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Jerome Hue authoredJerome Hue authored
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Test_HeavisideImpl.cpp 3.19 KiB
/********************************************************************************
* Copyright (c) 2025 CEA-List
*
* This program and the accompanying materials are made available under the
* terms of the Eclipse Public License 2.0 which is available at
* http://www.eclipse.org/legal/epl-2.0.
*
* SPDX-License-Identifier: EPL-2.0
*
********************************************************************************/
#include "aidge/backend/cpu/operator/HeavisideImpl_kernels.hpp"
#include <memory>
#include <cstdlib>
#include <random>
#include <catch2/catch_test_macros.hpp>
#include "aidge/data/Tensor.hpp"
#include "aidge/backend/cpu/operator/HeavisideImpl.hpp"
#include "aidge/graph/Node.hpp"
#include "aidge/utils/TensorUtils.hpp"
namespace Aidge
{
TEST_CASE("[cpu/operator] Heaviside(forward)", "[Heaviside][CPU]") {
std::random_device rd;
std::mt19937 gen(rd());
std::uniform_real_distribution<float> valueDist(-1.0f, 1.0f);
std::uniform_int_distribution<std::size_t> dimSizeDist(std::size_t(2), std::size_t(10));
std::uniform_int_distribution<std::size_t> nbDimsDist(std::size_t(1), std::size_t(5));
SECTION("1D Tensor") {
std::shared_ptr<Tensor> input0 = std::make_shared<Tensor>(Array1D<float,10> {
{0, 1, 2,-3, 4,-5,-6, 7, 8, 9}
});
std::shared_ptr<Tensor> expectedOutput = std::make_shared<Tensor>(Array1D<float,10> {
{0.5, 1, 1, 0, 1, 0, 0, 1, 1, 1}
});
std::shared_ptr<Node> heaviside = Heaviside(0.5);
auto op = std::static_pointer_cast<OperatorTensor>(heaviside->getOperator());
op->associateInput(0, input0);
op->setBackend("cpu");
op->setDataType(DataType::Float32);
op->forward();
REQUIRE(approxEq<float>(*op->getOutput(0),*expectedOutput));
}
SECTION("+1-D Tensor")
{
auto dims = std::vector<std::size_t>();
auto nbDims = nbDimsDist(gen);
for (auto i = 0u; i < nbDims; ++i) {
dims.push_back(dimSizeDist(gen));
}
auto numberOfElements = std::accumulate(dims.cbegin(), dims.cend(), std::size_t(1), std::multiplies<std::size_t>());
float* inputArray = new float[numberOfElements];
float* resultArray = new float[numberOfElements];
for(auto i = 0u; i < numberOfElements; ++i)
{
inputArray[i] = valueDist(gen);
resultArray[i] = inputArray[i] > 0 ? 1 : (inputArray[i] == 0 ? 0.5 : 0);
}
auto T0 = std::make_shared<Tensor>();
T0->setDataType(DataType::Float32);
T0->setBackend("cpu");
auto T1 = std::make_shared<Tensor>();
T1->setDataType(DataType::Float32);
T1->setBackend("cpu");
T0->resize(dims);
T0->getImpl()->setRawPtr(inputArray, numberOfElements);
T1->resize(dims);
T1->getImpl()->setRawPtr(resultArray, numberOfElements);
std::shared_ptr<Node> heaviside = Heaviside(0.5);
auto op = std::static_pointer_cast<OperatorTensor>(heaviside->getOperator());
op->associateInput(0, T0);
op->setBackend("cpu");
op->setDataType(DataType::Float32);
op->forward();
REQUIRE(approxEq<float>(*(op->getOutput(0)), *T1));
}
}
}