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>
75 lines
3 KiB
C++
75 lines
3 KiB
C++
/**
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* @file network_functions.h
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* @brief BLIFAT specific network functions.
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* @kaspersky_support D. Postnikov
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* @date 03.02.2026
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* @license Apache 2.0
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* @copyright © 2026 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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#pragma once
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#include <memory>
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// cppcheck-suppress missingInclude
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#include "dataset.h"
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// cppcheck-suppress missingInclude
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#include "models/network_functions.h"
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/**
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* @brief Specialized network construction function for BLIFAT neuron model.
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*
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* @details This template specialization creates the complete network architecture specifically designed for the BLIFAT
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* neuron model. It constructs populations, synapses, and connections tailored to the BLIFAT neuron's unique properties
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* and requirements.
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*
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* @param model_desc model description containing configuration parameters.
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*
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* @return `AnnotatedNetwork` containing the fully constructed BLIFAT network.
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*/
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template <>
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AnnotatedNetwork construct_network<knp::neuron_traits::BLIFATNeuron>(const ModelDescription& model_desc);
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/**
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* @brief Specialized network preparation function for inference with BLIFAT neuron model.
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*
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* @details This template specialization prepares a trained BLIFAT network for inference operations. It configures the
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* network state, sets up necessary annotations, and ensures proper execution for testing and validation phases.
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*
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* @param backend shared pointer to the computational backend for inference execution.
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* @param model_desc model description containing configuration parameters and paths.
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* @param network annotated network structure to prepare for inference.
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*/
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template <>
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void prepare_network_for_inference<knp::neuron_traits::BLIFATNeuron>(
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const std::shared_ptr<knp::core::Backend>& backend, const ModelDescription& model_desc, AnnotatedNetwork& network);
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/**
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* @brief Specialized training labels spike generator for BLIFAT neuron model.
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*
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* @details This template specialization creates a spike generator specifically designed for generating label spikes during
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* training with the BLIFAT neuron model. It converts label information from the dataset into appropriate spike patterns
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* for supervised learning.
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*
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* @param dataset dataset containing training labels and configuration.
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*
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* @return callable function that generates spike data for training labels.
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*/
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template <>
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std::function<knp::core::messaging::SpikeData(knp::core::Step)>
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make_training_labels_spikes_generator<knp::neuron_traits::BLIFATNeuron>(const Dataset& dataset);
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