blob: 82bffc66ad09afd44811d7d7ce5bcab5f0e2891c [file] [log] [blame]
/*
* 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 "ImageUtils.hpp"
#include "TensorFlowLiteMicro.hpp"
#include "TestData_vww.hpp"
#include "VisualWakeWordModel.hpp"
#include <catch.hpp>
bool RunInference(arm::app::Model& model, const int8_t* imageData)
{
TfLiteTensor* inputTensor = model.GetInputTensor(0);
REQUIRE(inputTensor);
const size_t copySz =
inputTensor->bytes < IFM_0_DATA_SIZE ? inputTensor->bytes : IFM_0_DATA_SIZE;
memcpy(inputTensor->data.data, imageData, copySz);
if (model.IsDataSigned()) {
arm::app::image::ConvertImgToInt8(inputTensor->data.data, copySz);
}
return model.RunInference();
}
template <typename T>
void TestInference(int imageIdx, arm::app::Model& model)
{
auto image = test::GetIfmDataArray(imageIdx);
auto goldenFV = test::GetOfmDataArray(imageIdx);
REQUIRE(RunInference(model, image));
TfLiteTensor* outputTensor = model.GetOutputTensor(0);
REQUIRE(outputTensor);
REQUIRE(outputTensor->bytes == OFM_0_DATA_SIZE);
auto tensorData = tflite::GetTensorData<T>(outputTensor);
REQUIRE(tensorData);
for (size_t i = 0; i < outputTensor->bytes; i++) {
auto testVal = static_cast<int>(tensorData[i]);
auto goldenVal = static_cast<int>(goldenFV[i]);
CHECK(testVal == goldenVal);
}
}