examples/ is based on KasperskyLab/knp at 55470ed6 with local changes to the mnist-learn altai/blifat models, cuda-backend CMake and model_loader. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
222 lines
7.7 KiB
C++
222 lines
7.7 KiB
C++
/**
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* @file network_test.cpp
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* @brief Network class testing.
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* @kaspersky_support A. Vartenkov
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* @date 12.02.2024
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* @license Apache 2.0
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* @copyright © 2024 AO Kaspersky Lab
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <knp/framework/network.h>
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#include <knp/framework/population/creators.h>
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#include <tests_common.h>
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#include <exception>
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#include <tuple>
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using BLIFATParams = knp::neuron_traits::neuron_parameters<knp::neuron_traits::BLIFATNeuron>;
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using DeltaProjection = knp::core::Projection<knp::synapse_traits::DeltaSynapse>;
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using Synapse = DeltaProjection::Synapse;
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const auto neurons_count = 10;
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const auto synapses_count = 10;
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static auto create_entities()
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{
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knp::core::Population<knp::neuron_traits::BLIFATNeuron> population1(
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[=](size_t index) -> BLIFATParams
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{
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BLIFATParams params;
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params.potential_ = static_cast<double>(index / 2);
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return params;
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},
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neurons_count);
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DeltaProjection projection1(
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knp::core::UID{}, knp::core::UID{},
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[=](size_t index) -> std::optional<Synapse>
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{
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const uint32_t id_from = index;
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const uint32_t id_to = index;
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return Synapse{{}, id_from, id_to};
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},
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synapses_count);
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return std::make_tuple(population1, projection1);
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}
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TEST(FrameworkSuite, EmptyNetwork)
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{
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// Test default network constructor. This should create an empty network.
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knp::framework::Network network;
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// Number of projections in an empty network is zero.
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ASSERT_EQ(network.projections_count(), 0);
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// Number of populations in an empty network is zero.
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ASSERT_EQ(network.populations_count(), 0);
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// Check iterator correctness.
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ASSERT_EQ(network.begin_populations(), network.end_populations());
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ASSERT_EQ(network.begin_projections(), network.end_projections());
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}
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TEST(FrameworkSuite, NetworkCreation) //!OCLINT(False positive)
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{
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knp::framework::Network network;
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auto [population1, projection1] = create_entities();
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auto pop_uid = population1.get_uid();
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auto proj_uid = projection1.get_uid();
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network.add_population(std::move(population1));
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ASSERT_EQ(network.populations_count(), 1);
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ASSERT_EQ(network.projections_count(), 0);
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network.add_projection(std::move(projection1));
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ASSERT_EQ(network.populations_count(), 1);
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ASSERT_EQ(network.projections_count(), 1);
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ASSERT_TRUE(network.is_population_exists(pop_uid));
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ASSERT_EQ(network.get_population<knp::neuron_traits::BLIFATNeuron>(pop_uid).get_uid(), pop_uid);
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ASSERT_TRUE(network.is_projection_exists(proj_uid));
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ASSERT_EQ(network.get_projection<DeltaProjection::ProjectionSynapseType>(proj_uid).get_uid(), proj_uid);
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ASSERT_NE(network.get_projection<DeltaProjection::ProjectionSynapseType>(proj_uid).get_uid(), pop_uid);
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}
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TEST(FrameworkSuite, NetworkRemoveEntities) //!OCLINT(False positive)
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{
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knp::framework::Network network;
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auto [population1, projection1] = create_entities();
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auto [uid_pop, uid_proj] = std::make_tuple(population1.get_uid(), projection1.get_uid());
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ASSERT_EQ(network.populations_count(), 0);
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ASSERT_EQ(network.projections_count(), 0);
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network.add_population(std::move(population1));
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network.add_projection(std::move(projection1));
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ASSERT_EQ(network.populations_count(), 1);
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ASSERT_EQ(network.projections_count(), 1);
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// Incorrect UID.
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EXPECT_THROW(network.remove_population(uid_proj), std::logic_error); //!OCLINT(False positive)
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ASSERT_EQ(network.populations_count(), 1);
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// Correct UID.
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network.remove_population(uid_pop);
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ASSERT_EQ(network.populations_count(), 0);
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// Incorrect UID.
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EXPECT_THROW(network.remove_projection(uid_pop), std::logic_error); //!OCLINT(False positive)
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ASSERT_EQ(network.projections_count(), 1);
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// Correct UID.
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network.remove_projection(uid_proj);
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ASSERT_EQ(network.projections_count(), 0);
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}
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TEST(FrameworkSuite, NetworkConnectPopulations)
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{
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constexpr auto src_neurons_count = 5;
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constexpr auto dst_neurons_count = 3;
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auto src_pop{knp::framework::population::creators::make_random<typename knp::neuron_traits::BLIFATNeuron>(
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src_neurons_count)};
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auto dst_pop{knp::framework::population::creators::make_random<typename knp::neuron_traits::BLIFATNeuron>(
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dst_neurons_count)};
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knp::framework::Network network;
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knp::core::UID proj_uid;
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auto connector = [&]()
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{
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proj_uid = network.connect_populations<
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typename knp::synapse_traits::DeltaSynapse, knp::neuron_traits::BLIFATNeuron,
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knp::neuron_traits::BLIFATNeuron>(src_pop, dst_pop);
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SPDLOG_DEBUG("New projection UID = {}.", std::string(proj_uid));
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};
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EXPECT_THROW(connector(), std::logic_error); //!OCLINT(False positive)
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network.add_population(src_pop);
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EXPECT_THROW(connector(), std::logic_error); //!OCLINT(False positive)
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SPDLOG_DEBUG("Checking projection UID = {} [False?]", std::string(proj_uid));
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ASSERT_FALSE(network.is_projection_exists(proj_uid));
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network.add_population(dst_pop);
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EXPECT_NO_THROW(connector()); //!OCLINT(False positive)
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ASSERT_EQ(network.projections_count(), 1);
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ASSERT_EQ(network.populations_count(), 2);
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SPDLOG_DEBUG("Checking projection UID = {} [True?]", std::string(proj_uid));
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ASSERT_TRUE(network.is_projection_exists(proj_uid));
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ASSERT_EQ(
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network.get_projection<knp::synapse_traits::DeltaSynapse>(proj_uid).size(),
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src_neurons_count * dst_neurons_count);
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}
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TEST(FrameworkSuite, NetworkConnectPopulationsArbitrary)
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{
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constexpr auto src_neurons_count = 5;
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constexpr auto dst_neurons_count = 3;
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auto src_pop{
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knp::framework::population::creators::make_random<knp::neuron_traits::BLIFATNeuron>(src_neurons_count)};
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auto dst_pop{
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knp::framework::population::creators::make_random<knp::neuron_traits::BLIFATNeuron>(dst_neurons_count)};
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knp::framework::Network network;
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knp::core::UID proj_uid;
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auto connector = [&]()
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{
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proj_uid = network.connect_populations<
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knp::synapse_traits::DeltaSynapse, knp::neuron_traits::BLIFATNeuron, knp::neuron_traits::BLIFATNeuron>(
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src_pop, dst_pop,
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[dst_neurons_count](size_t index)
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{
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return std::make_tuple(
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knp::core::Projection<knp::synapse_traits::DeltaSynapse>::SynapseParameters(), index,
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index % dst_neurons_count);
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},
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src_neurons_count);
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SPDLOG_DEBUG("New projection UID = {}.", std::string(proj_uid));
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};
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EXPECT_THROW(connector(), std::logic_error); //!OCLINT(False positive)
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network.add_population(src_pop);
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EXPECT_THROW(connector(), std::logic_error); //!OCLINT(False positive)
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ASSERT_FALSE(network.is_projection_exists(proj_uid));
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network.add_population(dst_pop);
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EXPECT_NO_THROW(connector()); //!OCLINT(False positive)
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ASSERT_EQ(network.projections_count(), 1);
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ASSERT_EQ(network.populations_count(), 2);
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SPDLOG_DEBUG("Checking projection UID = {} [True?]", std::string(proj_uid));
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ASSERT_TRUE(network.is_projection_exists(proj_uid));
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ASSERT_EQ(network.get_projection<knp::synapse_traits::DeltaSynapse>(proj_uid).size(), src_neurons_count);
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}
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