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author | Isabella Gottardi <isabella.gottardi@arm.com> | 2021-04-07 17:15:31 +0100 |
---|---|---|
committer | Alexander Efremov <alexander.efremov@arm.com> | 2021-04-12 14:00:49 +0000 |
commit | 8df12f37531d57a10cba2f8b2e8b6a9065202dd5 (patch) | |
tree | ba833d15649c3b0f885d57b40d3916970b3fd2c8 /source/use_case/kws | |
parent | 37ce22ebc9cf3e8529d9914c0eed0f718243d961 (diff) | |
download | ml-embedded-evaluation-kit-8df12f37531d57a10cba2f8b2e8b6a9065202dd5.tar.gz |
MLECO-1870: Cherry pick profiling changes from dev to open source repo
* Documentation update
Change-Id: If85e7ebc44498840b291c408f14e66a5a5faa424
Signed-off-by: Isabella Gottardi <isabella.gottardi@arm.com>
Diffstat (limited to 'source/use_case/kws')
-rw-r--r-- | source/use_case/kws/src/MainLoop.cc | 3 | ||||
-rw-r--r-- | source/use_case/kws/src/UseCaseHandler.cc | 30 |
2 files changed, 24 insertions, 9 deletions
diff --git a/source/use_case/kws/src/MainLoop.cc b/source/use_case/kws/src/MainLoop.cc index 24cb939..f971c30 100644 --- a/source/use_case/kws/src/MainLoop.cc +++ b/source/use_case/kws/src/MainLoop.cc @@ -58,6 +58,9 @@ void main_loop(hal_platform& platform) /* Instantiate application context. */ arm::app::ApplicationContext caseContext; + arm::app::Profiler profiler{&platform, "kws"}; + caseContext.Set<arm::app::Profiler&>("profiler", profiler); + caseContext.Set<hal_platform&>("platform", platform); caseContext.Set<arm::app::Model&>("model", model); caseContext.Set<uint32_t>("clipIndex", 0); diff --git a/source/use_case/kws/src/UseCaseHandler.cc b/source/use_case/kws/src/UseCaseHandler.cc index 872d323..d2cba55 100644 --- a/source/use_case/kws/src/UseCaseHandler.cc +++ b/source/use_case/kws/src/UseCaseHandler.cc @@ -82,6 +82,7 @@ namespace app { bool ClassifyAudioHandler(ApplicationContext& ctx, uint32_t clipIndex, bool runAll) { auto& platform = ctx.Get<hal_platform&>("platform"); + auto& profiler = ctx.Get<Profiler&>("profiler"); constexpr uint32_t dataPsnTxtInfStartX = 20; constexpr uint32_t dataPsnTxtInfStartY = 40; @@ -215,7 +216,7 @@ namespace app { audioDataSlider.TotalStrides() + 1); /* Run inference over this audio clip sliding window. */ - arm::app::RunInference(platform, model); + arm::app::RunInference(model, profiler); std::vector<ClassificationResult> classificationResult; auto& classifier = ctx.Get<KwsClassifier&>("classifier"); @@ -243,6 +244,8 @@ namespace app { return false; } + profiler.PrintProfilingResult(); + _IncrementAppCtxClipIdx(ctx); } while (runAll && ctx.Get<uint32_t>("clipIndex") != startClipIdx); @@ -281,6 +284,8 @@ namespace app { constexpr uint32_t dataPsnTxtYIncr = 16; /* Row index increment. */ platform.data_psn->set_text_color(COLOR_GREEN); + info("Final results:\n"); + info("Total number of inferences: %zu\n", results.size()); /* Display each result */ uint32_t rowIdx1 = dataPsnTxtStartY1 + 2 * dataPsnTxtYIncr; @@ -290,7 +295,7 @@ namespace app { std::string topKeyword{"<none>"}; float score = 0.f; - if (results[i].m_resultVec.size()) { + if (!results[i].m_resultVec.empty()) { topKeyword = results[i].m_resultVec[0].m_label; score = results[i].m_resultVec[0].m_normalisedVal; } @@ -305,13 +310,20 @@ namespace app { dataPsnTxtStartX1, rowIdx1, false); rowIdx1 += dataPsnTxtYIncr; - info("For timestamp: %f (inference #: %u); threshold: %f\n", - results[i].m_timeStamp, results[i].m_inferenceNumber, - results[i].m_threshold); - for (uint32_t j = 0; j < results[i].m_resultVec.size(); ++j) { - info("\t\tlabel @ %u: %s, score: %f\n", j, - results[i].m_resultVec[j].m_label.c_str(), - results[i].m_resultVec[j].m_normalisedVal); + if (results[i].m_resultVec.empty()) { + info("For timestamp: %f (inference #: %u); label: %s; threshold: %f\n", + results[i].m_timeStamp, results[i].m_inferenceNumber, + topKeyword.c_str(), + results[i].m_threshold); + } else { + for (uint32_t j = 0; j < results[i].m_resultVec.size(); ++j) { + info("For timestamp: %f (inference #: %u); label: %s, score: %f; threshold: %f\n", + results[i].m_timeStamp, + results[i].m_inferenceNumber, + results[i].m_resultVec[j].m_label.c_str(), + results[i].m_resultVec[j].m_normalisedVal, + results[i].m_threshold); + } } } |