| /* |
| * 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 "Wav2LetterPreprocess.hpp" |
| |
| #include "log_macros.h" |
| |
| #include <catch.hpp> |
| #include <random> |
| |
| class TestPreprocess : public arm::app::audio::asr::Preprocess { |
| public: |
| |
| static bool ComputeDeltas(arm::app::Array2d<float>& mfcc, |
| arm::app::Array2d<float>& delta1, |
| arm::app::Array2d<float>& delta2) |
| { |
| return Preprocess::ComputeDeltas(mfcc, delta1, delta2); |
| } |
| |
| static float GetMean(arm::app::Array2d<float>& vec) |
| { |
| return Preprocess::GetMean(vec); |
| } |
| |
| static float GetStdDev(arm::app::Array2d<float>& vec, const float mean) |
| { |
| return Preprocess::GetStdDev(vec, mean); |
| } |
| |
| static void NormaliseVec(arm::app::Array2d<float>& vec) |
| { |
| return Preprocess::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]") |
| { |
| |
| 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); |
| |
| TestPreprocess::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(TestPreprocess::GetMean(mean1))); |
| |
| arm::app::Array2d<float> mean2(2, 2); |
| std::fill(mean2.begin(), mean2.end(), 0.f); |
| REQUIRE(0 == Approx(TestPreprocess::GetMean(mean2))); |
| |
| arm::app::Array2d<float> mean3(3,3); |
| std::fill(mean3.begin(), mean3.end(), 1.f); |
| REQUIRE(1 == Approx(TestPreprocess::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(TestPreprocess::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 = TestPreprocess::GetMean(std2); |
| REQUIRE(2.872281323 == Approx(TestPreprocess::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(TestPreprocess::GetStdDev(std3, 1))); |
| } |
| |
| SECTION("Norm") { |
| auto checker = [&](arm::app::Array2d<float>& d, std::vector<float>& g) { |
| TestPreprocess::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); |
| } |
| } |