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Commit 948d024b authored by Jerome Hue's avatar Jerome Hue Committed by Olivier BICHLER
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1 merge request!131CHORE: Add tests for Leaky MetaOperator
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include/aidge/backend/cpu.hpp
+ 0
− 1
View file @ 948d024b
......@@ -36,7 +36,6 @@
#include "aidge/backend/cpu/operator/GlobalAveragePoolingImpl.hpp"
#include "aidge/backend/cpu/operator/HeavisideImpl.hpp"
#include "aidge/backend/cpu/operator/LRNImpl.hpp"
#include "aidge/backend/cpu/operator/HeavisideImpl.hpp"
#include "aidge/backend/cpu/operator/LeakyReLUImpl.hpp"
#include "aidge/backend/cpu/operator/LnImpl.hpp"
#include "aidge/backend/cpu/operator/MatMulImpl.hpp"
......
unit_tests/operator/Test_MetaOperator.cpp
+ 107
− 59
View file @ 948d024b
......@@ -17,9 +17,10 @@
#include <memory>
#include <random>
#include "aidge/backend/cpu/operator/ConvImpl.hpp"
#include "aidge/backend/cpu/operator/ConvImpl.hpp"
#include "aidge/backend/cpu/operator/PadImpl.hpp"
#include "aidge/data/Tensor.hpp"
#include "aidge/filler/Filler.hpp"
#include "aidge/operator/Conv.hpp"
#include "aidge/operator/FC.hpp"
#include "aidge/operator/Identity.hpp"
......@@ -31,7 +32,6 @@
#include "aidge/scheduler/ParallelScheduler.hpp"
#include "aidge/scheduler/SequentialScheduler.hpp"
#include "aidge/utils/TensorUtils.hpp"
#include "aidge/filler/Filler.hpp"
using namespace Aidge;
......@@ -599,80 +599,125 @@ TEST_CASE("[cpu/operator] MetaOperator", "[MetaOperator][CPU]") {
}
SECTION("Leaky(forward)(fixed)") {
constexpr auto inChannels = 10;
constexpr auto outChannels = 5;
constexpr auto beta = 0.95;
constexpr auto threshold = 1.0;
constexpr auto threshold = 1.0;
constexpr auto nbTimeSteps = 2;
auto myWeights = std::make_shared<Tensor>(Array2D<float, outChannels, inChannels>{{
{0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0},
{1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1},
{0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 0.1, 0.2, 0.3, 0.4},
{0.4, 0.3, 0.2, 0.1, 0.0, 0.1, 0.2, 0.3, 0.4, 0.5},
{0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0},
}});
auto myWeights2 = std::make_shared<Tensor>(Array2D<float, inChannels, outChannels>{{
{0.1, 0.2, 0.3, 0.4, 0.5},
{0.6, 0.7, 0.8, 0.9, 1.0},
{1.0, 0.9, 0.8, 0.7, 0.6},
{0.5, 0.4, 0.3, 0.2, 0.1},
{0.5, 0.6, 0.7, 0.8, 0.9},
{1.0, 0.1, 0.2, 0.3, 0.4},
{0.4, 0.3, 0.2, 0.1, 0.0},
{0.1, 0.2, 0.3, 0.4, 0.5},
{0.9, 0.8, 0.7, 0.6, 0.5},
{0.4, 0.3, 0.2, 0.1, 0.0},
}});
auto myInput = std::make_shared<Tensor>(Array2D<float, 2, 10>{{
auto myWeights =
std::make_shared<Tensor>(Array2D<float, outChannels, inChannels>{{
{0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0},
{1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1},
{0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 0.1, 0.2, 0.3, 0.4},
{0.4, 0.3, 0.2, 0.1, 0.0, 0.1, 0.2, 0.3, 0.4, 0.5},
{0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0},
}});
auto myWeights2 =
std::make_shared<Tensor>(Array2D<float, inChannels, outChannels>{{
{0.1, 0.2, 0.3, 0.4, 0.5},
{0.6, 0.7, 0.8, 0.9, 1.0},
{1.0, 0.9, 0.8, 0.7, 0.6},
{0.5, 0.4, 0.3, 0.2, 0.1},
{0.5, 0.6, 0.7, 0.8, 0.9},
{1.0, 0.1, 0.2, 0.3, 0.4},
{0.4, 0.3, 0.2, 0.1, 0.0},
{0.1, 0.2, 0.3, 0.4, 0.5},
{0.9, 0.8, 0.7, 0.6, 0.5},
{0.4, 0.3, 0.2, 0.1, 0.0},
}});
auto myInput = std::make_shared<Tensor>(Array2D<float, 2, 10>{{
{0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0},
{1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1},
}});
// py/snn Torch computed result, output of fc1 at time step 1
auto expectedOutputlif1ts1 = std::make_shared<Tensor>(Array2D<float,2,5>{{
{3.850, 2.2000, 2.6500, 1.5000, 1.6500},
{2.200, 3.8500, 3.4000, 1.2500, 3.3000},
}});
auto expectedOutputfc2ts1 = std::make_shared<Tensor>(Array2D<float,2,10>{{
{1.5000, 4.0000, 4.0000, 1.5000, 3.5000, 2.0000, 1.0000, 1.5000, 3.5000, 1.0000},
{1.5000, 4.0000, 4.0000, 1.5000, 3.5000, 2.0000, 1.0000, 1.5000, 3.5000, 1.0000},
}});
auto expectedOutputlif1ts2 = std::make_shared<Tensor>(Array2D<float,2,5>{{
{6.5075, 3.2900, 4.1675, 1.9250, 2.2175},
{3.2900, 6.5075, 5.6300, 1.4375, 5.4350},
}});
// NOTE: Same output as before, because for all channels, we have a potential higher than threshold.
// Thus the lif neuron fires at every timestep for every channel.
auto expectedOutputfc2ts2 = std::make_shared<Tensor>(Array2D<float,2,10>{{
{1.5000, 4.0000, 4.0000, 1.5000, 3.5000, 2.0000, 1.0000, 1.5000, 3.5000, 1.0000},
{1.5000, 4.0000, 4.0000, 1.5000, 3.5000, 2.0000, 1.0000, 1.5000, 3.5000, 1.0000},
}});
auto expectedOutputlif1ts1 =
std::make_shared<Tensor>(Array2D<float, 2, 5>{{
{3.850, 2.2000, 2.6500, 1.5000, 1.6500},
{2.200, 3.8500, 3.4000, 1.2500, 3.3000},
}});
auto expectedOutputfc2ts1 =
std::make_shared<Tensor>(Array2D<float, 2, 10>{{
{1.5000,
4.0000,
4.0000,
1.5000,
3.5000,
2.0000,
1.0000,
1.5000,
3.5000,
1.0000},
{1.5000,
4.0000,
4.0000,
1.5000,
3.5000,
2.0000,
1.0000,
1.5000,
3.5000,
1.0000},
}});
auto expectedOutputlif1ts2 =
std::make_shared<Tensor>(Array2D<float, 2, 5>{{
{6.5075, 3.2900, 4.1675, 1.9250, 2.2175},
{3.2900, 6.5075, 5.6300, 1.4375, 5.4350},
}});
// NOTE: Same output as before, because for all channels, we have a
// potential higher than threshold. Thus the lif neuron fires at every
// timestep for every channel.
auto expectedOutputfc2ts2 =
std::make_shared<Tensor>(Array2D<float, 2, 10>{{
{1.5000,
4.0000,
4.0000,
1.5000,
3.5000,
2.0000,
1.0000,
1.5000,
3.5000,
1.0000},
{1.5000,
4.0000,
4.0000,
1.5000,
3.5000,
2.0000,
1.0000,
1.5000,
3.5000,
1.0000},
}});
auto init = std::make_shared<Tensor>(Array2D<float, 2, 5>{});
uniformFiller<float>(init, 0.0, 0.0);
auto fc1 = FC(inChannels, outChannels, true, "myfc");
auto fc2 = FC(outChannels, inChannels, true, "fc2");
// NOTE: Account for init step by adding 1 to the max timestep parameter.
auto lif1 = Leaky(nbTimeSteps+1, beta, threshold, "leaky");
// NOTE: Account for init step by adding 1 to the max timestep
// parameter.
auto lif1 = Leaky(nbTimeSteps + 1, beta, threshold, "leaky");
// associateInput() does not work
fc1->input(1).first->getOperator()->setOutput(0, myWeights);
fc2->input(1).first->getOperator()->setOutput(0, myWeights2);
auto fc1Op = std::static_pointer_cast<OperatorTensor>(fc1->getOperator());
auto lif1Op = std::static_pointer_cast<MetaOperator_Op>(lif1->getOperator());
auto fc2Op = std::static_pointer_cast<OperatorTensor>(fc2->getOperator());
auto fc1Op =
std::static_pointer_cast<OperatorTensor>(fc1->getOperator());
auto lif1Op =
std::static_pointer_cast<MetaOperator_Op>(lif1->getOperator());
auto fc2Op =
std::static_pointer_cast<OperatorTensor>(fc2->getOperator());
fc1Op->associateInput(0, myInput);
lif1Op->associateInput(1, init);
......@@ -681,7 +726,6 @@ TEST_CASE("[cpu/operator] MetaOperator", "[MetaOperator][CPU]") {
fc1->addChild(lif1, 0, 0);
lif1->addChild(fc2, 1, 0);
auto g = std::make_shared<GraphView>();
g->add({fc1, lif1, fc2});
g->compile("cpu", DataType::Float32);
......@@ -689,13 +733,17 @@ TEST_CASE("[cpu/operator] MetaOperator", "[MetaOperator][CPU]") {
// Forward 1 (simulate timestep 0)
scheduler.forward(true);
REQUIRE(approxEq<float>(*(lif1Op->getOutput(0)), *(expectedOutputlif1ts1)));
REQUIRE(approxEq<float>(*(fc2Op->getOutput(0)), *(expectedOutputfc2ts1)));
REQUIRE(approxEq<float>(*(lif1Op->getOutput(0)),
*(expectedOutputlif1ts1)));
REQUIRE(
approxEq<float>(*(fc2Op->getOutput(0)), *(expectedOutputfc2ts1)));
// Forward 1 (simulate timestep 1)
scheduler.forward(true);
REQUIRE(approxEq<float>(*(lif1Op->getOutput(0)), *(expectedOutputlif1ts2)));
REQUIRE(approxEq<float>(*(fc2Op->getOutput(0)), *(expectedOutputfc2ts2)));
REQUIRE(approxEq<float>(*(lif1Op->getOutput(0)),
*(expectedOutputlif1ts2)));
REQUIRE(
approxEq<float>(*(fc2Op->getOutput(0)), *(expectedOutputfc2ts2)));
}
SECTION("Leaky(forward)") {
......
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