728, 0.12141, 0.10756, 0.07157, 0.07602, 0.04603, 0.04986, 0.01415, -0.01059, -0.07097, -0.09258, -0.13962,
+ -0.10807, -0.14815, -0.14954, -0.14938, -0.17144, -0.17927, -0.17881, -0.17386, -0.18305, -0.16965, -0.14692, -0.10745, -0.07029,
+ 0.10584, 0.12991, 0.14904, 0.13138, 0.10066, 0.05203, 0.07636, 0.04703, 0.01529, -0.01553, 0.00099, -0.01276, 0.01326,
+ 0.08425, 0.10493, 0.13542, 0.09583, 0.08445, 0.04019, 0.05727, 0.02121, 0.00529, -0.05714, -0.05560, -0.08407, -0.08461,
+ 0.38736, 0.54152, 0.51499, 0.46106, 0.39383, 0.33696, 0.29355, 0.24304, 0.17114, 0.08912, 0.01619, -0.04488, -0.10124,
+ 0.57681, 0.80494, 0.77494, 0.73010, 0.67231, 0.60115, 0.51754, 0.42478, 0.32564, 0.22085, 0.11215, 0.00524, -0.09257,
+ 0.26486, 0.36144, 0.34555, 0.35903, 0.38883, 0.39362, 0.36565, 0.33999, 0.33649, 0.32611, 0.27476, 0.19535, 0.12650,
+ -0.21093, -0.29556, -0.27549, -0.22377, -0.15293, -0.09083, -0.04424, 0.00619, 0.07127, 0.13267, 0.16759, 0.17926, 0.18613,
+ -0.24814, -0.35065, -0.33638, -0.33100, -0.31921, -0.31383, -0.29480, -0.27651, -0.24126, -0.20092, -0.14114, -0.08350, -0.02431,
+ -0.28843, -0.40336, -0.39127, -0.38497, -0.38041, -0.37398, -0.35692, -0.33460, -0.30211, -0.25593, -0.18824, -0.11065, -0.03383,
+ -0.40388, -0.55839, -0.53149, -0.49648, -0.45975, -0.41103, -0.35497, -0.29469, -0.23840, -0.17541, -0.10385, -0.02526, 0.04476,
+ -0.14369, -0.19512, -0.18577, -0.17187, -0.16303, -0.14426, -0.12706, -0.11088, -0.11023, -0.11001, -0.11046, -0.10197, -0.09659,
+ 0.04986, 0.07119, 0.06103, 0.05379, 0.04249, 0.04304, 0.04101, 0.03907, 0.01958, -0.00486, -0.03727, -0.06044, -0.07913,
+ 0.11266, 0.15889, 0.14937, 0.14394, 0.13163, 0.11935, 0.09718, 0.07876, 0.05759, 0.04176, 0.02059, 0.00451, -0.01118,
+ 0.24149, 0.33048, 0.30735, 0.29830, 0.29356, 0.27574, 0.23733, 0.20474, 0.18577, 0.16789, 0.12721, 0.07614, 0.03404,
+ 0.30163, 0.39157, 0.35508, 0.31405, 0.30194, 0.24286, 0.17205, 0.09610, 0.07223, 0.04378, 0.00352, -0.05629, -0.07777,
+ 1.16603, 0.08366, -0.87697, 0.89533, 1.06093, -0.67183, -0.29497, 0.89540, 0.08121, -0.66815, 0.15620, 0.37290, -0.36530,
+ 9.21120, -2.82343, -4.35932, 1.65763, 2.25143, -1.19674, -1.27081, 1.41156, -0.36733, 0.31764, -0.23390, 0.75131, -0.77766,
+ 15.01506, -4.99195, -4.69809, 1.75278, 2.29372, -1.12755, -1.63234, 0.76995, -0.39868, 0.45715, -0.90487, 0.81855, -1.40586,
+ 14.57721, -5.55807, -2.11822, 2.03013, 0.87119, -0.47299, -0.55130, 0.30038, -0.43459, 0.55848, -0.93575, 0.75292, -1.14337,
+ 9.43524, -4.92830, 1.26108, 1.52253, -1.06139, 0.05145, 0.22248, -0.33880, -0.28392, 1.37014, -0.24485, -0.51274, -0.57657,
+ 1.76494, -2.84747, 3.64396, -0.05073, -3.01963, 0.48404, 0.46461, -1.16985, -0.00458, 0.98046, 0.29409, -1.08060, 0.74265,
+ -5.80262, 1.24152, 4.80939, -1.44025, -4.01440, 0.55141, 0.71258, -1.72037, 0.21627, -0.15831, 0.42853, -1.66622, 0.90462,
+ -11.92034, 4.72914, 4.48976, -1.85948, -3.03117, 1.10386, 1.54666, -0.90115, -0.23760, -1.21684, 0.45243, -1.10811, 1.32431,
+ -12.56092, 7.24714, 2.34986, -1.60707, -0.33190, 0.82056, 1.54856, 0.30501, -0.65289, -1.78371, 0.70834, 0.18954, 1.21825,
+ -6.37655, 7.25386, -0.86549, -1.12217, 2.09120, 0.25773, -0.13453, 0.52964, -0.37262, -1.10231, 0.11707, 0.54931, 1.06735,
+ -5.12965, 9.50558, 0.06137, 0.05321, 4.38371, 1.29442, 0.60271, 0.50784, 0.90449, -1.15440, -0.76032, 0.79430, 0.42655,
+ -4.91588, 13.99363, 2.21924, 1.72793, 4.22636, 0.88434, 1.02688, -0.11563, 0.80970, -0.95908, -1.16542, 0.09138, -0.25571,
+ -0.49899, 13.50086, 0.45976, 2.08231, 2.57830, -2.23514, 1.04862, -0.80894, 0.50177, -0.39439, -1.32026, -0.65541, -0.80816,
+ 2.50879, 7.05446, -1.60173, 0.75048, 0.44241, -3.20741, 1.17587, -0.86417, 0.22232, -0.48021, -1.41610, 0.34684, -1.20772,
+ 3.91430, -0.11253, -2.98095, 0.26236, -1.73557, -2.69258, 0.81257, -0.76090, -0.14933, -0.11267, -0.33433, 0.35107, -2.20689,
+ 1.52597, -8.08723, -2.88646, -0.01534, -2.71940, -0.59833, 0.44367, -0.36338, -0.70591, 0.03754, 1.07923, 1.28916, -0.98862,
+ -3.19241, -13.07944, -1.45363, -1.00014, -3.23551, 1.02494, -0.75324, -0.25386, -0.06039, 0.07222, 2.70142, 0.74582, -0.42609,
+ -9.37112, -14.01679, 1.58559, -0.99353, -2.70695, 2.30827, -2.86112, 0.00562, 1.23688, -0.28028, 3.36462, 0.27533, 0.38289,
+ -15.65554, -9.69857, 5.53239, -0.88511, -0.60628, 4.34134, -2.31666, 1.16146, 2.59606, 0.06560, 2.47435, 0.14085, 1.17497,
+ -17.38906, -2.45135, 6.80561, -2.23381, 0.29775, 4.22087, -1.59670, 1.92207, 1.32889, 0.40569, 1.28392, -1.24831, 1.78650,
+ -12.32829, -0.45323, 4.02706, -3.48876, 0.91028, 2.64065, -0.40734, 1.09273, -0.07504, 2.04266, -0.33405, -1.75580, 2.78248,
+ -5.48976, -1.31076, 1.13817, -4.10307, 1.68517, 2.64528, 0.61998, 0.31068, -0.72026, 3.38016, -1.75093, -1.89652, 2.49156,
+ 4.86518, 0.46760, -4.62680, -5.68874, -0.53312, 1.27476, 0.91930, -0.88800, -1.38324, 3.65460, -1.17333, -1.46998, 1.47362,
+ 23.59956, 1.54103, -10.57325, -6.55460, -1.18614, -3.24342, 0.75381, -2.71058, -3.01869, 2.41544, -1.13300, -0.30150, 0.60880,
+ 32.33330, 2.70337, -11.78239, -3.99596, -1.67392, -5.54388, 0.69011, -2.90009, -3.08534, 0.37034, -0.66760, 0.15104, -1.36276,
+ 30.06627, 3.26370, -7.79426, -0.60895, -2.00669, -5.92217, 1.14711, -1.47520, -1.91072, -1.88113, 0.17036, 1.92276, -2.50109,
+ 39.37696, -4.69698, -0.04885, 4.63564, -2.39147, -3.19453, -0.69839, 1.31964, 1.29003, -2.78135, -0.00281, 2.12537, -1.31877,
+ 28.62589, -7.60295, 5.43086, 7.42344, -1.12472, 0.32970, -1.36870, 2.95929, 2.25571, -2.58043, -0.04934, 0.91945, -0.31753,
+ 8.88008, -7.52631, 8.67690, 8.57319, 0.51966, 2.83565, -1.92872, 2.09044, 2.85297, -1.26876, -0.45494, -0.01347, 0.57816,
+ -11.64625, -4.59992, 7.86869, 6.87035, 1.68262, 3.67577, -1.31846, 1.67403, 2.82795, -0.42186, -0.61134, -0.46697, 0.59609
+};
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // ASR_F_GOLDEN_HPP
\ No newline at end of file
diff --git a/tests/use_case/ad/AdTests.cc b/tests/use_case/ad/AdTests.cc
new file mode 100644
index 0000000..09f82da
--- /dev/null
+++ b/tests/use_case/ad/AdTests.cc
@@ -0,0 +1,18 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#define CATCH_CONFIG_MAIN
+#include <catch.hpp>
diff --git a/tests/use_case/ad/InferenceTestAD.cc b/tests/use_case/ad/InferenceTestAD.cc
new file mode 100644
index 0000000..b87699d
--- /dev/null
+++ b/tests/use_case/ad/InferenceTestAD.cc
@@ -0,0 +1,100 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <catch.hpp>
+#include <random>
+
+#include "AdModel.hpp"
+#include "AdGoldenInput.hpp"
+#include "hal.h"
+#include "TensorFlowLiteMicro.hpp"
+
+#ifndef AD_FEATURE_VEC_DATA_SIZE
+#define AD_IN_FEATURE_VEC_DATA_SIZE (1024)
+#endif /* AD_FEATURE_VEC_DATA_SIZE */
+
+bool RunInference(arm::app::Model& model, const int8_t vec[])
+{
+ TfLiteTensor *inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ const size_t copySz = inputTensor->bytes < AD_IN_FEATURE_VEC_DATA_SIZE ? inputTensor->bytes : AD_IN_FEATURE_VEC_DATA_SIZE;
+
+ memcpy(inputTensor->data.data, vec, copySz);
+
+ return model.RunInference();
+}
+
+bool RunInferenceRandom(arm::app::Model& model)
+{
+ TfLiteTensor *inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ std::random_device rndDevice;
+ std::mt19937 mersenneGen{rndDevice()};
+ std::uniform_int_distribution<short> dist{-128, 127};
+
+ auto gen = [&dist, &mersenneGen]() {
+ return dist(mersenneGen);
+ };
+
+ std::vector<int8_t> randomInput(inputTensor->bytes);
+ std::generate(std::begin(randomInput), std::end(randomInput), gen);
+
+ REQUIRE(RunInference(model, randomInput.data()));
+ return true;
+}
+
+template <typename T>
+void TestInference(const T *input_goldenFV, const T *output_goldenFV, arm::app::Model& model)
+{
+ REQUIRE(RunInference(model, (int8_t*)input_goldenFV));
+
+ TfLiteTensor *outputTensor = model.GetOutputTensor(0);
+
+ REQUIRE(outputTensor);
+ REQUIRE(outputTensor->bytes == AD_OUT_FEATURE_VEC_DATA_SIZE);
+ auto tensorData = tflite::GetTensorData<T>(outputTensor);
+ REQUIRE(tensorData);
+
+ for (size_t i = 0; i < outputTensor->bytes; i++)
+ {
+ REQUIRE((int)tensorData[i] == (int)((T)output_goldenFV[i]));
+ }
+}
+
+TEST_CASE("Running random inference with TensorFlow Lite Micro and AdModel Int8", "[AD][.]")
+{
+ arm::app::AdModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ REQUIRE(RunInferenceRandom(model));
+}
+
+TEST_CASE("Running golden vector inference with TensorFlow Lite Micro and AdModel Int8", "[AD][.]")
+{
+ arm::app::AdModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ TestInference(ad_golden_input, ad_golden_out, model);
+}
\ No newline at end of file
diff --git a/tests/use_case/ad/MelSpecTests.cc b/tests/use_case/ad/MelSpecTests.cc
new file mode 100644
index 0000000..affc67a
--- /dev/null
+++ b/tests/use_case/ad/MelSpecTests.cc
@@ -0,0 +1,226 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "AdMelSpectrogram.hpp"
+#include <limits>
+#include <algorithm>
+#include <catch.hpp>
+
+/* First 1024 samples from test wav. */
+const std::vector<int16_t> testWav1 = std::vector<int16_t>{
+ 490,495,445,403,390,259,126,146,
+ 175,134,232,243,166,145,123,33,
+ -61,-4,8,-115,-281,-292,-210,-133,
+ -98,-142,-229,-356,-415,-438,-443,-396,
+ -377,-297,-85,122,172,16,-197,-351,
+ -484,-408,-378,-405,-399,-335,-180,-141,
+ -124,-108,-46,37,141,234,264,218,
+ 147,164,132,111,125,73,2,36,
+ 107,113,93,6,-40,-153,-273,-282,
+ -291,-298,-389,-446,-394,-324,-333,-385,
+ -485,-548,-690,-718,-660,-704,-690,-601,
+ -549,-641,-637,-513,-469,-366,-227,-269,
+ -348,-408,-486,-570,-638,-666,-730,-746,
+ -710,-634,-543,-461,-281,-156,-130,-126,
+ -144,-118,-23,103,132,37,-69,-86,
+ -234,-360,-366,-330,-248,-268,-282,-169,
+ -190,-152,-151,-145,-133,-205,-263,-397,
+ -558,-656,-668,-718,-779,-828,-856,-817,
+ -761,-759,-722,-772,-873,-983,-962,-897,
+ -843,-788,-750,-677,-555,-447,-373,-218,
+ -182,-230,-204,-174,-144,-127,-231,-199,
+ -127,-194,-250,-183,-189,-254,-249,-337,
+ -417,-459,-513,-505,-481,-402,-344,-284,
+ -281,-441,-450,-423,-327,-119,102,197,
+ 208,173,102,103,165,131,15,75,
+ 283,365,322,391,303,287,372,406,
+ 493,577,640,681,577,498,524,511,
+ 476,425,380,315,337,339,408,603,
+ 749,745,672,654,588,520,523,544,
+ 557,632,636,565,491,413,368,252,
+ 136,33,1,-26,-152,-258,-98,18,
+ 1,-18,-99,-117,-109,-228,-295,-349,
+ -334,-337,-441,-373,-279,-202,-204,-219,
+ -119,149,410,489,564,623,683,642,
+ 707,872,932,862,833,862,894,784,
+ 637,559,507,394,306,420,510,484,
+ 519,526,599,789,959,1052,1063,1030,
+ 860,697,603,530,475,463,468,461,
+ 609,641,534,482,435,329,239,216,
+ 185,82,88,106,60,26,-43,-127,
+ -220,-262,-317,-259,-172,-175,-271,-217,
+ -196,-164,8,144,150,134,60,13,
+ 57,-58,-115,-171,-282,-310,-298,-106,
+ 42,-101,-172,-181,-249,-326,-262,-132,
+ -56,-82,-71,-88,-196,-325,-426,-413,
+ -411,-317,-191,-172,-195,-292,-328,-191,
+ -88,-60,21,-63,-175,-135,-64,-83,
+ -163,-279,-440,-536,-403,-308,-236,-132,
+ -95,-69,-73,-21,13,133,185,251,
+ 238,88,-66,-134,-175,-231,-219,-151,
+ -213,-328,-340,-374,-459,-601,-556,-395,
+ -248,-205,-174,-227,-402,-493,-464,-483,
+ -588,-564,-463,-493,-505,-416,-378,-313,
+ -215,-192,-192,-59,18,-40,-66,-60,
+ -143,-263,-213,-224,-265,-249,-237,-227,
+ -418,-504,-573,-699,-679,-577,-500,-570,
+ -538,-416,-444,-415,-294,-300,-427,-423,
+ -299,-279,-279,-187,-137,-123,60,230,
+ 227,277,356,413,440,418,477,594,
+ 697,729,586,561,653,570,590,628,
+ 497,357,366,470,591,576,458,439,
+ 417,431,447,349,304,241,294,406,
+ 484,516,587,598,566,465,380,347,
+ 316,391,429,409,216,69,57,76,
+ 150,101,93,113,90,41,-28,-15,
+ -2,47,208,261,333,362,239,301,
+ 422,431,426,434,482,510,480,407,
+ 244,53,-108,-234,-275,-302,-304,-207,
+ -117,-181,-214,-248,-203,-52,5,-14,
+ 24,-9,-154,-186,-82,-23,-62,-165,
+ -174,-190,-368,-414,-316,-301,-180,41,
+ 116,214,319,408,416,157,-100,-40,
+ 118,248,310,301,302,387,458,414,
+ 301,261,233,111,33,39,65,56,
+ 9,-92,-87,-98,-172,-196,-186,-18,
+ -14,-57,-111,-178,-278,-304,-358,-359,
+ -362,-464,-528,-400,-355,-284,-189,-240,
+ -253,-216,-319,-490,-621,-684,-758,-860,
+ -883,-877,-847,-787,-766,-852,-727,-481,
+ -339,-282,-266,-405,-414,-286,-225,-204,
+ -330,-488,-412,-292,-254,-290,-372,-436,
+ -545,-564,-413,-360,-344,-389,-430,-340,
+ -248,-271,-343,-383,-414,-409,-272,-223,
+ -215,-123,-10,-4,-6,-27,-11,78,
+ 169,226,139,-19,16,100,54,-75,
+ -117,-103,-77,-277,-598,-644,-602,-509,
+ -396,-232,-227,-208,-153,-146,-205,-223,
+ -108,-55,-26,-8,-42,-178,-298,-320,
+ -254,-146,-135,-262,-370,-331,-337,-394,
+ -265,-53,136,309,354,312,345,303,
+ 275,338,287,269,346,329,319,327,
+ 199,118,251,296,243,111,90,150,
+ 104,163,274,278,242,135,93,138,
+ 5,-154,-206,-270,-334,-356,-251,-96,
+ -78,-123,-80,-93,-160,-217,-214,-154,
+ -42,128,228,243,307,465,492,425,
+ 381,382,425,530,518,484,560,654,
+ 659,663,723,717,672,652,542,507,
+ 471,468,579,573,459,313,262,310,
+ 284,235,331,361,275,207,104,35,
+ 35,89,136,192,218,161,89,64,
+ 116,175,159,95,96,242,350,248,
+ 170,64,-35,-136,-202,-271,-307,-290,
+ -257,-219,-206,-185,-216,-213,-184,-135,
+ -165,-141,-25,-31,-28,-98,-247,-162,
+ 10,35,-16,-113,-139,-127,-58,-100,
+ -166,-320,-406,-462,-604,-594,-650,-538,
+ -427,-365,-196,-117,-120,-102,-66,-122,
+ -211,-235,-202,-135,-40,-10,-38,-150,
+ -286,-223,-50,93,149,86,184,128,
+ 113,163,13,-53,-135,-100,-72,-75,
+ -73,-118,-150,-197,-224,-131,-59,-109,
+ -92,-129,-189,-220,-166,-173,-114,-8,
+ 26,-27,-38,50,109,143,161,209,
+ 266,289,384,397,312,203,5,-64,
+ -14,6,56,67,19,-43,-112,-46,
+ -74,-101,-83,-115,-142,-207,-274,-292,
+ -299,-236,-181,-188,-48,60,6,-76,
+ -8,115,188,260,236,143,44,-30,
+ -17,31,37,-16,-28,87,210,276,
+ 372,365,302,270,137,-8,-142,-246,
+ -279,-259,-203,-241,-278,-254,-245,-177,
+ -77,-8,-47,-159,-295,-412,-414,-414,
+ -566,-533,-255,-82,-10,222,358,336,
+ 355,360,303,237,267,224,244,434,
+ 422,372,404,464,559,538,446,294,
+ 217,60,-82,-150,-144,-162,-250,-263,
+ -222,-148,-81,-134,-134,-106,-27,-71,
+};
+
+/* Golden log mel spec output for test wav. */
+const std::vector<float> testWavMelSpec {
+ -8.601085, -10.563560, -13.791912, -12.356619, -16.892878,
+ -16.913876, -15.695299, -21.848980, -21.193371, -18.772688,
+ -21.795116, -20.008236, -22.413673, -25.162649, -24.091856,
+ -24.936411, -19.341146, -23.534576, -29.052885, -26.562546,
+ -25.046455, -29.586889, -30.115177, -32.281334, -29.806450,
+ -30.398304, -26.682615, -27.397421, -31.224312, -31.033779,
+ -36.314369, -29.530331, -28.428139, -30.097546, -34.101303,
+ -32.660480, -34.229076, -34.668293, -35.140759, -34.104649,
+ -34.141472, -36.514408, -37.655891, -33.590931, -40.532566,
+ -39.105091, -39.600319, -40.239834, -41.356224, -41.103714,
+ -39.861557, -41.827553, -41.275696, -42.203575, -42.689217,
+ -46.495552, -46.704731, -45.560322, -47.423828, -50.672031,
+ -51.387669, -53.410839, -54.899536, -55.807552,
+};
+
+
+arm::app::audio::AdMelSpectrogram GetMelSpecInstance() {
+ int frameLenSamples = 1024;
+ return arm::app::audio::AdMelSpectrogram(frameLenSamples);
+}
+
+template <class T>
+void TestQuntisedMelSpec() {
+ float quantScale = 0.1410219967365265;
+ int quantOffset = 11;
+ std::vector<T> melSpecOutput = GetMelSpecInstance().MelSpecComputeQuant<T>(testWav1, quantScale, quantOffset);
+
+ long min_val = std::numeric_limits<T>::min();
+ long max_val = std::numeric_limits<T>::max();
+
+ for (size_t i = 0; i < testWavMelSpec.size(); i++){
+ long TestWavMelSpec = (std::lround((testWavMelSpec[i] / quantScale) + quantOffset));
+ T quantizedTestWavMelSpec = static_cast<T>(std::max(min_val, std::min(TestWavMelSpec, max_val)));
+
+ REQUIRE(quantizedTestWavMelSpec == Approx(melSpecOutput[i]).margin(1));
+ }
+}
+
+template void TestQuntisedMelSpec<int8_t>();
+template void TestQuntisedMelSpec<uint8_t>();
+template void TestQuntisedMelSpec<int16_t>();
+
+TEST_CASE("Mel Spec calculation") {
+
+ hal_platform platform;
+ data_acq_module dataAcq;
+ data_psn_module dataPsn;
+ platform_timer timer;
+
+ /* Initialise the HAL and platform */
+ hal_init(&platform, &dataAcq, &dataPsn, &timer);
+ hal_platform_init(&platform);
+
+ SECTION("FP32") {
+ auto melSpecOutput = GetMelSpecInstance().ComputeMelSpec(testWav1);
+ REQUIRE_THAT( melSpecOutput, Catch::Approx( testWavMelSpec ).margin(0.1) );
+ }
+
+ SECTION("int8_t") {
+ TestQuntisedMelSpec<int8_t>();
+ }
+
+ SECTION("uint8_t") {
+ TestQuntisedMelSpec<uint8_t>();
+ }
+
+ SECTION("int16_t") {
+ TestQuntisedMelSpec<int16_t>();
+ }
+}
diff --git a/tests/use_case/ad/PostProcessTests.cc b/tests/use_case/ad/PostProcessTests.cc
new file mode 100644
index 0000000..62fa9e7
--- /dev/null
+++ b/tests/use_case/ad/PostProcessTests.cc
@@ -0,0 +1,53 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "AdPostProcessing.hpp"
+#include <catch.hpp>
+
+TEST_CASE("Softmax_vector") {
+
+ std::vector<float> testVec = {1, 2, 3, 4, 1, 2, 3};
+ arm::app::Softmax(testVec);
+ CHECK((testVec[0] - 0.024) == Approx(0.0).margin(0.001));
+ CHECK((testVec[1] - 0.064) == Approx(0.0).margin(0.001));
+ CHECK((testVec[2] - 0.175) == Approx(0.0).margin(0.001));
+ CHECK((testVec[3] - 0.475) == Approx(0.0).margin(0.001));
+ CHECK((testVec[4] - 0.024) == Approx(0.0).margin(0.001));
+ CHECK((testVec[5] - 0.064) == Approx(0.0).margin(0.001));
+ CHECK((testVec[6] - 0.175) == Approx(0.0).margin(0.001));
+}
+
+TEST_CASE("Output machine index") {
+
+ auto index = arm::app::OutputIndexFromFileName("test_id_00.wav");
+ CHECK(index == 0);
+
+ auto index1 = arm::app::OutputIndexFromFileName("test_id_02.wav");
+ CHECK(index1 == 1);
+
+ auto index2 = arm::app::OutputIndexFromFileName("test_id_4.wav");
+ CHECK(index2 == 2);
+
+ auto index3 = arm::app::OutputIndexFromFileName("test_id_6.wav");
+ CHECK(index3 == 3);
+
+ auto index4 = arm::app::OutputIndexFromFileName("test_id_id_00.wav");
+ CHECK(index4 == -1);
+
+ auto index5 = arm::app::OutputIndexFromFileName("test_id_7.wav");
+ CHECK(index5 == -1);
+}
\ No newline at end of file
diff --git a/tests/use_case/asr/AsrClassifierTests.cc b/tests/use_case/asr/AsrClassifierTests.cc
new file mode 100644
index 0000000..7c71912
--- /dev/null
+++ b/tests/use_case/asr/AsrClassifierTests.cc
@@ -0,0 +1,98 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "AsrClassifier.hpp"
+#include "Wav2LetterModel.hpp"
+
+#include <catch.hpp>
+
+TEST_CASE("Test invalid classifier")
+{
+ TfLiteTensor* outputTens = nullptr;
+ std::vector <arm::app::ClassificationResult> resultVec;
+ arm::app::AsrClassifier classifier;
+
+ REQUIRE(!classifier.GetClassificationResults(outputTens, resultVec, {}, 1));
+}
+
+
+TEST_CASE("Test valid classifier UINT8") {
+ const int dimArray[] = {4, 1, 1, 246, 29};
+ std::vector <std::string> labels(29);
+ std::vector <uint8_t> outputVec(7134);
+ TfLiteIntArray* dims= tflite::testing::IntArrayFromInts(dimArray);
+ TfLiteTensor tfTensor = tflite::testing::CreateQuantizedTensor(
+ outputVec.data(), dims, 1, 0, "test");
+ TfLiteTensor* outputTensor = &tfTensor;
+ std::vector <arm::app::ClassificationResult> resultVec;
+ arm::app::AsrClassifier classifier;
+
+ REQUIRE(classifier.GetClassificationResults(outputTensor, resultVec, labels, 1));
+ REQUIRE(246 == resultVec.size());
+}
+
+
+TEST_CASE("Get classification results") {
+ const int dimArray[] = {4, 1, 1, 10, 15};
+ std::vector <std::string> labels(15);
+ std::vector<uint8_t> outputVec(150, static_cast<uint8_t>(1));
+ TfLiteIntArray* dims= tflite::testing::IntArrayFromInts(dimArray);
+ TfLiteTensor tfTensor = tflite::testing::CreateQuantizedTensor(
+ outputVec.data(), dims, 1, 0, "test");
+ TfLiteTensor* outputTensor = &tfTensor;
+
+ std::vector <arm::app::ClassificationResult> resultVec(10);
+
+ /* set the top five results: */
+ std::vector<std::pair<uint32_t, std::pair<uint32_t, uint8_t>>> selectedResults {
+ {0, {3, 23}},
+ {0, {9, 15}},
+ {1, {5, 24}},
+ {1, {7, 4}},
+ {2, {9, 5}},
+ {3, {8, 6}},
+ {4, {13, 10}},
+ {4, {6, 18}},
+ {5, {3, 15}},
+ {5, {4, 115}},
+ {6, {6, 25}},
+ {7, {1, 7}},
+ {8, {11, 9}},
+ {9, {1, 10}}
+ };
+
+ const uint32_t nCols = outputTensor->dims->data[arm::app::Wav2LetterModel::ms_outputColsIdx];
+ for (size_t i = 0; i < selectedResults.size(); ++i) {
+ uint32_t rIndex = selectedResults[i].first;
+ uint32_t cIndex = selectedResults[i].second.first;
+ uint8_t value = selectedResults[i].second.second;
+ outputVec[rIndex * nCols + cIndex] = value;
+ }
+
+ arm::app::AsrClassifier classifier;
+
+ REQUIRE(classifier.GetClassificationResults(outputTensor, resultVec, labels, 1));
+ REQUIRE(resultVec[0].m_labelIdx == 3);
+ REQUIRE(resultVec[1].m_labelIdx == 5);
+ REQUIRE(resultVec[2].m_labelIdx == 9);
+ REQUIRE(resultVec[3].m_labelIdx == 8);
+ REQUIRE(resultVec[4].m_labelIdx == 6);
+ REQUIRE(resultVec[5].m_labelIdx == 4);
+ REQUIRE(resultVec[6].m_labelIdx == 6);
+ REQUIRE(resultVec[7].m_labelIdx == 1);
+ REQUIRE(resultVec[8].m_labelIdx == 11);
+ REQUIRE(resultVec[9].m_labelIdx == 1);
+}
diff --git a/tests/use_case/asr/AsrFeaturesTests.cc b/tests/use_case/asr/AsrFeaturesTests.cc
new file mode 100644
index 0000000..9401f40
--- /dev/null
+++ b/tests/use_case/asr/AsrFeaturesTests.cc
@@ -0,0 +1,188 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "DataStructures.hpp"
+#include "AsrGoldenFeatures.hpp"
+#include "hal.h"
+#include "TensorFlowLiteMicro.hpp"
+#include "Wav2LetterPreprocess.hpp"
+
+#include <catch.hpp>
+#include <random>
+
+class TestPreprocess : public arm::app::audio::asr::Preprocess {
+public:
+ TestPreprocess()
+ : arm::app::audio::asr::Preprocess(0,0,0,0)
+ {}
+
+ bool ComputeDeltas(arm::app::Array2d<float>& mfcc,
+ arm::app::Array2d<float>& delta1,
+ arm::app::Array2d<float>& delta2)
+ {
+ return this->_ComputeDeltas(mfcc, delta1, delta2);
+ }
+
+ float GetMean(arm::app::Array2d<float>& vec)
+ {
+ return this->_GetMean(vec);
+ }
+
+ float GetStdDev(arm::app::Array2d<float>& vec, const float mean)
+ {
+ return this->_GetStdDev(vec, mean);
+ }
+
+ void NormaliseVec(arm::app::Array2d<float>& vec)
+ {
+ return this->_NormaliseVec(vec);
+ }
+};
+
+template<class T>
+void CheckOutputs(const std::vector<T> goldenOutput, std::vector<T> output)
+{
+ const size_t goldenSize = goldenOutput.size();
+ const size_t realSize = output.size();
+
+ REQUIRE(realSize == goldenSize);
+ REQUIRE_THAT(output, Catch::Approx( goldenOutput ).margin(0.0001));
+}
+template void CheckOutputs<float>(const std::vector<float> goldenOutput, std::vector<float> output);
+
+void populateBuffer(const float* input, size_t size, size_t numMfccFeats, std::vector<std::vector<float>>& buf)
+{
+ size_t time = 0;
+ for (size_t i = 0; i < size; ++i) {
+ if (i > 0 && i % numMfccFeats == 0) {
+ ++time;
+ }
+ float featureValue = *(input + i);
+ buf[i % numMfccFeats][time] = featureValue;
+ }
+}
+
+void populateArray2dWithVectorOfVector(std::vector<std::vector<float>> vec, arm::app::Array2d<float>& buf)
+{
+ for (size_t i = 0; i < vec.size(); ++i) {
+ for (size_t j = 0; j < vec[i].size(); ++j) {
+ buf(i, j) = vec[i][j];
+ }
+ }
+}
+
+TEST_CASE("Floating point asr features calculation", "[ASR]")
+{
+ TestPreprocess tp;
+
+ SECTION("First and second diff")
+ {
+ constexpr uint32_t numMfccFeats = 13;
+ constexpr uint32_t numFeatVectors = 296;
+
+ arm::app::Array2d<float> mfccBuf(numMfccFeats, numFeatVectors);
+ arm::app::Array2d<float> delta1Buf(numMfccFeats, numFeatVectors);
+ arm::app::Array2d<float> delta2Buf(numMfccFeats, numFeatVectors);
+
+ std::vector<std::vector<float>> goldenMfccBuf(numMfccFeats, std::vector<float>(numFeatVectors));
+ std::vector<std::vector<float>> goldenDelta1Buf(numMfccFeats, std::vector<float>(numFeatVectors));
+ std::vector<std::vector<float>> goldenDelta2Buf(numMfccFeats, std::vector<float>(numFeatVectors));
+
+ populateBuffer(golden_asr_mfcc, golden_asr_mfcc_len, numMfccFeats, goldenMfccBuf);
+ populateBuffer(golden_diff1_features, golden_diff1_len, numMfccFeats, goldenDelta1Buf);
+ populateBuffer(golden_diff2_features, golden_diff2_len, numMfccFeats, goldenDelta2Buf);
+
+ populateArray2dWithVectorOfVector(goldenMfccBuf, mfccBuf);
+ std::fill(delta1Buf.begin(), delta1Buf.end(), 0.f);
+ std::fill(delta2Buf.begin(), delta2Buf.end(), 0.f);
+
+ tp.ComputeDeltas(mfccBuf, delta1Buf, delta2Buf);
+
+ /* First 4 and last 4 values are different because we pad AFTER diff calculated. */
+ for (size_t i = 0; i < numMfccFeats; ++i) {
+ const float* start_goldenDelta1Buf = goldenDelta1Buf[i].data() + 4;
+ const float* start_delta1 = delta1Buf.begin() + i * delta1Buf.size(1) + 4;
+ std::vector<float> goldenDataDelta1(start_goldenDelta1Buf, start_goldenDelta1Buf + numFeatVectors - 8);
+ std::vector<float> tensorDataDelta1(start_delta1, start_delta1 + numFeatVectors - 8);
+
+ CheckOutputs<float>(goldenDataDelta1,tensorDataDelta1);
+
+ const float* start_goldenDelta2Buf = goldenDelta2Buf[i].data() + 4;
+ const float* start_delta2 = delta2Buf.begin() + i * delta2Buf.size(1) + 4;
+ std::vector<float> goldenDataDelta2(start_goldenDelta2Buf, start_goldenDelta2Buf + numFeatVectors - 8);
+ std::vector<float> tensorDataDelta2(start_delta2, start_delta2 + numFeatVectors - 8);
+
+ CheckOutputs<float>(goldenDataDelta2,tensorDataDelta2);
+ }
+
+ }
+
+ SECTION("Mean")
+ {
+ std::vector<std::vector<float>> mean1vec{{1, 2},
+ {-1, -2}};
+ arm::app::Array2d<float> mean1(2,2); /* {{1, 2},{-1, -2}} */
+ populateArray2dWithVectorOfVector(mean1vec, mean1);
+ REQUIRE(0 == Approx(tp.GetMean(mean1)));
+
+ arm::app::Array2d<float> mean2(2, 2);
+ std::fill(mean2.begin(), mean2.end(), 0.f);
+ REQUIRE(0 == Approx(tp.GetMean(mean2)));
+
+ arm::app::Array2d<float> mean3(3,3);
+ std::fill(mean3.begin(), mean3.end(), 1.f);
+ REQUIRE(1 == Approx(tp.GetMean(mean3)));
+ }
+
+ SECTION("Std")
+ {
+ arm::app::Array2d<float> std1(2, 2);
+ std::fill(std1.begin(), std1.end(), 0.f); /* {{0, 0}, {0, 0}} */
+ REQUIRE(0 == Approx(tp.GetStdDev(std1, 0)));
+
+ std::vector<std::vector<float>> std2vec{{1, 2, 3, 4, 5}, {6, 7, 8, 9, 0}};
+ arm::app::Array2d<float> std2(2,5);
+ populateArray2dWithVectorOfVector(std2vec, std2);
+ const float mean = tp.GetMean(std2);
+ REQUIRE(2.872281323 == Approx(tp.GetStdDev(std2, mean)));
+
+ arm::app::Array2d<float> std3(2,2);
+ std::fill(std3.begin(), std3.end(), 1.f); /* std3{{1, 1}, {1, 1}}; */
+ REQUIRE(0 == Approx(tp.GetStdDev(std3, 1)));
+ }
+
+ SECTION("Norm") {
+ auto checker = [&](arm::app::Array2d<float>& d, std::vector<float>& g) {
+ tp.NormaliseVec(d);
+ std::vector<float> d_vec(d.begin(), d.end());
+ REQUIRE_THAT(g, Catch::Approx(d_vec));
+ };
+
+ std::vector<std::vector<float>> norm0vec{{1, 1}, {1, 1}};
+ std::vector<float> goldenNorm0 {0, 0, 0, 0};
+ arm::app::Array2d<float> norm0(2, 2);
+ populateArray2dWithVectorOfVector(norm0vec, norm0);
+ checker(norm0, goldenNorm0);
+
+ std::vector<std::vector<float>> norm1vec{{1, 2, 3, 4, 5}, {6, 7, 8, 9, 0}};
+ std::vector<float> goldenNorm1 {
+ -1.218543592, -0.87038828, -0.522232968, -0.174077656, 0.174077656,
+ 0.522232968, 0.87038828, 1.218543592, 1.566698904, -1.566698904};
+ arm::app::Array2d<float> norm1(2, 5);
+ populateArray2dWithVectorOfVector(norm1vec, norm1);
+ checker(norm1, goldenNorm1);
+ }
+}
diff --git a/tests/use_case/asr/AsrTests.cc b/tests/use_case/asr/AsrTests.cc
new file mode 100644
index 0000000..09f82da
--- /dev/null
+++ b/tests/use_case/asr/AsrTests.cc
@@ -0,0 +1,18 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#define CATCH_CONFIG_MAIN
+#include <catch.hpp>
diff --git a/tests/use_case/asr/InferenceTestWav2Letter.cc b/tests/use_case/asr/InferenceTestWav2Letter.cc
new file mode 100644
index 0000000..1fa4092
--- /dev/null
+++ b/tests/use_case/asr/InferenceTestWav2Letter.cc
@@ -0,0 +1,105 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "hal.h"
+#include "TensorFlowLiteMicro.hpp"
+#include "Wav2LetterModel.hpp"
+#include "TestData_asr.hpp"
+
+#include <catch.hpp>
+#include <random>
+
+bool RunInference(arm::app::Model& model, const int8_t vec[], const size_t copySz)
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ memcpy(inputTensor->data.data, vec, copySz);
+
+ return model.RunInference();
+}
+
+bool RunInferenceRandom(arm::app::Model& model)
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ std::random_device rndDevice;
+ std::mt19937 mersenneGen{rndDevice()};
+ std::uniform_int_distribution<short> dist {-128, 127};
+
+ auto gen = [&dist, &mersenneGen](){
+ return dist(mersenneGen);
+ };
+
+ std::vector<int8_t> randomAudio(inputTensor->bytes);
+ std::generate(std::begin(randomAudio), std::end(randomAudio), gen);
+
+ REQUIRE(RunInference(model, randomAudio.data(), inputTensor->bytes));
+ return true;
+}
+
+/* Skip this test, Wav2LetterModel if not Vela optimized but only from ML-zoo will fail. */
+TEST_CASE("Running random inference with TensorFlow Lite Micro and Wav2LetterModel Int8", "[Wav2Letter][.]")
+{
+ arm::app::Wav2LetterModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ REQUIRE(RunInferenceRandom(model));
+}
+
+template<typename T>
+void TestInference(const T* input_goldenFV, const T* output_goldenFV, arm::app::Model& model)
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ REQUIRE(RunInference(model, input_goldenFV, inputTensor->bytes));
+
+ TfLiteTensor* outputTensor = model.GetOutputTensor(0);
+
+ REQUIRE(outputTensor);
+ REQUIRE(outputTensor->bytes == OFM_DATA_SIZE);
+ auto tensorData = tflite::GetTensorData<T>(outputTensor);
+ REQUIRE(tensorData);
+
+ for (size_t i = 0; i < outputTensor->bytes; i++) {
+ REQUIRE((int)tensorData[i] == (int)((T)output_goldenFV[i]));
+ }
+}
+
+TEST_CASE("Running inference with Tflu and Wav2LetterModel Int8", "[Wav2Letter][.]")
+{
+ 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);
+
+ DYNAMIC_SECTION("Executing inference with re-init")
+ {
+ arm::app::Wav2LetterModel 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
diff --git a/tests/use_case/asr/MfccTests.cc b/tests/use_case/asr/MfccTests.cc
new file mode 100644
index 0000000..c70e53e
--- /dev/null
+++ b/tests/use_case/asr/MfccTests.cc
@@ -0,0 +1,170 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "Wav2LetterMfcc.hpp"
+
+#include <algorithm>
+#include <catch.hpp>
+#include <limits>
+
+/* First 512 samples from itellyou.wav. */
+const std::vector<int16_t> testWav1 = std::vector<int16_t> {
+ -3,0,1,-1,2,3,-2,2,
+ 1,-2,0,3,-1,8,3,2,
+ -1,-1,2,7,3,5,6,6,
+ 6,12,5,6,3,3,5,4,
+ 4,6,7,7,7,3,7,2,
+ 8,4,4,2,-4,-1,-1,-4,
+ 2,1,-1,-4,0,-7,-6,-2,
+ -5,1,-5,-1,-7,-3,-3,-7,
+ 0,-3,3,-5,0,1,-2,-2,
+ -3,-3,-7,-3,-2,-6,-5,-8,
+ -2,-8,4,-9,-4,-9,-5,-5,
+ -3,-9,-3,-9,-1,-7,-4,1,
+ -3,2,-8,-4,-4,-5,1,-3,
+ -1,0,-1,-2,-3,-2,-4,-1,
+ 1,-1,3,0,3,2,0,0,
+ 0,-3,1,1,0,8,3,4,
+ 1,5,6,4,7,3,3,0,
+ 3,6,7,6,4,5,9,9,
+ 5,5,8,1,6,9,6,6,
+ 7,1,8,1,5,0,5,5,
+ 0,3,2,7,2,-3,3,0,
+ 3,0,0,0,2,0,-1,-1,
+ -2,-3,-8,0,1,0,-3,-3,
+ -3,-2,-3,-3,-4,-6,-2,-8,
+ -9,-4,-1,-5,-3,-3,-4,-3,
+ -6,3,0,-1,-2,-9,-4,-2,
+ 2,-1,3,-5,-5,-2,0,-2,
+ 0,-1,-3,1,-2,9,4,5,
+ 2,2,1,0,-6,-2,0,0,
+ 0,-1,4,-4,3,-7,-1,5,
+ -6,-1,-5,4,3,9,-2,1,
+ 3,0,0,-2,1,2,1,1,
+ 0,3,2,-1,3,-3,7,0,
+ 0,3,2,2,-2,3,-2,2,
+ -3,4,-1,-1,-5,-1,-3,-2,
+ 1,-1,3,2,4,1,2,-2,
+ 0,2,7,0,8,-3,6,-3,
+ 6,1,2,-3,-1,-1,-1,1,
+ -2,2,1,2,0,-2,3,-2,
+ 3,-2,1,0,-3,-1,-2,-4,
+ -6,-5,-8,-1,-4,0,-3,-1,
+ -1,-1,0,-2,-3,-7,-1,0,
+ 1,5,0,5,1,1,-3,0,
+ -6,3,-8,4,-8,6,-6,1,
+ -6,-2,-5,-6,0,-5,4,-1,
+ 4,-2,1,2,1,0,-2,0,
+ 0,2,-2,2,-5,2,0,-2,
+ 1,-2,0,5,1,0,1,5,
+ 0,8,3,2,2,0,5,-2,
+ 3,1,0,1,0,-2,-1,-3,
+ 1,-1,3,0,3,0,-2,-1,
+ -4,-4,-4,-1,-4,-4,-3,-6,
+ -3,-7,-3,-1,-2,0,-5,-4,
+ -7,-3,-2,-2,1,2,2,8,
+ 5,4,2,4,3,5,0,3,
+ 3,6,4,2,2,-2,4,-2,
+ 3,3,2,1,1,4,-5,2,
+ -3,0,-1,1,-2,2,5,1,
+ 4,2,3,1,-1,1,0,6,
+ 0,-2,-1,1,-1,2,-5,-1,
+ -5,-1,-6,-3,-3,2,4,0,
+ -1,-5,3,-4,-1,-3,-4,1,
+ -4,1,-1,-1,0,-5,-4,-2,
+ -1,-1,-3,-7,-3,-3,4,4,
+};
+
+const std::vector<int16_t> testWav2 = std::vector<int16_t> (512, 0);
+
+/* Golden mfcc output for testwav1. */
+const std::vector<float> golden_mfcc_output_testWav1 {
+ -835.24603, 21.010452, 18.699404, 7.4338417, 19.028961, -5.401735, 6.4761047, -11.400679,
+ 8.392709, 12.202361, 8.403276, -13.508412, -18.307348
+};
+
+/* Golden mfcc output for the all zero wav. */
+const std::vector<float> golden_mfcc_output_testWav2 {
+ -1131.37085, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+};
+
+
+arm::app::audio::Wav2LetterMFCC GetMFCCInstance()
+{
+ const auto sampFreq = arm::app::audio::Wav2LetterMFCC::ms_defaultSamplingFreq;
+ const auto frameLenMs = 32;
+ const auto numMfccFeats = 13;
+ const auto frameLenSamples = sampFreq * frameLenMs * 0.001;
+ return arm::app::audio::Wav2LetterMFCC(numMfccFeats, frameLenSamples);
+}
+
+template <class T>
+void TestQuantisedMFCC()
+{
+ const auto quantScale = 0.1410219967365265;
+ const auto quantOffset = 11;
+ std::vector<T> mfccOutput = GetMFCCInstance().MfccComputeQuant<T>(testWav1, quantScale, quantOffset);
+
+ long min_val = std::numeric_limits<T>::min();
+ long max_val = std::numeric_limits<T>::max();
+
+ for (size_t i = 0; i < golden_mfcc_output_testWav1.size(); i++){
+ long TestWavMfcc = (std::lround((golden_mfcc_output_testWav1[i] / quantScale) + quantOffset));
+ T quantizedTestWavMfcc = static_cast<T>(std::max(min_val, std::min(TestWavMfcc, max_val)));
+
+ REQUIRE(quantizedTestWavMfcc == Approx(mfccOutput[i]).margin(2));
+ }
+}
+
+template void TestQuantisedMFCC<int8_t>();
+template void TestQuantisedMFCC<uint8_t>();
+template void TestQuantisedMFCC<int16_t>();
+
+TEST_CASE("MFCC calculation")
+{
+ hal_platform platform;
+ data_acq_module dataAcq;
+ data_psn_module dataPsn;
+ platform_timer timer;
+
+ /* Initialise the HAL and platform. */
+ hal_init(&platform, &dataAcq, &dataPsn, &timer);
+ hal_platform_init(&platform);
+
+ SECTION("FP32")
+ {
+ auto mfccOutput = GetMFCCInstance().MfccCompute(testWav1);
+ REQUIRE_THAT( mfccOutput, Catch::Approx( golden_mfcc_output_testWav1 ).margin(0.3) );
+
+ auto mfccOutput2 = GetMFCCInstance().MfccCompute(testWav2);
+ REQUIRE_THAT( mfccOutput2, Catch::Approx( golden_mfcc_output_testWav2 ).margin(0.001) );
+ }
+
+ SECTION("int8_t")
+ {
+ TestQuantisedMFCC<int8_t>();
+ }
+
+ SECTION("uint8_t")
+ {
+ TestQuantisedMFCC<uint8_t>();
+ }
+
+ SECTION("int16_t")
+ {
+ TestQuantisedMFCC<int16_t>();
+ }
+}
diff --git a/tests/use_case/asr/OutputDecodeTests.cc b/tests/use_case/asr/OutputDecodeTests.cc
new file mode 100644
index 0000000..22153f3
--- /dev/null
+++ b/tests/use_case/asr/OutputDecodeTests.cc
@@ -0,0 +1,67 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "OutputDecode.hpp"
+
+#include "catch.hpp"
+
+TEST_CASE("Running output decode on test vector") {
+
+ std::vector<arm::app::ClassificationResult> vecResult(20);
+ /* Number of test inputs. */
+ const size_t numStrings = 8;
+
+ /* The test inputs. */
+ std::string testText[numStrings][20]
+ {
+ {"a", "b", "c", "d", "e", "f", "g", "g", "g", " ", "h", "h", "i", " ", " ", "j", "k", "\'", "\'", "l"}, /* initial */
+ {" ", "b", "c", "d", "e", "f", "g", "g", "g", " ", "h", "h", "i", " ", " ", "j", "k", "\'", "\'", " "}, /* space start and end */
+ {"\'", "b", "c", "d", "e", "f", "g", "g", "g", " ", "h", "h", "i", " ", " ", "j", "k", "\'", "l", "\'"}, /* apostrophe start and end */
+ {"a", "a", "c", "d", "e", "f", "g", "g", "g", " ", "h", "h", "i", " ", " ", "j", "k", "\'", "l", "l"}, /* Double start and end */
+ {"a", "b", "c", "d", "e", "f", "g", "g", "o", "$", "o", "h", "i", " ", " ", "j", "k", "\'", "\'", "l"}, /* Legit double character */
+ {"a", "$", "a", "d", "e", "f", "g", "g", "o", "$", "o", "h", "i", " ", " ", "j", "k", "l", "$", "l"}, /* Legit double character start and end */
+ {"$", "a", "b", "d", "e", "f", "g", "g", "o", "$", "o", "h", "i", " ", " ", "j", "k", "l", "$", "$"}, /* $$ */
+ {"$", "a", "b", "d", "e", "f", "g", "g", "o", "$", "o", "h", "i", " ", " ", "j", "k", "l", "l", "l"}
+ };
+
+ /* The golden outputs for the above test inputs. */
+ std::string expectedOutput[numStrings] =
+ {
+ {"abcdefg hi jk\'l"},
+ {" bcdefg hi jk\' "},
+ {"\'bcdefg hi jk\'l\'"},
+ {"acdefg hi jk\'l"},
+ {"abcdefgoohi jk\'l"},
+ {"aadefgoohi jkll"},
+ {"abdefgoohi jkl"},
+ {"abdefgoohi jkl"}
+ };
+
+ /*For each test input. */
+ for (size_t h = 0; h < numStrings; ++h)
+ {
+ /* Generate fake vecResults.m_label to mimic AsrClassifier output containing the testText. */
+ for (size_t i = 0; i < 20; i++)
+ {
+ vecResult[i].m_label = testText[h][i];
+ }
+ /* Call function with fake vecResults and save returned string into 'buff'. */
+ std::string buff = arm::app::audio::asr::DecodeOutput(vecResult);
+
+ /* Check that the string returned from the function matches the expected output given above. */
+ REQUIRE(buff.compare(expectedOutput[h]) == 0);
+ }
+}
\ No newline at end of file
diff --git a/tests/use_case/asr/Wav2LetterPostprocessingTest.cc b/tests/use_case/asr/Wav2LetterPostprocessingTest.cc
new file mode 100644
index 0000000..9ed2e1b
--- /dev/null
+++ b/tests/use_case/asr/Wav2LetterPostprocessingTest.cc
@@ -0,0 +1,199 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "Wav2LetterPostprocess.hpp"
+#include "Wav2LetterModel.hpp"
+
+#include <algorithm>
+#include <catch.hpp>
+#include <limits>
+
+template <typename T>
+static TfLiteTensor GetTestTensor(
+ std::vector <int>& shape,
+ T initVal,
+ std::vector<T>& vectorBuf)
+{
+ REQUIRE(0 != shape.size());
+
+ shape.insert(shape.begin(), shape.size());
+ uint32_t sizeInBytes = sizeof(T);
+ for (size_t i = 1; i < shape.size(); ++i) {
+ sizeInBytes *= shape[i];
+ }
+
+ /* Allocate mem. */
+ vectorBuf = std::vector<T>(sizeInBytes, initVal);
+ TfLiteIntArray* dims = tflite::testing::IntArrayFromInts(shape.data());
+ return tflite::testing::CreateQuantizedTensor(
+ vectorBuf.data(), dims,
+ 1, 0, "test-tensor");
+}
+
+TEST_CASE("Checking return value")
+{
+ SECTION("Mismatched post processing parameters and tensor size")
+ {
+ const uint32_t ctxLen = 5;
+ const uint32_t innerLen = 3;
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, 0};
+
+ std::vector <int> tensorShape = {1, 1, 1, 13};
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+ REQUIRE(false == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, false));
+ }
+
+ SECTION("Post processing succeeds")
+ {
+ const uint32_t ctxLen = 5;
+ const uint32_t innerLen = 3;
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, 0};
+
+ std::vector <int> tensorShape = {1, 1, 13, 1};
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+
+ /* Copy elements to compare later. */
+ std::vector <int8_t> originalVec = tensorVec;
+
+ /* This step should not erase anything. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, false));
+ }
+}
+
+
+TEST_CASE("Postprocessing - erasing required elements")
+{
+ constexpr uint32_t ctxLen = 5;
+ constexpr uint32_t innerLen = 3;
+ constexpr uint32_t nRows = 2*ctxLen + innerLen;
+ constexpr uint32_t nCols = 10;
+ constexpr uint32_t blankTokenIdx = nCols - 1;
+ std::vector <int> tensorShape = {1, 1, nRows, nCols};
+
+ SECTION("First and last iteration")
+ {
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, blankTokenIdx};
+
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+
+ /* Copy elements to compare later. */
+ std::vector <int8_t> originalVec = tensorVec;
+
+ /* This step should not erase anything. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, true));
+ REQUIRE(originalVec == tensorVec);
+ }
+
+ SECTION("Right context erase")
+ {
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, blankTokenIdx};
+
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+
+ /* Copy elements to compare later. */
+ std::vector <int8_t> originalVec = tensorVec;
+
+ /* This step should erase the right context only. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, false));
+ REQUIRE(originalVec != tensorVec);
+
+ /* The last ctxLen * 10 elements should be gone. */
+ for (size_t i = 0; i < ctxLen; ++i) {
+ for (size_t j = 0; j < nCols; ++j) {
+ /* Check right context elements are zeroed. */
+ if (j == blankTokenIdx) {
+ CHECK(tensorVec[(ctxLen + innerLen) * nCols + i*nCols + j] == 1);
+ } else {
+ CHECK(tensorVec[(ctxLen + innerLen) * nCols + i*nCols + j] == 0);
+ }
+
+ /* Check left context is preserved. */
+ CHECK(tensorVec[i*nCols + j] == originalVec[i*nCols + j]);
+ }
+ }
+
+ /* Check inner elements are preserved. */
+ for (size_t i = ctxLen * nCols; i < (ctxLen + innerLen) * nCols; ++i) {
+ CHECK(tensorVec[i] == originalVec[i]);
+ }
+ }
+
+ SECTION("Left and right context erase")
+ {
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, blankTokenIdx};
+
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+
+ /* Copy elements to compare later. */
+ std::vector <int8_t> originalVec = tensorVec;
+
+ /* This step should erase right context. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, false));
+
+ /* Calling it the second time should erase the left context. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, false));
+
+ REQUIRE(originalVec != tensorVec);
+
+ /* The first and last ctxLen * 10 elements should be gone. */
+ for (size_t i = 0; i < ctxLen; ++i) {
+ for (size_t j = 0; j < nCols; ++j) {
+ /* Check left and right context elements are zeroed. */
+ if (j == blankTokenIdx) {
+ CHECK(tensorVec[(ctxLen + innerLen) * nCols + i*nCols + j] == 1);
+ CHECK(tensorVec[i*nCols + j] == 1);
+ } else {
+ CHECK(tensorVec[(ctxLen + innerLen) * nCols + i*nCols + j] == 0);
+ CHECK(tensorVec[i*nCols + j] == 0);
+ }
+ }
+ }
+
+ /* Check inner elements are preserved. */
+ for (size_t i = ctxLen * nCols; i < (ctxLen + innerLen) * nCols; ++i) {
+ /* Check left context is preserved. */
+ CHECK(tensorVec[i] == originalVec[i]);
+ }
+ }
+
+ SECTION("Try left context erase")
+ {
+ /* Should not be able to erase the left context if it is the first iteration. */
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, blankTokenIdx};
+
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+
+ /* Copy elements to compare later. */
+ std::vector <int8_t> originalVec = tensorVec;
+
+ /* Calling it the second time should erase the left context. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, true));
+
+ REQUIRE(originalVec == tensorVec);
+ }
+}
diff --git a/tests/use_case/asr/Wav2LetterPreprocessingTest.cc b/tests/use_case/asr/Wav2LetterPreprocessingTest.cc
new file mode 100644
index 0000000..1391011
--- /dev/null
+++ b/tests/use_case/asr/Wav2LetterPreprocessingTest.cc
@@ -0,0 +1,152 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "Wav2LetterPreprocess.hpp"
+
+#include <limits>
+#include <algorithm>
+#include <catch.hpp>
+
+constexpr uint32_t numMfccFeatures = 13;
+constexpr uint32_t numMfccVectors = 10;
+
+/* Test vector output: generated using test-asr-preprocessing.py. */
+int8_t expectedResult[numMfccVectors][numMfccFeatures * 3] = {
+ /* Feature vec 0. */
+ -32, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11, /* MFCCs. */
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, /* Delta 1. */
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, /* Delta 2. */
+
+ /* Feature vec 1. */
+ -31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 2. */
+ -31, 4, -9, -9, -10, -10, -11, -11, -11, -11, -12, -12, -12,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 3. */
+ -31, 4, -9, -9, -10, -10, -11, -11, -11, -11, -11, -12, -12,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 4 : this should have valid delta 1 and delta 2. */
+ -31, 4, -9, -9, -10, -10, -11, -11, -11, -11, -11, -12, -12,
+ -38, -29, -9, 1, -2, -7, -8, -8, -12, -16, -14, -5, 5,
+ -68, -50, -13, 5, 0, -9, -9, -8, -13, -20, -19, -3, 15,
+
+ /* Feature vec 5 : this should have valid delta 1 and delta 2. */
+ -31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -11, -12, -12,
+ -62, -45, -11, 5, 0, -8, -9, -8, -12, -19, -17, -3, 13,
+ -27, -22, -13, -9, -11, -12, -12, -11, -11, -13, -13, -10, -6,
+
+ /* Feature vec 6. */
+ -31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 7. */
+ -32, 4, -9, -8, -10, -10, -11, -11, -11, -12, -12, -11, -11,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 8. */
+ -32, 4, -9, -8, -10, -10, -11, -11, -11, -12, -12, -11, -11,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 9. */
+ -31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10
+};
+
+void PopulateTestWavVector(std::vector<int16_t>& vec)
+{
+ constexpr int int16max = std::numeric_limits<int16_t>::max();
+ int val = 0;
+ for (size_t i = 0; i < vec.size(); ++i, ++val) {
+
+ /* We want a differential filter response from both - order 1
+ * and 2 => Don't have a linear signal here - we use a signal
+ * using squares for example. Alternate sign flips might work
+ * just as well and will be computationally less work! */
+ int valsq = val * val;
+ if (valsq > int16max) {
+ val = 0;
+ valsq = 0;
+ }
+ vec[i] = valsq;
+ }
+}
+
+TEST_CASE("Preprocessing calculation INT8")
+{
+ /* Initialise the HAL and platform. */
+ hal_platform platform;
+ data_acq_module data_acq;
+ data_psn_module data_psn;
+ platform_timer timer;
+ hal_init(&platform, &data_acq, &data_psn, &timer);
+ hal_platform_init(&platform);
+
+ /* Constants. */
+ const uint32_t windowLen = 512;
+ const uint32_t windowStride = 160;
+ const int dimArray[] = {3, 1, numMfccFeatures * 3, numMfccVectors};
+ const float quantScale = 0.1410219967365265;
+ const int quantOffset = -11;
+
+ /* Test wav memory. */
+ std::vector <int16_t> testWav((windowStride * numMfccVectors) +
+ (windowLen - windowStride));
+
+ /* Populate with dummy input. */
+ PopulateTestWavVector(testWav);
+
+ /* Allocate mem for tensor. */
+ std::vector<int8_t> tensorVec(dimArray[1]*dimArray[2]*dimArray[3]);
+
+ /* Initialise dimensions and the test tensor. */
+ TfLiteIntArray* dims= tflite::testing::IntArrayFromInts(dimArray);
+ TfLiteTensor tensor = tflite::testing::CreateQuantizedTensor(
+ tensorVec.data(), dims, quantScale, quantOffset, "preprocessedInput");
+
+ /* Initialise pre-processing module. */
+ arm::app::audio::asr::Preprocess prep{
+ numMfccFeatures, windowLen, windowStride, numMfccVectors};
+
+ /* Invoke pre-processing. */
+ REQUIRE(prep.Invoke(testWav.data(), testWav.size(), &tensor));
+
+ /* Wrap the tensor with a std::vector for ease. */
+ int8_t * tensorData = tflite::GetTensorData<int8_t>(&tensor);
+ std::vector <int8_t> vecResults =
+ std::vector<int8_t>(tensorData, tensorData + tensor.bytes);
+
+ /* Check sizes. */
+ REQUIRE(vecResults.size() == sizeof(expectedResult));
+
+ /* Check that the elements have been calculated correctly. */
+ for (uint32_t j = 0; j < numMfccVectors; ++j) {
+ for (uint32_t i = 0; i < numMfccFeatures * 3; ++i) {
+ size_t tensorIdx = (j * numMfccFeatures * 3) + i;
+ CHECK(vecResults[tensorIdx] == expectedResult[j][i]);
+ }
+ }
+}
diff --git a/tests/use_case/img_class/ImgClassTests.cc b/tests/use_case/img_class/ImgClassTests.cc
new file mode 100644
index 0000000..09f82da
--- /dev/null
+++ b/tests/use_case/img_class/ImgClassTests.cc
@@ -0,0 +1,18 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#define CATCH_CONFIG_MAIN
+#include <catch.hpp>
diff --git a/tests/use_case/img_class/ImgClassificationUCTest.cc b/tests/use_case/img_class/ImgClassificationUCTest.cc
new file mode 100644
index 0000000..abfcc44
--- /dev/null
+++ b/tests/use_case/img_class/ImgClassificationUCTest.cc
@@ -0,0 +1,140 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "ClassificationResult.hpp"
+#include "Classifier.hpp"
+#include "hal.h"
+#include "Labels.hpp"
+#include "MobileNetModel.hpp"
+#include "UseCaseHandler.hpp"
+#include "UseCaseCommonUtils.hpp"
+
+#include <catch.hpp>
+
+TEST_CASE("Model info")
+{
+ /* Model wrapper object. */
+ arm::app::MobileNetModel model;
+
+ /* Load the model. */
+ REQUIRE(model.Init());
+
+ /* Instantiate application context. */
+ arm::app::ApplicationContext caseContext;
+
+ caseContext.Set<arm::app::Model&>("model", model);
+
+ REQUIRE(model.ShowModelInfoHandler());
+}
+
+
+TEST_CASE("Inference by index", "[.]")
+{
+ hal_platform platform;
+ data_acq_module data_acq;
+ data_psn_module data_psn;
+ platform_timer timer;
+
+ /* Initialise the HAL and platform. */
+ hal_init(&platform, &data_acq, &data_psn, &timer);
+ hal_platform_init(&platform);
+
+ /* Model wrapper object. */
+ arm::app::MobileNetModel model;
+
+ /* Load the model. */
+ REQUIRE(model.Init());
+
+ /* Instantiate application context. */
+ arm::app::ApplicationContext caseContext;
+
+ caseContext.Set<hal_platform&>("platform", platform);
+ caseContext.Set<arm::app::Model&>("model", model);
+ caseContext.Set<uint32_t>("imgIndex", 0);
+ arm::app::Classifier classifier; /* Classifier wrapper object. */
+ caseContext.Set<arm::app::Classifier&>("classifier", classifier);
+
+ std::vector <std::string> labels;
+ GetLabelsVector(labels);
+ caseContext.Set<const std::vector <std::string>&>("labels", labels);
+
+ REQUIRE(arm::app::ClassifyImageHandler(caseContext, 0, false));
+
+ auto results = caseContext.Get<std::vector<arm::app::ClassificationResult>>("results");
+
+ REQUIRE(results[0].m_labelIdx == 282);
+}
+
+
+TEST_CASE("Inference run all images", "[.]")
+{
+ hal_platform platform;
+ data_acq_module data_acq;
+ data_psn_module data_psn;
+ platform_timer timer;
+
+ /* Initialise the HAL and platform. */
+ hal_init(&platform, &data_acq, &data_psn, &timer);
+ hal_platform_init(&platform);
+
+ /* Model wrapper object. */
+ arm::app::MobileNetModel model;
+
+ /* Load the model. */
+ REQUIRE(model.Init());
+
+ /* Instantiate application context. */
+ arm::app::ApplicationContext caseContext;
+
+ caseContext.Set<hal_platform&>("platform", platform);
+ caseContext.Set<arm::app::Model&>("model", model);
+ caseContext.Set<uint32_t>("imgIndex", 0);
+ arm::app::Classifier classifier; /* classifier wrapper object. */
+ caseContext.Set<arm::app::Classifier&>("classifier", classifier);
+
+ std::vector <std::string> labels;
+ GetLabelsVector(labels);
+ caseContext.Set<const std::vector <std::string>&>("labels", labels);
+
+ REQUIRE(arm::app::ClassifyImageHandler(caseContext, 0, true));
+}
+
+
+TEST_CASE("List all images")
+{
+ hal_platform platform;
+ data_acq_module data_acq;
+ data_psn_module data_psn;
+ platform_timer timer;
+
+ /* Initialise the HAL and platform. */
+ hal_init(&platform, &data_acq, &data_psn, &timer);
+ hal_platform_init(&platform);
+
+ /* Model wrapper object. */
+ arm::app::MobileNetModel model;
+
+ /* Load the model. */
+ REQUIRE(model.Init());
+
+ /* Instantiate application context. */
+ arm::app::ApplicationContext caseContext;
+
+ caseContext.Set<hal_platform&>("platform", platform);
+ caseContext.Set<arm::app::Model&>("model", model);
+
+ REQUIRE(arm::app::ListFilesHandler(caseContext));
+}
\ No newline at end of file
diff --git a/tests/use_case/img_class/InferenceTestMobilenetV2.cc b/tests/use_case/img_class/InferenceTestMobilenetV2.cc
new file mode 100644
index 0000000..698382f
--- /dev/null
+++ b/tests/use_case/img_class/InferenceTestMobilenetV2.cc
@@ -0,0 +1,90 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "hal.h"
+#include "ImageUtils.hpp"
+#include "MobileNetModel.hpp"
+#include "TensorFlowLiteMicro.hpp"
+#include "TestData_img_class.hpp"
+
+#include <catch.hpp>
+
+
+bool RunInference(arm::app::Model& model, const uint8_t imageData[])
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ const size_t copySz = inputTensor->bytes < IFM_DATA_SIZE ?
+ inputTensor->bytes :
+ IFM_DATA_SIZE;
+ memcpy(inputTensor->data.data, imageData, copySz);
+
+ if(model.IsDataSigned()){
+ convertImgIoInt8(inputTensor->data.data, copySz);
+ }
+
+ return model.RunInference();
+}
+
+template<typename T>
+void TestInference(int imageIdx, arm::app::Model& model, T tolerance) {
+ auto image = get_ifm_data_array(imageIdx);
+ auto goldenFV = get_ofm_data_array(imageIdx);
+
+ REQUIRE(RunInference(model, image));
+
+ TfLiteTensor* outputTensor = model.GetOutputTensor(0);
+
+ REQUIRE(outputTensor);
+ REQUIRE(outputTensor->bytes == OFM_DATA_SIZE);
+ auto tensorData = tflite::GetTensorData<T>(outputTensor);
+ REQUIRE(tensorData);
+
+ for (size_t i = 0; i < outputTensor->bytes; i++) {
+ REQUIRE((int)tensorData[i] == Approx((int)((T)goldenFV[i])).epsilon(tolerance));
+ }
+}
+
+
+TEST_CASE("Running inference with TensorFlow Lite Micro and MobileNeV2 Uint8", "[MobileNetV2]")
+{
+ SECTION("Executing inferences sequentially")
+ {
+ arm::app::MobileNetModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ for (uint32_t i = 0 ; i < NUMBER_OF_FM_FILES; ++i) {
+ TestInference<uint8_t>(i, model, 1);
+ }
+ }
+
+ for (uint32_t i = 0 ; i < NUMBER_OF_FM_FILES; ++i) {
+ DYNAMIC_SECTION("Executing inference with re-init")
+ {
+ arm::app::MobileNetModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ TestInference<uint8_t>(i, model, 1);
+ }
+ }
+}
diff --git a/tests/use_case/kws/InferenceTestDSCNN.cc b/tests/use_case/kws/InferenceTestDSCNN.cc
new file mode 100644
index 0000000..06358a4
--- /dev/null
+++ b/tests/use_case/kws/InferenceTestDSCNN.cc
@@ -0,0 +1,104 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "DsCnnModel.hpp"
+#include "hal.h"
+#include "TestData_kws.hpp"
+#include "TensorFlowLiteMicro.hpp"
+
+#include <catch.hpp>
+#include <random>
+
+bool RunInference(arm::app::Model& model, const int8_t vec[])
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ const size_t copySz = inputTensor->bytes < IFM_DATA_SIZE ?
+ inputTensor->bytes :
+ IFM_DATA_SIZE;
+ memcpy(inputTensor->data.data, vec, copySz);
+
+ return model.RunInference();
+}
+
+bool RunInferenceRandom(arm::app::Model& model)
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ std::random_device rndDevice;
+ std::mt19937 mersenneGen{rndDevice()};
+ std::uniform_int_distribution<short> dist {-128, 127};
+
+ auto gen = [&dist, &mersenneGen](){
+ return dist(mersenneGen);
+ };
+
+ std::vector<int8_t> randomAudio(inputTensor->bytes);
+ std::generate(std::begin(randomAudio), std::end(randomAudio), gen);
+
+ REQUIRE(RunInference(model, randomAudio.data()));
+ return true;
+}
+
+template<typename T>
+void TestInference(const T* input_goldenFV, const T* output_goldenFV, arm::app::Model& model)
+{
+ REQUIRE(RunInference(model, input_goldenFV));
+
+ TfLiteTensor* outputTensor = model.GetOutputTensor(0);
+
+ REQUIRE(outputTensor);
+ REQUIRE(outputTensor->bytes == OFM_DATA_SIZE);
+ auto tensorData = tflite::GetTensorData<T>(outputTensor);
+ REQUIRE(tensorData);
+
+ for (size_t i = 0; i < outputTensor->bytes; i++) {
+ REQUIRE((int)tensorData[i] == (int)((T)output_goldenFV[i]));
+ }
+}
+
+TEST_CASE("Running random inference with TensorFlow Lite Micro and DsCnnModel Int8", "[DS_CNN]")
+{
+ arm::app::DsCnnModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ REQUIRE(RunInferenceRandom(model));
+}
+
+TEST_CASE("Running inference with TensorFlow Lite Micro and DsCnnModel Uint8", "[DS_CNN]")
+{
+ for (uint32_t i = 0 ; i < NUMBER_OF_FM_FILES; ++i) {
+ const int8_t* input_goldenFV = get_ifm_data_array(i);;
+ const int8_t* output_goldenFV = get_ofm_data_array(i);
+
+ DYNAMIC_SECTION("Executing inference with re-init")
+ {
+ arm::app::DsCnnModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ TestInference<int8_t>(input_goldenFV, output_goldenFV, model);
+
+ }
+ }
+}
diff --git a/tests/use_case/kws/KWSHandlerTest.cc b/tests/use_case/kws/KWSHandlerTest.cc
new file mode 100644
index 0000000..dee2f6f
--- /dev/null
+++ b/tests/use_case/kws/KWSHandlerTest.cc
@@ -0,0 +1,180 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include <catch.hpp>
+#include "DsCnnModel.hpp"
+#include "hal.h"
+
+#include "KwsResult.hpp"
+#include "Labels.hpp"
+#include "UseCaseHandler.hpp"
+#include "Classifier.hpp"
+#include "UseCaseCommonUtils.hpp"
+
+TEST_CASE("Model info")
+{
+ /* Model wrapper object. */
+ arm::app::DsCnnModel model;
+
+ /* Load the model. */
+ REQUIRE(model.Init());
+
+ /* Instantiate application context. */
+ arm::app::ApplicationContext caseContext;
+
+ caseContext.Set<arm::app::Model&>("model", model);
+
+ REQUIRE(model.ShowModelInfoHandler());
+}
+
+
+TEST_CASE("Inference by index")
+{
+ hal_platform platform;
+ data_acq_module data_acq;
+ data_psn_module data_psn;
+ platform_timer timer;
+
+ /* Initialise the HAL and platform. */
+ hal_init(&platform, &data_acq, &data_psn, &timer);
+ hal_platform_init(&platform);
+
+ /* Model wrapper object. */
+ arm::app::DsCnnModel model;
+
+ /* Load the model. */
+ REQUIRE(model.Init());
+
+ /* Instantiate application context. */
+ arm::app::ApplicationContext caseContext;
+ caseContext.Set<hal_platform&>("platform", platform);
+ caseContext.Set<arm::app::Model&>("model", model);
+ caseContext.Set<int>("frameLength", g_FrameLength); /* 640 sample length for DSCNN. */
+ caseContext.Set<int>("frameStride", g_FrameStride); /* 320 sample stride for DSCNN. */
+ caseContext.Set<float>("scoreThreshold", 0.5); /* Normalised score threshold. */
+
+ arm::app::Classifier classifier; /* classifier wrapper object. */
+ caseContext.Set<arm::app::Classifier&>("classifier", classifier);
+
+ auto checker = [&](uint32_t audioIndex, std::vector<uint32_t> labelIndex)
+ {
+ caseContext.Set<uint32_t>("audioIndex", audioIndex);
+
+ std::vector<std::string> labels;
+ GetLabelsVector(labels);
+ caseContext.Set<const std::vector<std::string> &>("labels", labels);
+
+ REQUIRE(arm::app::ClassifyAudioHandler(caseContext, audioIndex, false));
+ REQUIRE(caseContext.Has("results"));
+
+ auto results = caseContext.Get<std::vector<arm::app::kws::KwsResult>>("results");
+
+ REQUIRE(results.size() == labelIndex.size());
+
+ for (size_t i = 0; i < results.size(); i++ ) {
+ REQUIRE(results[i].m_resultVec.size());
+ REQUIRE(results[i].m_resultVec[0].m_labelIdx == labelIndex[i]);
+ }
+
+ };
+
+ SECTION("Index = 0, short clip down")
+ {
+ /* Result: down. */
+ checker(0, {5});
+ }
+
+ SECTION("Index = 1, long clip right->left->up")
+ {
+ /* Result: right->right->left->up->up. */
+ checker(1, {7, 1, 6, 4, 4});
+ }
+
+ SECTION("Index = 2, short clip yes")
+ {
+ /* Result: yes. */
+ checker(2, {2});
+ }
+
+ SECTION("Index = 3, long clip yes->no->go->stop")
+ {
+ /* Result: yes->go->no->go->go->go->stop. */
+ checker(3, {2, 11, 3, 11, 11, 11, 10});
+ }
+}
+
+
+TEST_CASE("Inference run all clips")
+{
+ hal_platform platform;
+ data_acq_module data_acq;
+ data_psn_module data_psn;
+ platform_timer timer;
+
+ /* Initialise the HAL and platform. */
+ hal_init(&platform, &data_acq, &data_psn, &timer);
+ hal_platform_init(&platform);
+
+ /* Model wrapper object. */
+ arm::app::DsCnnModel model;
+
+ /* Load the model. */
+ REQUIRE(model.Init());
+
+ /* Instantiate application context. */
+ arm::app::ApplicationContext caseContext;
+
+ caseContext.Set<hal_platform&>("platform", platform);
+ caseContext.Set<arm::app::Model&>("model", model);
+ caseContext.Set<uint32_t>("clipIndex", 0);
+ caseContext.Set<int>("frameLength", g_FrameLength); /* 640 sample length for DSCNN. */
+ caseContext.Set<int>("frameStride", g_FrameStride); /* 320 sample stride for DSCNN. */
+ caseContext.Set<float>("scoreThreshold", 0.9); /* Normalised score threshold. */
+ arm::app::Classifier classifier; /* classifier wrapper object. */
+ caseContext.Set<arm::app::Classifier&>("classifier", classifier);
+
+ std::vector <std::string> labels;
+ GetLabelsVector(labels);
+ caseContext.Set<const std::vector <std::string>&>("labels", labels);
+ REQUIRE(arm::app::ClassifyAudioHandler(caseContext, 0, true));
+}
+
+
+TEST_CASE("List all audio clips")
+{
+ hal_platform platform;
+ data_acq_module data_acq;
+ data_psn_module data_psn;
+ platform_timer timer;
+
+ /* Initialise the HAL and platform. */
+ hal_init(&platform, &data_acq, &data_psn, &timer);
+ hal_platform_init(&platform);
+
+ /* Model wrapper object. */
+ arm::app::DsCnnModel model;
+
+ /* Load the model. */
+ REQUIRE(model.Init());
+
+ /* Instantiate application context. */
+ arm::app::ApplicationContext caseContext;
+
+ caseContext.Set<hal_platform&>("platform", platform);
+ caseContext.Set<arm::app::Model&>("model", model);
+
+ REQUIRE(arm::app::ListFilesHandler(caseContext));
+}
\ No newline at end of file
diff --git a/tests/use_case/kws/KwsTests.cc b/tests/use_case/kws/KwsTests.cc
new file mode 100644
index 0000000..09f82da
--- /dev/null
+++ b/tests/use_case/kws/KwsTests.cc
@@ -0,0 +1,18 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#define CATCH_CONFIG_MAIN
+#include <catch.hpp>
diff --git a/tests/use_case/kws/MfccTests.cc b/tests/use_case/kws/MfccTests.cc
new file mode 100644
index 0000000..407861f
--- /dev/null
+++ b/tests/use_case/kws/MfccTests.cc
@@ -0,0 +1,156 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "DsCnnMfcc.hpp"
+
+#include <algorithm>
+#include <catch.hpp>
+#include <limits>
+
+/* First 640 samples from yes.wav. */
+const std::vector<int16_t> testWav = std::vector<int16_t>{
+ 139, 143, 164, 163, 157, 156, 151, 148, 172, 171,
+ 165, 169, 149, 142, 145, 147, 166, 146, 112, 132,
+ 132, 136, 165, 176, 176, 152, 138, 158, 179, 185,
+ 183, 148, 121, 130, 167, 204, 163, 132, 165, 184,
+ 193, 205, 210, 204, 195, 178, 168, 197, 207, 201,
+ 197, 177, 185, 196, 191, 198, 196, 183, 193, 181,
+ 157, 170, 167, 159, 164, 152, 146, 167, 180, 171,
+ 194, 232, 204, 173, 171, 172, 184, 169, 175, 199,
+ 200, 195, 185, 214, 214, 193, 196, 191, 204, 191,
+ 172, 187, 183, 192, 203, 172, 182, 228, 232, 205,
+ 177, 174, 191, 210, 210, 211, 197, 177, 198, 217,
+ 233, 236, 203, 191, 169, 145, 149, 161, 198, 206,
+ 176, 137, 142, 181, 200, 215, 201, 188, 166, 162,
+ 184, 155, 135, 132, 126, 142, 169, 184, 172, 156,
+ 132, 119, 150, 147, 154, 160, 125, 130, 137, 154,
+ 161, 168, 195, 182, 160, 134, 138, 146, 130, 120,
+ 101, 122, 137, 118, 117, 131, 145, 140, 146, 148,
+ 148, 168, 159, 134, 114, 114, 130, 147, 147, 134,
+ 125, 98, 107, 127, 99, 79, 84, 107, 117, 114,
+ 93, 92, 127, 112, 109, 110, 96, 118, 97, 87,
+ 110, 95, 128, 153, 147, 165, 146, 106, 101, 137,
+ 139, 96, 73, 90, 91, 51, 69, 102, 100, 103,
+ 96, 101, 123, 107, 82, 89, 118, 127, 99, 100,
+ 111, 97, 111, 123, 106, 121, 133, 103, 100, 88,
+ 85, 111, 114, 125, 102, 91, 97, 84, 139, 157,
+ 109, 66, 72, 129, 111, 90, 127, 126, 101, 109,
+ 142, 138, 129, 159, 140, 80, 74, 78, 76, 98,
+ 68, 42, 106, 143, 112, 102, 115, 114, 82, 75,
+ 92, 80, 110, 114, 66, 86, 119, 101, 101, 103,
+ 118, 145, 85, 40, 62, 88, 95, 87, 73, 64,
+ 86, 71, 71, 105, 80, 73, 96, 92, 85, 90,
+ 81, 86, 105, 100, 89, 78, 102, 114, 95, 98,
+ 69, 70, 108, 112, 111, 90, 104, 137, 143, 160,
+ 145, 121, 98, 86, 91, 87, 115, 123, 109, 99,
+ 85, 120, 131, 116, 125, 144, 153, 111, 98, 110,
+ 93, 89, 101, 137, 155, 142, 108, 94, 136, 145,
+ 129, 129, 122, 109, 90, 76, 81, 110, 119, 96,
+ 95, 102, 105, 111, 90, 89, 111, 115, 86, 51,
+ 107, 140, 105, 105, 110, 142, 125, 76, 75, 69,
+ 65, 52, 61, 69, 55, 42, 47, 58, 37, 35,
+ 24, 20, 44, 22, 16, 26, 6, 3, 4, 23,
+ 60, 51, 30, 12, 24, 31, -9, -16, -13, 13,
+ 19, 9, 37, 55, 70, 36, 23, 57, 45, 33,
+ 50, 59, 18, 11, 62, 74, 52, 8, -3, 26,
+ 51, 48, -5, -9, 12, -7, -12, -5, 28, 41,
+ -2, -30, -13, 31, 33, -12, -22, -8, -15, -17,
+ 2, -6, -25, -27, -24, -8, 4, -9, -52, -47,
+ -9, -32, -45, -5, 41, 15, -32, -14, 2, -1,
+ -10, -30, -32, -25, -21, -17, -14, 8, -4, -13,
+ 34, 18, -36, -38, -18, -19, -28, -17, -14, -16,
+ -2, -20, -27, 12, 11, -17, -33, -12, -22, -64,
+ -42, -26, -23, -22, -37, -51, -53, -30, -18, -48,
+ -69, -38, -54, -96, -72, -49, -50, -57, -41, -22,
+ -43, -64, -54, -23, -49, -69, -41, -44, -42, -49,
+ -40, -26, -54, -50, -38, -49, -70, -94, -89, -69,
+ -56, -65, -71, -47, -39, -49, -79, -91, -56, -46,
+ -62, -86, -64, -32, -47, -50, -71, -77, -65, -68,
+ -52, -51, -61, -67, -61, -81, -93, -52, -59, -62,
+ -51, -75, -76, -50, -32, -54, -68, -70, -43, 1,
+ -42, -92, -80, -41, -38, -79, -69, -49, -82, -122,
+ -93, -21, -24, -61, -70, -73, -62, -74, -69, -43,
+ -25, -15, -43, -23, -26, -69, -44, -12, 1, -51,
+ -78, -13, 3, -53, -105, -72, -24, -62, -66, -31,
+ -40, -65, -86, -64, -44, -55, -63, -61, -37, -41,
+};
+
+/* Golden audio ops mfcc output for the above wav. */
+const std::vector<float> testWavMfcc {
+ -22.67135, -0.61615, 2.07233, 0.58137, 1.01655, 0.85816, 0.46039, 0.03393, 1.16511, 0.0072,
+};
+
+arm::app::audio::DsCnnMFCC GetMFCCInstance() {
+ const int sampFreq = arm::app::audio::DsCnnMFCC::ms_defaultSamplingFreq;
+ const int frameLenMs = 40;
+ const int frameLenSamples = sampFreq * frameLenMs * 0.001;
+ const int numMfccFeats = 10;
+
+ return arm::app::audio::DsCnnMFCC(numMfccFeats, frameLenSamples);
+}
+
+template <class T>
+void TestQuantisedMFCC() {
+ const float quantScale = 1.1088106632232666;
+ const int quantOffset = 95;
+ std::vector<T> mfccOutput = GetMFCCInstance().MfccComputeQuant<T>(testWav, quantScale, quantOffset);
+
+ const long min_val = std::numeric_limits<T>::min();
+ const long max_val = std::numeric_limits<T>::max();
+
+ for (size_t i = 0; i < testWavMfcc.size(); ++i){
+ long TestWavMfcc = (std::lround((testWavMfcc[i] / quantScale) + quantOffset));
+ T quantizedTestWavMfcc = static_cast<T>(std::max(min_val, std::min(TestWavMfcc, max_val)));
+
+ REQUIRE(quantizedTestWavMfcc == Approx(mfccOutput[i]).margin(0));
+ }
+}
+template void TestQuantisedMFCC<int8_t>();
+template void TestQuantisedMFCC<uint8_t>();
+template void TestQuantisedMFCC<int16_t>();
+
+
+TEST_CASE("MFCC calculation test") {
+ hal_platform platform;
+ data_acq_module dataAcq;
+ data_psn_module dataPsn;
+ platform_timer timer;
+
+ /* Initialise the HAL and platform. */
+ hal_init(&platform, &dataAcq, &dataPsn, &timer);
+ hal_platform_init(&platform);
+
+ SECTION("FP32")
+ {
+ auto mfccOutput = GetMFCCInstance().MfccCompute(testWav);
+ REQUIRE_THAT( mfccOutput, Catch::Approx(testWavMfcc).margin(0.0001) );
+ }
+
+ SECTION("int8_t")
+ {
+ TestQuantisedMFCC<int8_t>();
+ }
+
+ SECTION("uint8_t")
+ {
+ TestQuantisedMFCC<uint8_t>();
+ }
+
+ SECTION("MFCC quant calculation test - int16_t")
+ {
+ TestQuantisedMFCC<int16_t>();
+ }
+}
\ No newline at end of file
diff --git a/tests/use_case/kws_asr/InferenceTestDSCNN.cc b/tests/use_case/kws_asr/InferenceTestDSCNN.cc
new file mode 100644
index 0000000..f0e5c02
--- /dev/null
+++ b/tests/use_case/kws_asr/InferenceTestDSCNN.cc
@@ -0,0 +1,111 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "DsCnnModel.hpp"
+#include "hal.h"
+#include "TestData_kws.hpp"
+#include "TensorFlowLiteMicro.hpp"
+
+#include <catch.hpp>
+#include <random>
+
+namespace arm {
+namespace app {
+namespace kws {
+bool RunInference(arm::app::Model& model, const int8_t vec[])
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ const size_t copySz = inputTensor->bytes < IFM_DATA_SIZE ?
+ inputTensor->bytes :
+ IFM_DATA_SIZE;
+ memcpy(inputTensor->data.data, vec, copySz);
+
+ return model.RunInference();
+}
+
+bool RunInferenceRandom(arm::app::Model& model)
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ std::random_device rndDevice;
+ std::mt19937 mersenneGen{rndDevice()};
+ std::uniform_int_distribution<short> dist {-128, 127};
+
+ auto gen = [&dist, &mersenneGen](){
+ return dist(mersenneGen);
+ };
+
+ std::vector<int8_t> randomAudio(inputTensor->bytes);
+ std::generate(std::begin(randomAudio), std::end(randomAudio), gen);
+
+ REQUIRE(RunInference(model, randomAudio.data()));
+ return true;
+}
+
+template<typename T>
+void TestInference(const T* input_goldenFV, const T* output_goldenFV, arm::app::Model& model)
+{
+ REQUIRE(RunInference(model, input_goldenFV));
+
+ TfLiteTensor* outputTensor = model.GetOutputTensor(0);
+
+ REQUIRE(outputTensor);
+ REQUIRE(outputTensor->bytes == OFM_DATA_SIZE);
+ auto tensorData = tflite::GetTensorData<T>(outputTensor);
+ REQUIRE(tensorData);
+
+ for (size_t i = 0; i < outputTensor->bytes; i++) {
+ REQUIRE((int)tensorData[i] == (int)((T)output_goldenFV[i]));
+ }
+}
+
+TEST_CASE("Running random inference with Tflu and DsCnnModel Int8", "[DS_CNN]")
+{
+ arm::app::DsCnnModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ REQUIRE(RunInferenceRandom(model));
+}
+
+TEST_CASE("Running inference with Tflu and DsCnnModel Uint8", "[DS_CNN]")
+{
+ for (uint32_t i = 0 ; i < NUMBER_OF_FM_FILES; ++i) {
+ const int8_t* input_goldenFV = get_ifm_data_array(i);
+ const int8_t* output_goldenFV = get_ofm_data_array(i);
+
+ DYNAMIC_SECTION("Executing inference with re-init")
+ {
+ arm::app::DsCnnModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ TestInference<int8_t>(input_goldenFV, output_goldenFV, model);
+
+ }
+ }
+}
+
+} //namespace
+} //namespace
+} //namespace
diff --git a/tests/use_case/kws_asr/InferenceTestWav2Letter.cc b/tests/use_case/kws_asr/InferenceTestWav2Letter.cc
new file mode 100644
index 0000000..ee63c2f
--- /dev/null
+++ b/tests/use_case/kws_asr/InferenceTestWav2Letter.cc
@@ -0,0 +1,114 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "hal.h"
+#include "TensorFlowLiteMicro.hpp"
+#include "Wav2LetterModel.hpp"
+#include "TestData_asr.hpp"
+
+#include <catch.hpp>
+#include <random>
+
+namespace arm {
+namespace app {
+namespace asr {
+
+bool RunInference(arm::app::Model& model, const int8_t vec[], const size_t copySz)
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ memcpy(inputTensor->data.data, vec, copySz);
+
+ return model.RunInference();
+}
+
+bool RunInferenceRandom(arm::app::Model& model)
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ std::random_device rndDevice;
+ std::mt19937 mersenneGen{rndDevice()};
+ std::uniform_int_distribution<short> dist {-128, 127};
+
+ auto gen = [&dist, &mersenneGen](){
+ return dist(mersenneGen);
+ };
+
+ std::vector<int8_t> randomAudio(inputTensor->bytes);
+ std::generate(std::begin(randomAudio), std::end(randomAudio), gen);
+
+ REQUIRE(RunInference(model, randomAudio.data(), inputTensor->bytes));
+ return true;
+}
+
+/* Skip this test, Wav2LetterModel if not Vela optimized but only from ML-zoo will fail. */
+TEST_CASE("Running random inference with Tflu and Wav2LetterModel Int8", "[Wav2Letter][.]")
+{
+ arm::app::Wav2LetterModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ REQUIRE(RunInferenceRandom(model));
+}
+
+
+template<typename T>
+void TestInference(const T* input_goldenFV, const T* output_goldenFV, arm::app::Model& model)
+{
+ TfLiteTensor* inputTensor = model.GetInputTensor(0);
+ REQUIRE(inputTensor);
+
+ REQUIRE(RunInference(model, input_goldenFV, inputTensor->bytes));
+
+ TfLiteTensor* outputTensor = model.GetOutputTensor(0);
+
+ REQUIRE(outputTensor);
+ REQUIRE(outputTensor->bytes == OFM_DATA_SIZE);
+ auto tensorData = tflite::GetTensorData<T>(outputTensor);
+ REQUIRE(tensorData);
+
+ for (size_t i = 0; i < outputTensor->bytes; i++) {
+ REQUIRE((int)tensorData[i] == (int)((T)output_goldenFV[i]));
+ }
+}
+
+TEST_CASE("Running inference with Tflu and Wav2LetterModel Int8", "[Wav2Letter][.]")
+{
+ 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);
+
+ DYNAMIC_SECTION("Executing inference with re-init")
+ {
+ arm::app::Wav2LetterModel model{};
+
+ REQUIRE_FALSE(model.IsInited());
+ REQUIRE(model.Init());
+ REQUIRE(model.IsInited());
+
+ TestInference<int8_t>(input_goldenFV, output_goldenFV, model);
+
+ }
+ }
+}
+
+} //namespace
+} //namespace
+} //namespace
diff --git a/tests/use_case/kws_asr/InitModels.cc b/tests/use_case/kws_asr/InitModels.cc
new file mode 100644
index 0000000..770944d
--- /dev/null
+++ b/tests/use_case/kws_asr/InitModels.cc
@@ -0,0 +1,52 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "DsCnnModel.hpp"
+#include "Wav2LetterModel.hpp"
+
+#include <catch.hpp>
+
+/* Skip this test, Wav2LetterModel if not Vela optimized but only from ML-zoo will fail. */
+TEST_CASE("Init two Models", "[.]")
+{
+ arm::app::DsCnnModel model1;
+ arm::app::DsCnnModel model2;
+
+ /* Ideally we should load the wav2letter model here, but there is
+ * none available to run on native (ops not supported on unoptimised
+ * version). However, we can certainly create two instances of the
+ * same type of model to see if our tensor arena re-use works as
+ * intended.
+ *
+ * @TODO: uncomment this when this model can run on native pipeline. */
+ //arm::app::Wav2LetterModel model2; /* model2. */
+
+ /* Load/initialise the first model. */
+ REQUIRE(model1.Init());
+
+ /* Allocator instance should have been created. */
+ REQUIRE(nullptr != model1.GetAllocator());
+
+ /* Load the second model using the same allocator as model 1. */
+ REQUIRE(model2.Init(model1.GetAllocator()));
+
+ /* Make sure they point to the same allocator object. */
+ REQUIRE(model1.GetAllocator() == model2.GetAllocator());
+
+ /* Both models should report being initialised. */
+ REQUIRE(true == model1.IsInited());
+ REQUIRE(true == model2.IsInited());
+}
\ No newline at end of file
diff --git a/tests/use_case/kws_asr/KwsAsrTests.cc b/tests/use_case/kws_asr/KwsAsrTests.cc
new file mode 100644
index 0000000..09f82da
--- /dev/null
+++ b/tests/use_case/kws_asr/KwsAsrTests.cc
@@ -0,0 +1,18 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#define CATCH_CONFIG_MAIN
+#include <catch.hpp>
diff --git a/tests/use_case/kws_asr/MfccTests.cc b/tests/use_case/kws_asr/MfccTests.cc
new file mode 100644
index 0000000..9509519
--- /dev/null
+++ b/tests/use_case/kws_asr/MfccTests.cc
@@ -0,0 +1,156 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "DsCnnMfcc.hpp"
+
+#include <algorithm>
+#include <catch.hpp>
+#include <limits>
+
+/* First 640 samples from yes.wav. */
+const std::vector<int16_t> testWav = std::vector<int16_t>{
+ 139, 143, 164, 163, 157, 156, 151, 148, 172, 171,
+ 165, 169, 149, 142, 145, 147, 166, 146, 112, 132,
+ 132, 136, 165, 176, 176, 152, 138, 158, 179, 185,
+ 183, 148, 121, 130, 167, 204, 163, 132, 165, 184,
+ 193, 205, 210, 204, 195, 178, 168, 197, 207, 201,
+ 197, 177, 185, 196, 191, 198, 196, 183, 193, 181,
+ 157, 170, 167, 159, 164, 152, 146, 167, 180, 171,
+ 194, 232, 204, 173, 171, 172, 184, 169, 175, 199,
+ 200, 195, 185, 214, 214, 193, 196, 191, 204, 191,
+ 172, 187, 183, 192, 203, 172, 182, 228, 232, 205,
+ 177, 174, 191, 210, 210, 211, 197, 177, 198, 217,
+ 233, 236, 203, 191, 169, 145, 149, 161, 198, 206,
+ 176, 137, 142, 181, 200, 215, 201, 188, 166, 162,
+ 184, 155, 135, 132, 126, 142, 169, 184, 172, 156,
+ 132, 119, 150, 147, 154, 160, 125, 130, 137, 154,
+ 161, 168, 195, 182, 160, 134, 138, 146, 130, 120,
+ 101, 122, 137, 118, 117, 131, 145, 140, 146, 148,
+ 148, 168, 159, 134, 114, 114, 130, 147, 147, 134,
+ 125, 98, 107, 127, 99, 79, 84, 107, 117, 114,
+ 93, 92, 127, 112, 109, 110, 96, 118, 97, 87,
+ 110, 95, 128, 153, 147, 165, 146, 106, 101, 137,
+ 139, 96, 73, 90, 91, 51, 69, 102, 100, 103,
+ 96, 101, 123, 107, 82, 89, 118, 127, 99, 100,
+ 111, 97, 111, 123, 106, 121, 133, 103, 100, 88,
+ 85, 111, 114, 125, 102, 91, 97, 84, 139, 157,
+ 109, 66, 72, 129, 111, 90, 127, 126, 101, 109,
+ 142, 138, 129, 159, 140, 80, 74, 78, 76, 98,
+ 68, 42, 106, 143, 112, 102, 115, 114, 82, 75,
+ 92, 80, 110, 114, 66, 86, 119, 101, 101, 103,
+ 118, 145, 85, 40, 62, 88, 95, 87, 73, 64,
+ 86, 71, 71, 105, 80, 73, 96, 92, 85, 90,
+ 81, 86, 105, 100, 89, 78, 102, 114, 95, 98,
+ 69, 70, 108, 112, 111, 90, 104, 137, 143, 160,
+ 145, 121, 98, 86, 91, 87, 115, 123, 109, 99,
+ 85, 120, 131, 116, 125, 144, 153, 111, 98, 110,
+ 93, 89, 101, 137, 155, 142, 108, 94, 136, 145,
+ 129, 129, 122, 109, 90, 76, 81, 110, 119, 96,
+ 95, 102, 105, 111, 90, 89, 111, 115, 86, 51,
+ 107, 140, 105, 105, 110, 142, 125, 76, 75, 69,
+ 65, 52, 61, 69, 55, 42, 47, 58, 37, 35,
+ 24, 20, 44, 22, 16, 26, 6, 3, 4, 23,
+ 60, 51, 30, 12, 24, 31, -9, -16, -13, 13,
+ 19, 9, 37, 55, 70, 36, 23, 57, 45, 33,
+ 50, 59, 18, 11, 62, 74, 52, 8, -3, 26,
+ 51, 48, -5, -9, 12, -7, -12, -5, 28, 41,
+ -2, -30, -13, 31, 33, -12, -22, -8, -15, -17,
+ 2, -6, -25, -27, -24, -8, 4, -9, -52, -47,
+ -9, -32, -45, -5, 41, 15, -32, -14, 2, -1,
+ -10, -30, -32, -25, -21, -17, -14, 8, -4, -13,
+ 34, 18, -36, -38, -18, -19, -28, -17, -14, -16,
+ -2, -20, -27, 12, 11, -17, -33, -12, -22, -64,
+ -42, -26, -23, -22, -37, -51, -53, -30, -18, -48,
+ -69, -38, -54, -96, -72, -49, -50, -57, -41, -22,
+ -43, -64, -54, -23, -49, -69, -41, -44, -42, -49,
+ -40, -26, -54, -50, -38, -49, -70, -94, -89, -69,
+ -56, -65, -71, -47, -39, -49, -79, -91, -56, -46,
+ -62, -86, -64, -32, -47, -50, -71, -77, -65, -68,
+ -52, -51, -61, -67, -61, -81, -93, -52, -59, -62,
+ -51, -75, -76, -50, -32, -54, -68, -70, -43, 1,
+ -42, -92, -80, -41, -38, -79, -69, -49, -82, -122,
+ -93, -21, -24, -61, -70, -73, -62, -74, -69, -43,
+ -25, -15, -43, -23, -26, -69, -44, -12, 1, -51,
+ -78, -13, 3, -53, -105, -72, -24, -62, -66, -31,
+ -40, -65, -86, -64, -44, -55, -63, -61, -37, -41,
+};
+
+/* Golden audio ops mfcc output for the above wav. */
+const std::vector<float> testWavMfcc {
+ -22.67135, -0.61615, 2.07233, 0.58137, 1.01655, 0.85816, 0.46039, 0.03393, 1.16511, 0.0072,
+};
+
+arm::app::audio::DsCnnMFCC GetMFCCInstance() {
+ const int sampFreq = arm::app::audio::DsCnnMFCC::ms_defaultSamplingFreq;
+ const int frameLenMs = 40;
+ const int frameLenSamples = sampFreq * frameLenMs * 0.001;
+ const int numMfccFeats = 10;
+
+ return arm::app::audio::DsCnnMFCC(numMfccFeats, frameLenSamples);
+}
+
+template <class T>
+void TestQuntisedMFCC() {
+ const float quantScale = 1.1088106632232666;
+ const int quantOffset = 95;
+ std::vector<T> mfccOutput = GetMFCCInstance().MfccComputeQuant<T>(testWav, quantScale, quantOffset);
+
+ const long min_val = std::numeric_limits<T>::min();
+ const long max_val = std::numeric_limits<T>::max();
+
+ for (size_t i = 0; i < testWavMfcc.size(); ++i){
+ long TestWavMfcc = (std::lround((testWavMfcc[i] / quantScale) + quantOffset));
+ T quantizedTestWavMfcc = static_cast<T>(std::max(min_val, std::min(TestWavMfcc, max_val)));
+
+ REQUIRE(quantizedTestWavMfcc == Approx(mfccOutput[i]).margin(0));
+ }
+}
+template void TestQuntisedMFCC<int8_t>();
+template void TestQuntisedMFCC<uint8_t>();
+template void TestQuntisedMFCC<int16_t>();
+
+TEST_CASE("MFCC calculation test")
+{
+ hal_platform platform;
+ data_acq_module dataAcq;
+ data_psn_module dataPsn;
+ platform_timer timer;
+
+ /* Initialise the HAL and platform. */
+ hal_init(&platform, &dataAcq, &dataPsn, &timer);
+ hal_platform_init(&platform);
+
+ SECTION("FP32")
+ {
+ auto mfccOutput = GetMFCCInstance().MfccCompute(testWav);
+ REQUIRE_THAT( mfccOutput, Catch::Approx( testWavMfcc ).margin(0.0001) );
+ }
+
+ SECTION("int8_t")
+ {
+ TestQuntisedMFCC<int8_t>();
+ }
+
+ SECTION("uint8_t")
+ {
+ TestQuntisedMFCC<uint8_t>();
+ }
+
+ SECTION("MFCC quant calculation test - int16_t")
+ {
+ TestQuntisedMFCC<int16_t>();
+ }
+}
\ No newline at end of file
diff --git a/tests/use_case/kws_asr/Wav2LetterPostprocessingTest.cc b/tests/use_case/kws_asr/Wav2LetterPostprocessingTest.cc
new file mode 100644
index 0000000..6fd7df3
--- /dev/null
+++ b/tests/use_case/kws_asr/Wav2LetterPostprocessingTest.cc
@@ -0,0 +1,194 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "Wav2LetterPostprocess.hpp"
+#include "Wav2LetterModel.hpp"
+
+#include <algorithm>
+#include <catch.hpp>
+#include <limits>
+
+template <typename T>
+static TfLiteTensor GetTestTensor(std::vector <int>& shape,
+ T initVal,
+ std::vector<T>& vectorBuf)
+{
+ REQUIRE(0 != shape.size());
+
+ shape.insert(shape.begin(), shape.size());
+ uint32_t sizeInBytes = sizeof(T);
+ for (size_t i = 1; i < shape.size(); ++i) {
+ sizeInBytes *= shape[i];
+ }
+
+ /* Allocate mem. */
+ vectorBuf = std::vector<T>(sizeInBytes, initVal);
+ TfLiteIntArray* dims = tflite::testing::IntArrayFromInts(shape.data());
+ return tflite::testing::CreateQuantizedTensor(
+ vectorBuf.data(), dims,
+ 1, 0, "test-tensor");
+}
+
+TEST_CASE("Checking return value")
+{
+ SECTION("Mismatched post processing parameters and tensor size")
+ {
+ const uint32_t ctxLen = 5;
+ const uint32_t innerLen = 3;
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, 0};
+
+ std::vector <int> tensorShape = {1, 1, 1, 13};
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+ REQUIRE(false == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, false));
+ }
+
+ SECTION("Post processing succeeds")
+ {
+ const uint32_t ctxLen = 5;
+ const uint32_t innerLen = 3;
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, 0};
+
+ std::vector <int> tensorShape = {1, 1, 13, 1};
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+
+ /* Copy elements to compare later. */
+ std::vector <int8_t> originalVec = tensorVec;
+
+ /* This step should not erase anything. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, false));
+ }
+}
+
+TEST_CASE("Postprocessing - erasing required elements")
+{
+ constexpr uint32_t ctxLen = 5;
+ constexpr uint32_t innerLen = 3;
+ constexpr uint32_t nRows = 2*ctxLen + innerLen;
+ constexpr uint32_t nCols = 10;
+ constexpr uint32_t blankTokenIdx = nCols - 1;
+ std::vector <int> tensorShape = {1, 1, nRows, nCols};
+
+ SECTION("First and last iteration")
+ {
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, blankTokenIdx};
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+
+ /* Copy elements to compare later. */
+ std::vector <int8_t> originalVec = tensorVec;
+
+ /* This step should not erase anything. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, true));
+ REQUIRE(originalVec == tensorVec);
+ }
+
+ SECTION("Right context erase")
+ {
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, blankTokenIdx};
+
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+
+ /* Copy elements to compare later. */
+ std::vector <int8_t> originalVec = tensorVec;
+
+ /* This step should erase the right context only. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, false));
+ REQUIRE(originalVec != tensorVec);
+
+ /* The last ctxLen * 10 elements should be gone. */
+ for (size_t i = 0; i < ctxLen; ++i) {
+ for (size_t j = 0; j < nCols; ++j) {
+ /* Check right context elements are zeroed. */
+ if (j == blankTokenIdx) {
+ CHECK(tensorVec[(ctxLen + innerLen) * nCols + i*nCols + j] == 1);
+ } else {
+ CHECK(tensorVec[(ctxLen + innerLen) * nCols + i*nCols + j] == 0);
+ }
+
+ /* Check left context is preserved. */
+ CHECK(tensorVec[i*nCols + j] == originalVec[i*nCols + j]);
+ }
+ }
+
+ /* Check inner elements are preserved. */
+ for (size_t i = ctxLen * nCols; i < (ctxLen + innerLen) * nCols; ++i) {
+ CHECK(tensorVec[i] == originalVec[i]);
+ }
+ }
+
+ SECTION("Left and right context erase")
+ {
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, blankTokenIdx};
+
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(tensorShape, 100, tensorVec);
+
+ /* Copy elements to compare later. */
+ std::vector <int8_t> originalVec = tensorVec;
+
+ /* This step should erase right context. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, false));
+
+ /* Calling it the second time should erase the left context. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, false));
+
+ REQUIRE(originalVec != tensorVec);
+
+ /* The first and last ctxLen * 10 elements should be gone. */
+ for (size_t i = 0; i < ctxLen; ++i) {
+ for (size_t j = 0; j < nCols; ++j) {
+ /* Check left and right context elements are zeroed. */
+ if (j == blankTokenIdx) {
+ CHECK(tensorVec[(ctxLen + innerLen) * nCols + i * nCols + j] == 1);
+ CHECK(tensorVec[i * nCols + j] == 1);
+ } else {
+ CHECK(tensorVec[(ctxLen + innerLen) * nCols + i * nCols + j] == 0);
+ CHECK(tensorVec[i * nCols + j] == 0);
+ }
+ }
+ }
+
+ /* Check inner elements are preserved. */
+ for (size_t i = ctxLen * nCols; i < (ctxLen + innerLen) * nCols; ++i) {
+ /* Check left context is preserved. */
+ CHECK(tensorVec[i] == originalVec[i]);
+ }
+ }
+
+ SECTION("Try left context erase")
+ {
+ /* Should not be able to erase the left context if it is the first iteration. */
+ arm::app::audio::asr::Postprocess post{ctxLen, innerLen, blankTokenIdx};
+
+ std::vector <int8_t> tensorVec;
+ TfLiteTensor tensor = GetTestTensor<int8_t>(
+ tensorShape, 100, tensorVec);
+
+ /* Copy elements to compare later. */
+ std::vector <int8_t> originalVec = tensorVec;
+
+ /* Calling it the second time should erase the left context. */
+ REQUIRE(true == post.Invoke(&tensor, arm::app::Wav2LetterModel::ms_outputRowsIdx, true));
+ REQUIRE(originalVec == tensorVec);
+ }
+}
\ No newline at end of file
diff --git a/tests/use_case/kws_asr/Wav2LetterPreprocessingTest.cc b/tests/use_case/kws_asr/Wav2LetterPreprocessingTest.cc
new file mode 100644
index 0000000..e71366a
--- /dev/null
+++ b/tests/use_case/kws_asr/Wav2LetterPreprocessingTest.cc
@@ -0,0 +1,152 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "Wav2LetterPreprocess.hpp"
+
+#include <algorithm>
+#include <catch.hpp>
+#include <limits>
+
+constexpr uint32_t numMfccFeatures = 13;
+constexpr uint32_t numMfccVectors = 10;
+
+/* Test vector output: generated using test-asr-preprocessing.py. */
+int8_t expectedResult[numMfccVectors][numMfccFeatures*3] = {
+ /* Feature vec 0. */
+ -32, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11, /* MFCCs. */
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, /* Delta 1. */
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, /* Delta 2. */
+
+ /* Feature vec 1. */
+ -31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 2. */
+ -31, 4, -9, -9, -10, -10, -11, -11, -11, -11, -12, -12, -12,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 3. */
+ -31, 4, -9, -9, -10, -10, -11, -11, -11, -11, -11, -12, -12,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 4 : this should have valid delta 1 and delta 2. */
+ -31, 4, -9, -9, -10, -10, -11, -11, -11, -11, -11, -12, -12,
+ -38, -29, -9, 1, -2, -7, -8, -8, -12, -16, -14, -5, 5,
+ -68, -50, -13, 5, 0, -9, -9, -8, -13, -20, -19, -3, 15,
+
+ /* Feature vec 5 : this should have valid delta 1 and delta 2. */
+ -31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -11, -12, -12,
+ -62, -45, -11, 5, 0, -8, -9, -8, -12, -19, -17, -3, 13,
+ -27, -22, -13, -9, -11, -12, -12, -11, -11, -13, -13, -10, -6,
+
+ /* Feature vec 6. */
+ -31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 7. */
+ -32, 4, -9, -8, -10, -10, -11, -11, -11, -12, -12, -11, -11,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 8. */
+ -32, 4, -9, -8, -10, -10, -11, -11, -11, -12, -12, -11, -11,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
+
+ /* Feature vec 9. */
+ -31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11,
+ -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
+ -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10
+};
+
+void PopulateTestWavVector(std::vector<int16_t>& vec)
+{
+ constexpr int int16max = std::numeric_limits<int16_t>::max();
+ int val = 0;
+ for (size_t i = 0; i < vec.size(); ++i, ++val) {
+
+ /* We want a differential filter response from both - order 1
+ * and 2 => Don't have a linear signal here - we use a signal
+ * using squares for example. Alternate sign flips might work
+ * just as well and will be computationally less work! */
+ int valsq = val * val;
+ if (valsq > int16max) {
+ val = 0;
+ valsq = 0;
+ }
+ vec[i] = valsq;
+ }
+}
+
+TEST_CASE("Preprocessing calculation INT8")
+{
+ /* Initialise the HAL and platform. */
+ hal_platform platform;
+ data_acq_module data_acq;
+ data_psn_module data_psn;
+ platform_timer timer;
+ hal_init(&platform, &data_acq, &data_psn, &timer);
+ hal_platform_init(&platform);
+
+ /* Constants. */
+ const uint32_t windowLen = 512;
+ const uint32_t windowStride = 160;
+ const int dimArray[] = {3, 1, numMfccFeatures * 3, numMfccVectors};
+ const float quantScale = 0.1410219967365265;
+ const int quantOffset = -11;
+
+ /* Test wav memory. */
+ std::vector <int16_t> testWav((windowStride * numMfccVectors) +
+ (windowLen - windowStride));
+
+ /* Populate with dummy input. */
+ PopulateTestWavVector(testWav);
+
+ /* Allocate mem for tensor. */
+ std::vector<int8_t> tensorVec(dimArray[1]*dimArray[2]*dimArray[3]);
+
+ /* Initialise dimensions and the test tensor. */
+ TfLiteIntArray* dims= tflite::testing::IntArrayFromInts(dimArray);
+ TfLiteTensor tensor = tflite::testing::CreateQuantizedTensor(
+ tensorVec.data(), dims, quantScale, quantOffset, "preprocessedInput");
+
+ /* Initialise pre-processing module. */
+ arm::app::audio::asr::Preprocess prep{
+ numMfccFeatures, windowLen, windowStride, numMfccVectors};
+
+ /* Invoke pre-processing. */
+ REQUIRE(prep.Invoke(testWav.data(), testWav.size(), &tensor));
+
+ /* Wrap the tensor with a std::vector for ease. */
+ int8_t * tensorData = tflite::GetTensorData<int8_t>(&tensor);
+ std::vector <int8_t> vecResults =
+ std::vector<int8_t>(tensorData, tensorData + tensor.bytes);
+
+ /* Check sizes. */
+ REQUIRE(vecResults.size() == sizeof(expectedResult));
+
+ /* Check that the elements have been calculated correctly. */
+ for (uint32_t j = 0; j < numMfccVectors; ++j) {
+ for (uint32_t i = 0; i < numMfccFeatures * 3; ++i) {
+ size_t tensorIdx = (j * numMfccFeatures * 3) + i;
+ CHECK(vecResults[tensorIdx] == expectedResult[j][i]);
+ }
+ }
+}
diff --git a/tests/utils/ImageUtils.cc b/tests/utils/ImageUtils.cc
new file mode 100644
index 0000000..f77ce1e
--- /dev/null
+++ b/tests/utils/ImageUtils.cc
@@ -0,0 +1,37 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "ImageUtils.hpp"
+
+void convertImgIoInt8(void * data, const size_t sz)
+{
+ uint8_t * tmp_req_data = (uint8_t *)data;
+ int8_t * tmp_signed_req_data = (int8_t *) data;
+
+ for (size_t i = 0; i < sz; ++i) {
+ tmp_signed_req_data[i] = (int8_t)(
+ (int32_t)(tmp_req_data[i]) - 128);
+ }
+}
+
+void convertImgIoGreyscale(const uint8_t * srcPtr, uint8_t * dstPtr, const size_t sz)
+{
+ for (size_t i = 0; i < sz; ++i, srcPtr += 3) {
+ *dstPtr++ = 0.2989 * (*srcPtr) +
+ 0.587 * (*(srcPtr+1)) +
+ 0.114 * (*(srcPtr+2));
+ }
+}
\ No newline at end of file
diff --git a/tests/utils/ImageUtils.hpp b/tests/utils/ImageUtils.hpp
new file mode 100644
index 0000000..838dcef
--- /dev/null
+++ b/tests/utils/ImageUtils.hpp
@@ -0,0 +1,26 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef IMAGEUTILS_HPP
+#define IMAGEUTILS_HPP
+
+#include <catch.hpp>
+
+void convertImgIoInt8(void * data, const size_t sz);
+
+void convertImgIoGreyscale(const uint8_t * srcPtr, uint8_t * dstPtr, const size_t sz);
+
+#endif /* IMAGEUTILS_HPP */