Opensource ML embedded evaluation kit
Change-Id: I12e807f19f5cacad7cef82572b6dd48252fd61fd
diff --git a/tests/use_case/asr/AsrClassifierTests.cc b/tests/use_case/asr/AsrClassifierTests.cc
new file mode 100644
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+++ b/tests/use_case/asr/AsrClassifierTests.cc
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+/*
+ * 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);
+}