8f43927575
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>
102 lines
3.8 KiB
C++
102 lines
3.8 KiB
C++
/**
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* @file model_test.cpp
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* @brief Model class testing.
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* @kaspersky_support Artiom N.
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* @date 22.10.2023
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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/model.h>
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#include <knp/framework/population/creators.h>
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#include <knp/framework/projection/connectors.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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TEST(FrameworkSuite, ModelAddInputChannels)
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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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network.add_population(src_pop);
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network.add_population(dst_pop);
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knp::framework::Model model(std::move(network));
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auto new_proj = knp::framework::projection::connect_populations<
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knp::synapse_traits::DeltaSynapse, decltype(src_pop)::PopulationNeuronType,
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decltype(dst_pop)::PopulationNeuronType>(src_pop, dst_pop);
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SPDLOG_DEBUG(
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"Presynaptic population UID = {}, postsynaptic population UID = {}, projection UID = {}.",
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std::string(src_pop.get_uid()), std::string(dst_pop.get_uid()), std::string(new_proj.get_uid()));
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EXPECT_THROW(
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model.connect_input_projection(knp::core::UID(), new_proj), std::logic_error); //!OCLINT(False positive)
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EXPECT_THROW(
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model.add_input_channel(knp::core::UID(), new_proj.get_uid()), std::logic_error); //!OCLINT(False positive)
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model.get_network().add_projection(new_proj);
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EXPECT_NO_THROW(model.connect_input_projection(knp::core::UID(), new_proj)); //!OCLINT(False positive)
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ASSERT_EQ(model.get_input_channels().size(), 1);
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EXPECT_NO_THROW(model.add_input_channel(knp::core::UID(), new_proj.get_uid())); //!OCLINT(False positive)
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ASSERT_EQ(model.get_input_channels().size(), 2);
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}
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TEST(FrameworkSuite, ModelAddOutputChannels) //!OCLINT(False positive)
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{
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constexpr auto dst_neurons_count = 3;
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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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const auto pop_uid = dst_pop.get_uid();
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knp::framework::Model model(std::move(network));
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SPDLOG_DEBUG("Output population UID = {}.", std::string(pop_uid));
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EXPECT_THROW(
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model.connect_output_population(knp::core::UID(), dst_pop), std::logic_error); //!OCLINT(False positive)
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EXPECT_THROW(
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model.add_output_channel(knp::core::UID(), dst_pop.get_uid()), std::logic_error); //!OCLINT(False positive)
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model.get_network().add_population(dst_pop);
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EXPECT_NO_THROW(model.connect_output_population(knp::core::UID(), dst_pop)); //!OCLINT(False positive)
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ASSERT_EQ(model.get_output_channels().size(), 1);
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EXPECT_NO_THROW(model.add_output_channel(knp::core::UID(), pop_uid)); //!OCLINT(False positive)
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ASSERT_EQ(model.get_output_channels().size(), 2);
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}
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