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/*
* SPDX-FileCopyrightText: Copyright 2021-2022 Arm Limited and/or its affiliates <open-source-office@arm.com>
* 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 "MicroNetKwsModel.hpp"
#include "hal.h"
#include "KwsResult.hpp"
#include "Labels.hpp"
#include "UseCaseHandler.hpp"
#include "Classifier.hpp"
#include "UseCaseCommonUtils.hpp"
#include "BufAttributes.hpp"
namespace arm {
namespace app {
static uint8_t tensorArena[ACTIVATION_BUF_SZ] ACTIVATION_BUF_ATTRIBUTE;
namespace kws {
extern uint8_t* GetModelPointer();
extern size_t GetModelLen();
} /* namespace kws */
} /* namespace app */
} /* namespace arm */
TEST_CASE("Model info")
{
/* Model wrapper object. */
arm::app::MicroNetKwsModel model;
/* Load the model. */
REQUIRE(model.Init(arm::app::tensorArena,
sizeof(arm::app::tensorArena),
arm::app::kws::GetModelPointer(),
arm::app::kws::GetModelLen()));
/* Instantiate application context. */
arm::app::ApplicationContext caseContext;
caseContext.Set<arm::app::Model&>("model", model);
REQUIRE(model.ShowModelInfoHandler());
}
TEST_CASE("Inference by index")
{
/* Initialise the HAL and platform. */
hal_platform_init();
/* Model wrapper object. */
arm::app::MicroNetKwsModel model;
/* Load the model. */
REQUIRE(model.Init(arm::app::tensorArena,
sizeof(arm::app::tensorArena),
arm::app::kws::GetModelPointer(),
arm::app::kws::GetModelLen()));
/* Instantiate application context. */
arm::app::ApplicationContext caseContext;
arm::app::Profiler profiler{"kws"};
caseContext.Set<arm::app::Profiler&>("profiler", profiler);
caseContext.Set<arm::app::Model&>("model", model);
caseContext.Set<int>("frameLength", arm::app::kws::g_FrameLength); /* 640 sample length for MicroNetKws. */
caseContext.Set<int>("frameStride", arm::app::kws::g_FrameStride); /* 320 sample stride for MicroNetKws. */
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>("clipIndex", 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, {0});
}
SECTION("Index = 1, long clip right->left->up")
{
/* Result: right->right->left->up->up. */
checker(1, {6, 6, 2, 8, 8});
}
SECTION("Index = 2, short clip yes")
{
/* Result: yes. */
checker(2, {9});
}
SECTION("Index = 3, long clip yes->no->go->stop")
{
/* Result: yes->no->no->go->go->stop->stop. */
checker(3, {9, 3, 3, 1, 1, 7, 7});
}
}
TEST_CASE("Inference run all clips")
{
/* Initialise the HAL and platform. */
hal_platform_init();
/* Model wrapper object. */
arm::app::MicroNetKwsModel model;
/* Load the model. */
REQUIRE(model.Init(arm::app::tensorArena,
sizeof(arm::app::tensorArena),
arm::app::kws::GetModelPointer(),
arm::app::kws::GetModelLen()));
/* Instantiate application context. */
arm::app::ApplicationContext caseContext;
arm::app::Profiler profiler{"kws"};
caseContext.Set<arm::app::Profiler&>("profiler", profiler);
caseContext.Set<arm::app::Model&>("model", model);
caseContext.Set<uint32_t>("clipIndex", 0);
caseContext.Set<int>("frameLength", arm::app::kws::g_FrameLength); /* 640 sample length for MicroNet. */
caseContext.Set<int>("frameStride", arm::app::kws::g_FrameStride); /* 320 sample stride for MicroNet. */
caseContext.Set<float>("scoreThreshold", 0.7); /* 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")
{
/* Initialise the HAL and platform. */
hal_platform_init();
/* Model wrapper object. */
arm::app::MicroNetKwsModel model;
/* Load the model. */
REQUIRE(model.Init(arm::app::tensorArena,
sizeof(arm::app::tensorArena),
arm::app::kws::GetModelPointer(),
arm::app::kws::GetModelLen()));
/* Instantiate application context. */
arm::app::ApplicationContext caseContext;
caseContext.Set<arm::app::Model&>("model", model);
REQUIRE(arm::app::ListFilesHandler(caseContext));
}
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