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Програмування","\u002Fcsharp\u002Fsystem-programming-windows\u002Fasync-fundamentals","01.csharp\u002F07.system-programming-windows\u002F12.async-fundamentals",{"title":344,"path":345,"stem":346},"SynchronizationContext та ConfigureAwait — Контекст Виконання","\u002Fcsharp\u002Fsystem-programming-windows\u002Fasync-context-configureawait","01.csharp\u002F07.system-programming-windows\u002F13.async-context-configureawait",{"title":348,"path":349,"stem":350},"Async — Просунуті Паттерни","\u002Fcsharp\u002Fsystem-programming-windows\u002Fasync-advanced","01.csharp\u002F07.system-programming-windows\u002F14.async-advanced",{"title":352,"path":353,"stem":354},"System.Threading.Channels — Async Producer-Consumer","\u002Fcsharp\u002Fsystem-programming-windows\u002Fchannels","01.csharp\u002F07.system-programming-windows\u002F15.channels",{"title":356,"path":357,"stem":358},"Асинхронна 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ОС","\u002Fcsharp\u002Fsystem-programming-windows\u002Fwindows-hooks-services","01.csharp\u002F07.system-programming-windows\u002F20.windows-hooks-services",{"title":376,"path":377,"stem":378},"Системне Програмування C# (Windows) — 07.system-programming-windows","\u002Fcsharp\u002Fsystem-programming-windows\u002Fimplementation_plan","01.csharp\u002F07.system-programming-windows\u002Fimplementation_plan",{"title":380,"icon":132,"path":381,"stem":382,"children":383,"page":59},"Io","\u002Fcsharp\u002Fio","01.csharp\u002F08.io",[384,388,392,396,400],{"title":385,"path":386,"stem":387},"8.1.1. Основи роботи з файловою системою","\u002Fcsharp\u002Fio\u002Ffile-system-basics","01.csharp\u002F08.io\u002F01.file-system-basics",{"title":389,"path":390,"stem":391},"8.1.2. Потоки (Streams) та Серіалізація Даних","\u002Fcsharp\u002Fio\u002Fstreams-serialization","01.csharp\u002F08.io\u002F02.streams-serialization",{"title":393,"path":394,"stem":395},"8.2.1. JSON Serialization з System.Text.Json","\u002Fcsharp\u002Fio\u002Fjson-serialization","01.csharp\u002F08.io\u002F03.json-serialization",{"title":397,"path":398,"stem":399},"8.2.2. XML Serialization та LINQ to XML","\u002Fcsharp\u002Fio\u002Fxml-serialization","01.csharp\u002F08.io\u002F04.xml-serialization",{"title":401,"path":402,"stem":403},"8.2.3. Binary Serialization: MessagePack та Protocol Buffers","\u002Fcsharp\u002Fio\u002Fbinary-serialization","01.csharp\u002F08.io\u002F05.binary-serialization",{"title":405,"icon":132,"path":406,"stem":407,"children":408,"page":59},"Ado Net","\u002Fcsharp\u002Fado-net","01.csharp\u002F09.ado-net",[409,413,417,421,425,429,433,437,441,445,449,453],{"title":410,"path":411,"stem":412},"9.1. Введення в ADO.NET","\u002Fcsharp\u002Fado-net\u002Fintroduction-to-adonet","01.csharp\u002F09.ado-net\u002F01.introduction-to-adonet",{"title":414,"path":415,"stem":416},"9.2. Клас DbConnection — з'єднання з базою даних","\u002Fcsharp\u002Fado-net\u002Fconnection","01.csharp\u002F09.ado-net\u002F02.connection",{"title":418,"path":419,"stem":420},"9.3. Клас DbCommand — виконання SQL-запитів","\u002Fcsharp\u002Fado-net\u002Fcommand-and-queries","01.csharp\u002F09.ado-net\u002F03.command-and-queries",{"title":422,"path":423,"stem":424},"9.4. Клас DbDataReader — ефективне читання даних","\u002Fcsharp\u002Fado-net\u002Fdatareader","01.csharp\u002F09.ado-net\u002F04.datareader",{"title":426,"path":427,"stem":428},"9.5. Параметризовані запити та захист від SQL Injection","\u002Fcsharp\u002Fado-net\u002Fparameters-and-sql-injection","01.csharp\u002F09.ado-net\u002F05.parameters-and-sql-injection",{"title":430,"path":431,"stem":432},"9.6. Транзакції в ADO.NET","\u002Fcsharp\u002Fado-net\u002Ftransactions","01.csharp\u002F09.ado-net\u002F06.transactions",{"title":434,"path":435,"stem":436},"9.7. DbProviderFactory — провайдер-незалежний код","\u002Fcsharp\u002Fado-net\u002Fprovider-factory","01.csharp\u002F09.ado-net\u002F07.provider-factory",{"title":438,"path":439,"stem":440},"9.8. Асинхронний доступ до даних","\u002Fcsharp\u002Fado-net\u002Fasync-data-access","01.csharp\u002F09.ado-net\u002F08.async-data-access",{"title":442,"path":443,"stem":444},"9.9. Від'єднаний режим: DataSet, DataTable, DataRow","\u002Fcsharp\u002Fado-net\u002Fdisconnected-mode-dataset","01.csharp\u002F09.ado-net\u002F09.disconnected-mode-dataset",{"title":446,"path":447,"stem":448},"9.10. DataAdapter — міст між DataSet та базою даних","\u002Fcsharp\u002Fado-net\u002Fdata-adapter","01.csharp\u002F09.ado-net\u002F10.data-adapter",{"title":450,"path":451,"stem":452},"9.11. Data Mapper та Repository: Архітектура доступу до даних","\u002Fcsharp\u002Fado-net\u002Fdata-mapper-repository","01.csharp\u002F09.ado-net\u002F11.data-mapper-repository",{"title":454,"path":455,"stem":456},"9.12. Identity Map, Unit of Work та Specification Pattern","\u002Fcsharp\u002Fado-net\u002Fadvanced-patterns","01.csharp\u002F09.ado-net\u002F12.advanced-patterns",{"title":458,"icon":255,"path":459,"stem":460,"children":461,"page":59},"Ef Core","\u002Fcsharp\u002Fef-core","01.csharp\u002F10.ef-core",[462,466,470,474,478,482,486,490,494,498,502,506,510,514,518,522,526,532,538,542,546,550,554,558,562,566,570,574,578,582,586,590,594,598,602,606,610,614,618,622,626,630,634,638,642,646],{"title":463,"path":464,"stem":465},"Що таке ORM? Від SQL до об'єктів","\u002Fcsharp\u002Fef-core\u002Fwhat-is-orm","01.csharp\u002F10.ef-core\u002F01.what-is-orm",{"title":467,"path":468,"stem":469},"Перший проєкт — від нуля до CRUD","\u002Fcsharp\u002Fef-core\u002Ffirst-project","01.csharp\u002F10.ef-core\u002F02.first-project",{"title":471,"path":472,"stem":473},"DbContext — Серце EF Core","\u002Fcsharp\u002Fef-core\u002Fdbcontext-deep-dive","01.csharp\u002F10.ef-core\u002F03.dbcontext-deep-dive",{"title":475,"path":476,"stem":477},"Провайдери баз даних — Архітектура та Вибір СУБД","\u002Fcsharp\u002Fef-core\u002Fdatabase-providers","01.csharp\u002F10.ef-core\u002F04.database-providers",{"title":479,"path":480,"stem":481},"Конвенції EF Core — Магія без конфігурації","\u002Fcsharp\u002Fef-core\u002Fconventions","01.csharp\u002F10.ef-core\u002F05.conventions",{"title":483,"path":484,"stem":485},"Fluent API та Data Annotations — Явна конфігурація моделі","\u002Fcsharp\u002Fef-core\u002Ffluent-api-vs-annotations","01.csharp\u002F10.ef-core\u002F06.fluent-api-vs-annotations",{"title":487,"path":488,"stem":489},"Зв'язки — One-to-One та One-to-Many","\u002Fcsharp\u002Fef-core\u002Frelationships-basics","01.csharp\u002F10.ef-core\u002F07.relationships-basics",{"title":491,"path":492,"stem":493},"Зв'язки Advanced — Many-to-Many та Складні Сценарії","\u002Fcsharp\u002Fef-core\u002Frelationships-advanced","01.csharp\u002F10.ef-core\u002F08.relationships-advanced",{"title":495,"path":496,"stem":497},"Властивості — Типи, Конвертери, Компаратори (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fproperty-configuration-part1","01.csharp\u002F10.ef-core\u002F09.property-configuration-part1",{"title":499,"path":500,"stem":501},"Властивості — Value Comparers, Generators, Shadow Properties (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fproperty-configuration-part2","01.csharp\u002F10.ef-core\u002F09.property-configuration-part2",{"title":503,"path":504,"stem":505},"Складні типи — Owned Types та Complex Types (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fcomplex-types-owned-part1","01.csharp\u002F10.ef-core\u002F10.complex-types-owned-part1",{"title":507,"path":508,"stem":509},"Складні типи — Complex Types, Keyless Entities, Порівняння (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fcomplex-types-owned-part2","01.csharp\u002F10.ef-core\u002F10.complex-types-owned-part2",{"title":511,"path":512,"stem":513},"JSON Columns — Складні дані у JSON (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fjson-columns-part1","01.csharp\u002F10.ef-core\u002F11.json-columns-part1",{"title":515,"path":516,"stem":517},"JSON Columns — Value Comparers, Індекси, Провайдери (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fjson-columns-part2","01.csharp\u002F10.ef-core\u002F11.json-columns-part2",{"title":519,"path":520,"stem":521},"Успадкування — Абстрактні класи та TPH (Частина 1)","\u002Fcsharp\u002Fef-core\u002Finheritance-part1","01.csharp\u002F10.ef-core\u002F12.inheritance-part1",{"title":523,"path":524,"stem":525},"Успадкування — TPT, TPC та Порівняння Стратегій (Частина 2)","\u002Fcsharp\u002Fef-core\u002Finheritance-part2","01.csharp\u002F10.ef-core\u002F12.inheritance-part2",{"title":527,"path":528,"stem":529,"children":530},"Індекси, Обмеження та Схема (Частина 1)","\u002Fcsharp\u002Fef-core\u002Findexes-constraints-part1","01.csharp\u002F10.ef-core\u002F13.indexes-constraints-part1",[531],{"title":527,"path":528,"stem":529},{"title":533,"path":534,"stem":535,"children":536},"Індекси, Обмеження та Схема (Частина 2)","\u002Fcsharp\u002Fef-core\u002Findexes-constraints-part2","01.csharp\u002F10.ef-core\u002F13.indexes-constraints-part2",[537],{"title":533,"path":534,"stem":535},{"title":539,"path":540,"stem":541},"Seed Data — Початкові Дані (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fseeding-part1","01.csharp\u002F10.ef-core\u002F14.seeding-part1",{"title":543,"path":544,"stem":545},"Seed Data — SQL-скрипти, Bogus та Стратегії (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fseeding-part2","01.csharp\u002F10.ef-core\u002F14.seeding-part2",{"title":547,"path":548,"stem":549},"Global Query Filters — Глобальні Фільтри (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fglobal-query-filters-part1","01.csharp\u002F10.ef-core\u002F15.global-query-filters-part1",{"title":551,"path":552,"stem":553},"Global Query Filters — Підводні камені та Інтеграція (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fglobal-query-filters-part2","01.csharp\u002F10.ef-core\u002F15.global-query-filters-part2",{"title":555,"path":556,"stem":557},"LINQ-запити в EF Core (Частина 1)","\u002Fcsharp\u002Fef-core\u002Flinq-queries-part1","01.csharp\u002F10.ef-core\u002F16.linq-queries-part1",{"title":559,"path":560,"stem":561},"LINQ-запити в EF Core (Частина 2)","\u002Fcsharp\u002Fef-core\u002Flinq-queries-part2","01.csharp\u002F10.ef-core\u002F16.linq-queries-part2",{"title":563,"path":564,"stem":565},"Завантаження Пов'язаних Даних (Частина 1)","\u002Fcsharp\u002Fef-core\u002Floading-related-data-part1","01.csharp\u002F10.ef-core\u002F17.loading-related-data-part1",{"title":567,"path":568,"stem":569},"Завантаження Пов'язаних Даних (Частина 2)","\u002Fcsharp\u002Fef-core\u002Floading-related-data-part2","01.csharp\u002F10.ef-core\u002F17.loading-related-data-part2",{"title":571,"path":572,"stem":573},"Raw SQL, Views та Stored Procedures (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fraw-sql-part1","01.csharp\u002F10.ef-core\u002F18.raw-sql-part1",{"title":575,"path":576,"stem":577},"Raw SQL — Stored Procedures, DbFunction та Bulk Operations (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fraw-sql-part2","01.csharp\u002F10.ef-core\u002F18.raw-sql-part2",{"title":579,"path":580,"stem":581},"Продвинуті Запити — Compiled Queries, Bulk та Оптимізація (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fadvanced-queries-part1","01.csharp\u002F10.ef-core\u002F19.advanced-queries-part1",{"title":583,"path":584,"stem":585},"Продвинуті Запити — Query Tags, Bulk та Interceptors (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fadvanced-queries-part2","01.csharp\u002F10.ef-core\u002F19.advanced-queries-part2",{"title":587,"path":588,"stem":589},"Change Tracker — Відстеження Змін (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fchange-tracking-part1","01.csharp\u002F10.ef-core\u002F20.change-tracking-part1",{"title":591,"path":592,"stem":593},"Change Tracker — Графи Об'єктів та Disconnected (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fchange-tracking-part2","01.csharp\u002F10.ef-core\u002F20.change-tracking-part2",{"title":595,"path":596,"stem":597},"Збереження Даних та Транзакції (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fsaving-data-part1","01.csharp\u002F10.ef-core\u002F21.saving-data-part1",{"title":599,"path":600,"stem":601},"Збереження Даних — Concurrency та Outbox (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fsaving-data-part2","01.csharp\u002F10.ef-core\u002F21.saving-data-part2",{"title":603,"path":604,"stem":605},"Конкурентність та Блокування (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fconcurrency-part1","01.csharp\u002F10.ef-core\u002F22.concurrency-part1",{"title":607,"path":608,"stem":609},"Конкурентність — Дедлоки та Queue Processing (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fconcurrency-part2","01.csharp\u002F10.ef-core\u002F22.concurrency-part2",{"title":611,"path":612,"stem":613},"Міграції в EF Core — Основи (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fmigrations-basics-part1","01.csharp\u002F10.ef-core\u002F23.migrations-basics-part1",{"title":615,"path":616,"stem":617},"Міграції в EF Core — Основи (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fmigrations-basics-part2","01.csharp\u002F10.ef-core\u002F23.migrations-basics-part2",{"title":619,"path":620,"stem":621},"Міграції — Просунуті Сценарії (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fmigrations-advanced-part1","01.csharp\u002F10.ef-core\u002F24.migrations-advanced-part1",{"title":623,"path":624,"stem":625},"Міграції — Просунуті Сценарії (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fmigrations-advanced-part2","01.csharp\u002F10.ef-core\u002F24.migrations-advanced-part2",{"title":627,"path":628,"stem":629},"Управління Схемою та Database-First (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fschema-management-part1","01.csharp\u002F10.ef-core\u002F25.schema-management-part1",{"title":631,"path":632,"stem":633},"Управління Схемою та Database-First (Частина 2)","\u002Fcsharp\u002Fef-core\u002Fschema-management-part2","01.csharp\u002F10.ef-core\u002F25.schema-management-part2",{"title":635,"path":636,"stem":637},"Продуктивність EF Core — Основи (Частина 1)","\u002Fcsharp\u002Fef-core\u002Fperformance-fundamentals-part1","01.csharp\u002F10.ef-core\u002F26.performance-fundamentals-part1",{"title":639,"path":640,"stem":641},"Interceptors в EF Core (Частина 1)","\u002Fcsharp\u002Fef-core\u002Finterceptors-part1","01.csharp\u002F10.ef-core\u002F29.interceptors-part1",{"title":643,"path":644,"stem":645},"Interceptors в EF Core — Connection, Transaction та Materialization (Частина 2)","\u002Fcsharp\u002Fef-core\u002Finterceptors-part2","01.csharp\u002F10.ef-core\u002F29.interceptors-part2",{"title":647,"path":648,"stem":649},"План вивчення Entity Framework Core — Повний курс","\u002Fcsharp\u002Fef-core\u002Fimplementation_plan","01.csharp\u002F10.ef-core\u002Fimplementation_plan",{"title":651,"icon":652,"path":653,"stem":654,"children":655,"page":59},"ASP.NET","i-devicon-dotnetcore","\u002Fcsharp\u002Faspnet","01.csharp\u002F11.aspnet",[656,730,791,869,927,941,967,1057,1111,1182,1212,1289,1346],{"title":657,"icon":658,"path":659,"stem":660,"children":661,"page":59},"Minimal API","i-lucide-network","\u002Fcsharp\u002Faspnet\u002Fminimal-api","01.csharp\u002F11.aspnet\u002F01.minimal-api",[662,666,670,674,678,682,686,690,694,698,702,706,710,714,718,722,726],{"title":663,"path":664,"stem":665},"Вступ до ASP.NET та еволюція фреймворку","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fintroduction","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F01.introduction",{"title":667,"path":668,"stem":669},"Перший додаток на ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Ffirst-application","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F02.first-application",{"title":671,"path":672,"stem":673},"WebApplication, Builder та Dependency Injection","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fwebapplication-builder","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F03.webapplication-builder",{"title":675,"path":676,"stem":677},"Конвеєр запитів та Middleware","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Frequest-pipeline-middleware","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F04.request-pipeline-middleware",{"title":679,"path":680,"stem":681},"Маршрутизація в ASP.NET Core: Основи","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Frouting-basics","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F05.routing-basics",{"title":683,"path":684,"stem":685},"Маршрутизація в ASP.NET Core: Розширені можливості","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Frouting-advanced","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F06.routing-advanced",{"title":687,"path":688,"stem":689},"Статичні файли в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fstatic-files","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F07.static-files",{"title":691,"path":692,"stem":693},"Статичні Активи: MapStaticAssets (ASP.NET Core 9.0)","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fstatic-assets","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F08.static-assets",{"title":695,"path":696,"stem":697},"Конфігурація в ASP.NET Core: Основи","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fconfiguration-fundamentals","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F09.configuration-fundamentals",{"title":699,"path":700,"stem":701},"Конфігурація: Паттерн Options","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fconfiguration-options","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F10.configuration-options",{"title":703,"path":704,"stem":705},"Логування в ASP.NET Core: Основи","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Flogging-basics","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F11.logging-basics",{"title":707,"path":708,"stem":709},"Логування: Serilog та Middleware","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Flogging-advanced","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F12.logging-advanced",{"title":711,"path":712,"stem":713},"Управління станом: HttpContext.Items та Cookies","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fstate-management","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F13.state-management",{"title":715,"path":716,"stem":717},"Стан сесії: Sessions","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fsession-state","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F14.session-state",{"title":719,"path":720,"stem":721},"Структура проєкту: від хаосу до архітектури","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fproject-structure","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F15.project-structure",{"title":723,"path":724,"stem":725},"Scalar у Minimal API: повний проєкт і Fluent OpenAPI","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fscalar-openapi-fluent","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F16.scalar-openapi-fluent",{"title":727,"path":728,"stem":729},"Swagger \u002F Swashbuckle у Minimal API: окремий класичний шлях","\u002Fcsharp\u002Faspnet\u002Fminimal-api\u002Fswagger-swashbuckle","01.csharp\u002F11.aspnet\u002F01.minimal-api\u002F17.swagger-swashbuckle",{"title":731,"icon":658,"path":732,"stem":733,"children":734,"page":59},"API","\u002Fcsharp\u002Faspnet\u002Fapi","01.csharp\u002F11.aspnet\u002F02.api",[735,739,743,747,751,755,759,763,767,771,775,779,783,787],{"title":736,"path":737,"stem":738},"Що таке API. Клієнт-серверна архітектура","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fwhat-is-api","01.csharp\u002F11.aspnet\u002F02.api\u002F01.what-is-api",{"title":740,"path":741,"stem":742},"Формати даних: JSON, XML, TOML та бінарні формати","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fdata-formats","01.csharp\u002F11.aspnet\u002F02.api\u002F02.data-formats",{"title":744,"path":745,"stem":746},"Парадигми API та концепція REST","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fapi-paradigms-rest","01.csharp\u002F11.aspnet\u002F02.api\u002F03.api-paradigms-rest",{"title":748,"path":749,"stem":750},"HTTP-методи, статус-коди та заголовки","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fhttp-methods-status-codes","01.csharp\u002F11.aspnet\u002F02.api\u002F04.http-methods-status-codes",{"title":752,"path":753,"stem":754},"Організація HTTP API за принципами REST","\u002Fcsharp\u002Faspnet\u002Fapi\u002Frest-organizing","01.csharp\u002F11.aspnet\u002F02.api\u002F05.rest-organizing",{"title":756,"path":757,"stem":758},"Номенклатура URL та CRUD-операції","\u002Fcsharp\u002Faspnet\u002Fapi\u002Furl-nomenclature-crud","01.csharp\u002F11.aspnet\u002F02.api\u002F06.url-nomenclature-crud",{"title":760,"path":761,"stem":762},"Правила дизайну: іменування та стандарти","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fapi-design-naming","01.csharp\u002F11.aspnet\u002F02.api\u002F07.api-design-naming",{"title":764,"path":765,"stem":766},"Валідація, ліміти та обробка помилок","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fapi-design-validation","01.csharp\u002F11.aspnet\u002F02.api\u002F08.api-design-validation",{"title":768,"path":769,"stem":770},"Обробка помилок у Minimal API","\u002Fcsharp\u002Faspnet\u002Fapi\u002Ferror-handling-http","01.csharp\u002F11.aspnet\u002F02.api\u002F09.error-handling-http",{"title":772,"path":773,"stem":774},"Ідемпотентність та синхронізація стану","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fidempotency-sync","01.csharp\u002F11.aspnet\u002F02.api\u002F10.idempotency-sync",{"title":776,"path":777,"stem":778},"Пагінація та організація списків","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fpagination-lists","01.csharp\u002F11.aspnet\u002F02.api\u002F11.pagination-lists",{"title":780,"path":781,"stem":782},"Безпека API, кешування та інтернаціоналізація","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fsecurity-auth","01.csharp\u002F11.aspnet\u002F02.api\u002F12.security-auth",{"title":784,"path":785,"stem":786},"Процес проєктування API та документування","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fapi-design-process","01.csharp\u002F11.aspnet\u002F02.api\u002F13.api-design-process",{"title":788,"path":789,"stem":790},"OpenAPI: контракт, специфікація та документація API","\u002Fcsharp\u002Faspnet\u002Fapi\u002Fopenapi","01.csharp\u002F11.aspnet\u002F02.api\u002F14.openapi",{"title":792,"icon":793,"path":794,"stem":795,"children":796,"page":59},"Auth","i-lucide-shield-check","\u002Fcsharp\u002Faspnet\u002Fauth","01.csharp\u002F11.aspnet\u002F03.auth",[797,801,805,809,813,817,821,825,829,833,837,841,845,849,853,857,861,865],{"title":798,"path":799,"stem":800},"Основи аутентифікації та авторизації","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fauth-fundamentals","01.csharp\u002F11.aspnet\u002F03.auth\u002F01.auth-fundamentals",{"title":802,"path":803,"stem":804},"JWT-аутентифікація","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fjwt-authentication","01.csharp\u002F11.aspnet\u002F03.auth\u002F02.jwt-authentication",{"title":806,"path":807,"stem":808},"Авторизація: ролі, політики та resource-based доступ","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fauthorization-policies","01.csharp\u002F11.aspnet\u002F03.auth\u002F03.authorization-policies",{"title":810,"path":811,"stem":812},"Cookie-аутентифікація та ASP.NET Core Identity","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fcookie-auth-identity","01.csharp\u002F11.aspnet\u002F03.auth\u002F04.cookie-auth-identity",{"title":814,"path":815,"stem":816},"JWT + Refresh Tokens (HttpOnly Cookie)","\u002Fcsharp\u002Faspnet\u002Fauth\u002F04b.identity-auth-jwt","01.csharp\u002F11.aspnet\u002F03.auth\u002F04b.identity-auth-jwt",{"title":818,"path":819,"stem":820},"Identity: Підтвердження Email та Скидання Пароля","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fidentity-email-confirmation","01.csharp\u002F11.aspnet\u002F03.auth\u002F05.identity-email-confirmation",{"title":822,"path":823,"stem":824},"Identity: Двофакторна Аутентифікація (2FA)","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fidentity-two-factor","01.csharp\u002F11.aspnet\u002F03.auth\u002F06.identity-two-factor",{"title":826,"path":827,"stem":828},"Identity: Внутрішня Архітектура та Кастомізація","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fidentity-internals","01.csharp\u002F11.aspnet\u002F03.auth\u002F07.identity-internals",{"title":830,"path":831,"stem":832},"OAuth 2.0 та зовнішні провайдери","\u002Fcsharp\u002Faspnet\u002Fauth\u002Foauth-external-providers","01.csharp\u002F11.aspnet\u002F03.auth\u002F08.oauth-external-providers",{"title":834,"path":835,"stem":836},"Безпека на практиці: CORS, HTTPS та захист від атак","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fsecurity-hardening","01.csharp\u002F11.aspnet\u002F03.auth\u002F09.security-hardening",{"title":838,"path":839,"stem":840},"Теорія OAuth 2.0: Поняття, Аналогії та Флоу","\u002Fcsharp\u002Faspnet\u002Fauth\u002Foauth-theory","01.csharp\u002F11.aspnet\u002F03.auth\u002F10.oauth-theory",{"title":842,"path":843,"stem":844},"OIDC, OAuth 2.0 та Keycloak в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Foidc-keycloak","01.csharp\u002F11.aspnet\u002F03.auth\u002F10.oidc-keycloak",{"title":846,"path":847,"stem":848},"API Keys аутентифікація в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fapi-keys","01.csharp\u002F11.aspnet\u002F03.auth\u002F11.api-keys",{"title":850,"path":851,"stem":852},"Rate Limiting та Throttling в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Frate-limiting","01.csharp\u002F11.aspnet\u002F03.auth\u002F12.rate-limiting",{"title":854,"path":855,"stem":856},"Refresh Token Rotation в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Frefresh-token-rotation","01.csharp\u002F11.aspnet\u002F03.auth\u002F13.refresh-token-rotation",{"title":858,"path":859,"stem":860},"Certificate Authentication та mTLS в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fcertificate-auth","01.csharp\u002F11.aspnet\u002F03.auth\u002F14.certificate-auth",{"title":862,"path":863,"stem":864},"RBAC, ABAC та ReBAC в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Frbac-abac-rebac","01.csharp\u002F11.aspnet\u002F03.auth\u002F15.rbac-abac-rebac",{"title":866,"path":867,"stem":868},"Multi-tenancy та ізоляція даних в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fauth\u002Fmulti-tenancy","01.csharp\u002F11.aspnet\u002F03.auth\u002F16.multi-tenancy",{"title":870,"icon":871,"path":872,"stem":873,"children":874,"page":59},"Нотифікації","i-lucide-bell","\u002Fcsharp\u002Faspnet\u002Fnotifications","01.csharp\u002F11.aspnet\u002F04.notifications",[875,879,883,887,891,895,899,903,907,911,915,919,923],{"title":876,"path":877,"stem":878},"In-App нотифікації через базу даних","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fin-app-database-notifications","01.csharp\u002F11.aspnet\u002F04.notifications\u002F01.in-app-database-notifications",{"title":880,"path":881,"stem":882},"Polling: Регулярний запит оновлень","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fpolling","01.csharp\u002F11.aspnet\u002F04.notifications\u002F02.polling",{"title":884,"path":885,"stem":886},"Server-Sent Events: Однострімовий push від сервера","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fserver-sent-events","01.csharp\u002F11.aspnet\u002F04.notifications\u002F03.server-sent-events",{"title":888,"path":889,"stem":890},"WebSockets: Двостороннє з'єднання в реальному часі","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fwebsockets","01.csharp\u002F11.aspnet\u002F04.notifications\u002F04.websockets",{"title":892,"path":893,"stem":894},"SignalR: Абстракція над транспортами реального часу","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fsignalr","01.csharp\u002F11.aspnet\u002F04.notifications\u002F05.signalr",{"title":896,"path":897,"stem":898},"Background Services: Фонові задачі в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fbackground-services","01.csharp\u002F11.aspnet\u002F04.notifications\u002F06.background-services",{"title":900,"path":901,"stem":902},"Web Push нотифікації","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fweb-push","01.csharp\u002F11.aspnet\u002F04.notifications\u002F07.web-push",{"title":904,"path":905,"stem":906},"Email нотифікації","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Femail-notifications","01.csharp\u002F11.aspnet\u002F04.notifications\u002F08.email-notifications",{"title":908,"path":909,"stem":910},"Порівняння підходів: Як вибрати правильну технологію нотифікацій","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fchoosing-the-right-approach","01.csharp\u002F11.aspnet\u002F04.notifications\u002F09.choosing-the-right-approach",{"title":912,"path":913,"stem":914},"Hangfire: Надійне планування фонових задач","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fhangfire","01.csharp\u002F11.aspnet\u002F04.notifications\u002F10.hangfire",{"title":916,"path":917,"stem":918},"Практика: Конвертація зображень у WebP через Hangfire","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fhangfire-image-webp","01.csharp\u002F11.aspnet\u002F04.notifications\u002F11.hangfire-image-webp",{"title":920,"path":921,"stem":922},"Практика: Підготовка відео до HLS-стрімінгу через Hangfire","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Fhangfire-video-hls","01.csharp\u002F11.aspnet\u002F04.notifications\u002F12.hangfire-video-hls",{"title":924,"path":925,"stem":926},"Telegram-нотифікації: від одного повідомлення до масових розсилок і мульти-канального підходу","\u002Fcsharp\u002Faspnet\u002Fnotifications\u002Ftelegram-notifications","01.csharp\u002F11.aspnet\u002F04.notifications\u002F13.telegram-notifications",{"title":928,"icon":929,"path":930,"stem":931,"children":932,"page":59},"Інтернаціоналізація","i-lucide-languages","\u002Fcsharp\u002Faspnet\u002Fi18n","01.csharp\u002F11.aspnet\u002F05.i18n",[933,937],{"title":934,"path":935,"stem":936},"Інтернаціоналізація (i18n) у Minimal API: від A до Я","\u002Fcsharp\u002Faspnet\u002Fi18n\u002Finternationalization","01.csharp\u002F11.aspnet\u002F05.i18n\u002F01.internationalization",{"title":938,"path":939,"stem":940},"Humanizer: людиномовні рядки у .NET","\u002Fcsharp\u002Faspnet\u002Fi18n\u002Fhumanizer","01.csharp\u002F11.aspnet\u002F05.i18n\u002F02.humanizer",{"title":942,"icon":943,"path":944,"stem":945,"children":946,"page":59},"Кешування","i-lucide-layers","\u002Fcsharp\u002Faspnet\u002Fcaching","01.csharp\u002F11.aspnet\u002F06.caching",[947,951,955,959,963],{"title":948,"path":949,"stem":950},"Огляд кешування: чотири рівні і коли що обирати","\u002Fcsharp\u002Faspnet\u002Fcaching\u002Fcaching","01.csharp\u002F11.aspnet\u002F06.caching\u002F01.caching",{"title":952,"path":953,"stem":954},"IMemoryCache: кеш в оперативній пам'яті","\u002Fcsharp\u002Faspnet\u002Fcaching\u002Fmemory-cache","01.csharp\u002F11.aspnet\u002F06.caching\u002F02.memory-cache",{"title":956,"path":957,"stem":958},"IDistributedCache і Redis: розподілений кеш","\u002Fcsharp\u002Faspnet\u002Fcaching\u002Fdistributed-cache","01.csharp\u002F11.aspnet\u002F06.caching\u002F03.distributed-cache",{"title":960,"path":961,"stem":962},"Response Cache: HTTP-кешування через Cache-Control","\u002Fcsharp\u002Faspnet\u002Fcaching\u002Fresponse-cache","01.csharp\u002F11.aspnet\u002F06.caching\u002F04.response-cache",{"title":964,"path":965,"stem":966},"Output Cache: серверний кеш HTTP-відповідей (.NET 7+)","\u002Fcsharp\u002Faspnet\u002Fcaching\u002Foutput-cache","01.csharp\u002F11.aspnet\u002F06.caching\u002F05.output-cache",{"title":968,"icon":969,"path":970,"stem":971,"children":972,"page":59},"Тестування","i-lucide-test-tube","\u002Fcsharp\u002Faspnet\u002Ftesting","01.csharp\u002F11.aspnet\u002F07.testing",[973,977,981,985,989,993,997,1001,1005,1009,1013,1017,1021,1025,1029,1033,1037,1041,1045,1049,1053],{"title":974,"path":975,"stem":976},"Що таке тестування? Від інтуїції до науки","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fwhat-is-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F01.what-is-testing",{"title":978,"path":979,"stem":980},"Піраміда тестування — Стратегія, а не Догма","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Ftesting-pyramid","01.csharp\u002F11.aspnet\u002F07.testing\u002F02.testing-pyramid",{"title":982,"path":983,"stem":984},"Дві Школи Тестування — Лондон проти Детройту","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Ftesting-schools","01.csharp\u002F11.aspnet\u002F07.testing\u002F03.testing-schools",{"title":986,"path":987,"stem":988},"TDD та BDD — Тести як Дизайн-інструмент","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Ftdd-and-bdd","01.csharp\u002F11.aspnet\u002F07.testing\u002F04.tdd-and-bdd",{"title":990,"path":991,"stem":992},"Що саме тестувати — Техніки аналізу та Циклomatична складність","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fwhat-to-test","01.csharp\u002F11.aspnet\u002F07.testing\u002F05.what-to-test",{"title":994,"path":995,"stem":996},"Тестові Фреймворки — Навіщо вони і що всередині","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Ftest-frameworks","01.csharp\u002F11.aspnet\u002F07.testing\u002F06.test-frameworks",{"title":998,"path":999,"stem":1000},"xUnit — Факти, Теорії та Lifecycle тестів","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fxunit-basics","01.csharp\u002F11.aspnet\u002F07.testing\u002F07.xunit-basics",{"title":1002,"path":1003,"stem":1004},"xUnit Advanced — Fixtures, Кастомізація та Розширення","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fxunit-advanced","01.csharp\u002F11.aspnet\u002F07.testing\u002F08.xunit-advanced",{"title":1006,"path":1007,"stem":1008},"Moq — Глибоке занурення в мокування","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fmocking-with-moq","01.csharp\u002F11.aspnet\u002F07.testing\u002F09.mocking-with-moq",{"title":1010,"path":1011,"stem":1012},"Тестування Баз Даних — EF Core, SQLite та Testcontainers","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fdatabase-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F10.database-testing",{"title":1014,"path":1015,"stem":1016},"Integration Testing — Частина 1 [Теорія та WebApplicationFactory]","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fintegration-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F11.integration-testing",{"title":1018,"path":1019,"stem":1020},"Інтеграційне тестування — Практика","\u002Fcsharp\u002Faspnet\u002Ftesting\u002F11a.integration-testing-practice","01.csharp\u002F11.aspnet\u002F07.testing\u002F11a.integration-testing-practice",{"title":1022,"path":1023,"stem":1024},"Integration Testing — Частина 2 [Просунуті Сценарії та Testcontainers]","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fintegration-testing-advanced","01.csharp\u002F11.aspnet\u002F07.testing\u002F12.integration-testing-advanced",{"title":1026,"path":1027,"stem":1028},"Професійний Postman: Колекції, Змінні та GitHub Інтеграція","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fpostman-professional","01.csharp\u002F11.aspnet\u002F07.testing\u002F13.postman-professional",{"title":1030,"path":1031,"stem":1032},"HttpClient у Тестах Частина 1: Архітектура та MockHttpMessageHandler","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fhttpclient-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F14.httpclient-testing",{"title":1034,"path":1035,"stem":1036},"HttpClient у Тестах Частина 2: WireMock.Net та Resilience","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fwiremock-net","01.csharp\u002F11.aspnet\u002F07.testing\u002F15.wiremock-net",{"title":1038,"path":1039,"stem":1040},"Патерни та Анти-патерни Тестування: Test Smells","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Ftesting-patterns","01.csharp\u002F11.aspnet\u002F07.testing\u002F16.testing-patterns",{"title":1042,"path":1043,"stem":1044},"Просунуті інструменти: Time, Snapshots та Властивості","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fadvanced-testing-tools","01.csharp\u002F11.aspnet\u002F07.testing\u002F17.advanced-testing-tools",{"title":1046,"path":1047,"stem":1048},"Тестування Архітектури з NetArchTest","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Farchitecture-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F18.architecture-testing",{"title":1050,"path":1051,"stem":1052},"Тестування Продуктивності: BenchmarkDotNet, NBomber та k6","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fperformance-testing","01.csharp\u002F11.aspnet\u002F07.testing\u002F19.performance-testing",{"title":1054,"path":1055,"stem":1056},"Залишок плану для курсу \"Тестування ASP.NET Minimal API\"","\u002Fcsharp\u002Faspnet\u002Ftesting\u002Fremaining_plan","01.csharp\u002F11.aspnet\u002F07.testing\u002Fremaining_plan",{"title":1058,"icon":1059,"path":1060,"stem":1061,"children":1062,"page":59},"Платежі","i-lucide-credit-card","\u002Fcsharp\u002Faspnet\u002Fpayments","01.csharp\u002F11.aspnet\u002F08.payments",[1063,1067,1071,1075,1079,1083,1087,1091,1095,1099,1103,1107],{"title":1064,"path":1065,"stem":1066},"Основи платіжної інфраструктури","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fpayment-fundamentals","01.csharp\u002F11.aspnet\u002F08.payments\u002F01.payment-fundamentals",{"title":1068,"path":1069,"stem":1070},"Методи оплати в Україні","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fpayment-methods-ukraine","01.csharp\u002F11.aspnet\u002F08.payments\u002F02.payment-methods-ukraine",{"title":1072,"path":1073,"stem":1074},"PCI DSS та безпека платежів","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fpci-dss-security","01.csharp\u002F11.aspnet\u002F08.payments\u002F03.pci-dss-security",{"title":1076,"path":1077,"stem":1078},"Архітектура платіжної підсистеми","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fpayment-architecture","01.csharp\u002F11.aspnet\u002F08.payments\u002F04.payment-architecture",{"title":1080,"path":1081,"stem":1082},"Інтеграція LiqPay (ПриватБанк)","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fliqpay-integration","01.csharp\u002F11.aspnet\u002F08.payments\u002F05.liqpay-integration",{"title":1084,"path":1085,"stem":1086},"Інтеграція Monobank Acquiring API","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fmonobank-acquiring","01.csharp\u002F11.aspnet\u002F08.payments\u002F06.monobank-acquiring",{"title":1088,"path":1089,"stem":1090},"Інтеграція Stripe","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fstripe-integration","01.csharp\u002F11.aspnet\u002F08.payments\u002F07.stripe-integration",{"title":1092,"path":1093,"stem":1094},"Webhooks — глибоке занурення","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fwebhooks-deep-dive","01.csharp\u002F11.aspnet\u002F08.payments\u002F08.webhooks-deep-dive",{"title":1096,"path":1097,"stem":1098},"Підписки та рекурентні платежі","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fsubscriptions-recurring","01.csharp\u002F11.aspnet\u002F08.payments\u002F09.subscriptions-recurring",{"title":1100,"path":1101,"stem":1102},"Повернення коштів та диспути","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Frefunds-disputes","01.csharp\u002F11.aspnet\u002F08.payments\u002F10.refunds-disputes",{"title":1104,"path":1105,"stem":1106},"Тестування платіжних інтеграцій","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Ftesting-payments","01.csharp\u002F11.aspnet\u002F08.payments\u002F11.testing-payments",{"title":1108,"path":1109,"stem":1110},"Чекліст виходу в Production","\u002Fcsharp\u002Faspnet\u002Fpayments\u002Fproduction-checklist","01.csharp\u002F11.aspnet\u002F08.payments\u002F12.production-checklist",{"title":1112,"icon":1113,"items":1114,"path":1127,"stem":1128,"children":1129,"page":59},"Популярні бібліотеки","lucide:box",[1115,1116,1117,1118,1119,1120,1121,1122,1123,1124,1125,1126],"01.fluent-validation","02.mapster","03.erroror-result-pattern","04.serilog","05.mediatr","06.polly","07.health-checks","08.feature-management","09.fluent-email","10.quest-pdf","11.bogus","12.humanizer-guard","\u002Fcsharp\u002Faspnet\u002Flibraries","01.csharp\u002F11.aspnet\u002F09.libraries",[1130,1134,1138,1142,1146,1150,1154,1158,1162,1166,1170,1174,1178],{"title":1131,"path":1132,"stem":1133},"Валідація з FluentValidation в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Ffluent-validation","01.csharp\u002F11.aspnet\u002F09.libraries\u002F01.fluent-validation",{"title":1135,"path":1136,"stem":1137},"Маппінг об","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fmapster","01.csharp\u002F11.aspnet\u002F09.libraries\u002F02.mapster",{"title":1139,"path":1140,"stem":1141},"Обробка помилок з ErrorOr та Result Pattern в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Ferroror-result-pattern","01.csharp\u002F11.aspnet\u002F09.libraries\u002F03.erroror-result-pattern",{"title":1143,"path":1144,"stem":1145},"Структуроване логування з Serilog в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fserilog","01.csharp\u002F11.aspnet\u002F09.libraries\u002F04.serilog",{"title":1147,"path":1148,"stem":1149},"CQRS та Mediator з MediatR в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fmediatr","01.csharp\u002F11.aspnet\u002F09.libraries\u002F05.mediatr",{"title":1151,"path":1152,"stem":1153},"Відмовостійкість з Polly в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fpolly","01.csharp\u002F11.aspnet\u002F09.libraries\u002F06.polly",{"title":1155,"path":1156,"stem":1157},"Health Checks в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fhealth-checks","01.csharp\u002F11.aspnet\u002F09.libraries\u002F07.health-checks",{"title":1159,"path":1160,"stem":1161},"Feature Management та Feature Flags в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Ffeature-management","01.csharp\u002F11.aspnet\u002F09.libraries\u002F08.feature-management",{"title":1163,"path":1164,"stem":1165},"Відправка Email з FluentEmail в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Ffluent-email","01.csharp\u002F11.aspnet\u002F09.libraries\u002F09.fluent-email",{"title":1167,"path":1168,"stem":1169},"Генерація PDF з QuestPDF в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fquest-pdf","01.csharp\u002F11.aspnet\u002F09.libraries\u002F10.quest-pdf",{"title":1171,"path":1172,"stem":1173},"Генерація тестових даних з Bogus в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fbogus","01.csharp\u002F11.aspnet\u002F09.libraries\u002F11.bogus",{"title":1175,"path":1176,"stem":1177},"Humanizer та Guard Clauses в ASP.NET Core","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fhumanizer-guard","01.csharp\u002F11.aspnet\u002F09.libraries\u002F12.humanizer-guard",{"title":1179,"path":1180,"stem":1181},"План модуля 10.libraries — Популярні бібліотеки ASP.NET","\u002Fcsharp\u002Faspnet\u002Flibraries\u002Fplan","01.csharp\u002F11.aspnet\u002F09.libraries\u002Fplan",{"title":1183,"icon":1184,"path":1185,"stem":1186,"children":1187,"page":59},"Razor Pages","i-lucide-layout-template","\u002Fcsharp\u002Faspnet\u002Frazor-pages","01.csharp\u002F11.aspnet\u002F10.razor-pages",[1188,1192,1196,1200,1204,1208],{"title":1189,"path":1190,"stem":1191},"Від Minimal API до Razor Pages: концептуальний перехід","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Ffrom-minimal-api","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F01.from-minimal-api",{"title":1193,"path":1194,"stem":1195},"PageModel: логіка сторінки Razor Pages","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Fpage-model","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F02.page-model",{"title":1197,"path":1198,"stem":1199},"Razor синтаксис: шаблонізатор у .cshtml","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Frazor-syntax","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F03.razor-syntax",{"title":1201,"path":1202,"stem":1203},"Tag Helpers: типізований HTML","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Ftag-helpers","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F04.tag-helpers",{"title":1205,"path":1206,"stem":1207},"Форми і валідація: повний цикл обробки даних","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Fforms-validation","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F05.forms-validation",{"title":1209,"path":1210,"stem":1211},"Практичний проєкт: TaskManager на Razor Pages","\u002Fcsharp\u002Faspnet\u002Frazor-pages\u002Fproject-task-manager","01.csharp\u002F11.aspnet\u002F10.razor-pages\u002F06.project-task-manager",{"title":1213,"path":1214,"stem":1215,"children":1216,"page":59},"ASP.NET Core MVC","\u002Fcsharp\u002Faspnet\u002Fmvc","01.csharp\u002F11.aspnet\u002F11.mvc",[1217,1221,1225,1229,1233,1237,1241,1245,1249,1253,1257,1261,1265,1269,1273,1277,1281,1285],{"title":1218,"path":1219,"stem":1220},"Патерн MVC: архітектура, що змінила веб","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fmvc-pattern","01.csharp\u002F11.aspnet\u002F11.mvc\u002F01.mvc-pattern",{"title":1222,"path":1223,"stem":1224},"Від Razor Pages до MVC: концептуальний перехід","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Ffrom-razor-pages","01.csharp\u002F11.aspnet\u002F11.mvc\u002F02.from-razor-pages",{"title":1226,"path":1227,"stem":1228},"Controllers та Actions: серце MVC","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fcontrollers-actions","01.csharp\u002F11.aspnet\u002F11.mvc\u002F03.controllers-actions",{"title":1230,"path":1231,"stem":1232},"Маршрутизація в MVC: Convention vs Attribute Routing","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Frouting-mvc","01.csharp\u002F11.aspnet\u002F11.mvc\u002F04.routing-mvc",{"title":1234,"path":1235,"stem":1236},"Model Binding: від HTTP до C#","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fmodel-binding","01.csharp\u002F11.aspnet\u002F11.mvc\u002F05.model-binding",{"title":1238,"path":1239,"stem":1240},"Views, ViewData, ViewBag, TempData і ViewModel","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fviews-viewdata-tempdata","01.csharp\u002F11.aspnet\u002F11.mvc\u002F06.views-viewdata-tempdata",{"title":1242,"path":1243,"stem":1244},"Filters: аспектно-орієнтоване програмування в MVC","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Ffilters","01.csharp\u002F11.aspnet\u002F11.mvc\u002F07.filters",{"title":1246,"path":1247,"stem":1248},"Areas: структурування великих застосунків","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fareas","01.csharp\u002F11.aspnet\u002F11.mvc\u002F08.areas",{"title":1250,"path":1251,"stem":1252},"View Components: повторювані незалежні блоки UI","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fview-components","01.csharp\u002F11.aspnet\u002F11.mvc\u002F09.view-components",{"title":1254,"path":1255,"stem":1256},"Display та Editor Templates","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fdisplay-editor-templates","01.csharp\u002F11.aspnet\u002F11.mvc\u002F10.display-editor-templates",{"title":1258,"path":1259,"stem":1260},"Валідація: IValidatableObject та FluentValidation","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fvalidation-advanced","01.csharp\u002F11.aspnet\u002F11.mvc\u002F11.validation-advanced",{"title":1262,"path":1263,"stem":1264},"HTMX: інтерактивність через HTML-атрибути","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fhtmx","01.csharp\u002F11.aspnet\u002F11.mvc\u002F12.htmx",{"title":1266,"path":1267,"stem":1268},"HTMX у ASP.NET Core MVC: серверна інтеграція","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fajax-htmx-mvc","01.csharp\u002F11.aspnet\u002F11.mvc\u002F13.ajax-htmx-mvc",{"title":1270,"path":1271,"stem":1272},"Практичний проєкт: Каталог товарів з HTMX","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fhtmx-project","01.csharp\u002F11.aspnet\u002F11.mvc\u002F14.htmx-project",{"title":1274,"path":1275,"stem":1276},"Завантаження та обробка файлів","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Ffile-upload","01.csharp\u002F11.aspnet\u002F11.mvc\u002F15.file-upload",{"title":1278,"path":1279,"stem":1280},"Глобалізація та Локалізація MVC","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fglobalization-localization","01.csharp\u002F11.aspnet\u002F11.mvc\u002F16.globalization-localization",{"title":1282,"path":1283,"stem":1284},"Підсумковий проєкт: Блог-платформа","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fmvc-project","01.csharp\u002F11.aspnet\u002F11.mvc\u002F17.mvc-project",{"title":1286,"path":1287,"stem":1288},"План курсу: ASP.NET Core MVC","\u002Fcsharp\u002Faspnet\u002Fmvc\u002Fplan","01.csharp\u002F11.aspnet\u002F11.mvc\u002Fplan",{"title":1290,"path":1291,"stem":1292,"children":1293,"page":59},"Web Api","\u002Fcsharp\u002Faspnet\u002Fweb-api","01.csharp\u002F11.aspnet\u002F12.web-api",[1294,1298,1302,1306,1310,1314,1318,1322,1326,1330,1334,1338,1342],{"title":1295,"path":1296,"stem":1297},"Від Minimal API до Controller-based API","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Ffrom-minimal-api-to-controllers","01.csharp\u002F11.aspnet\u002F12.web-api\u002F01.from-minimal-api-to-controllers",{"title":1299,"path":1300,"stem":1301},"ControllerBase, ActionResult\u003CT> та Response Types","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fcontroller-base-actionresult","01.csharp\u002F11.aspnet\u002F12.web-api\u002F02.controller-base-actionresult",{"title":1303,"path":1304,"stem":1305},"Content Negotiation - JSON, XML та власні форматери","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fcontent-negotiation","01.csharp\u002F11.aspnet\u002F12.web-api\u002F03.content-negotiation",{"title":1307,"path":1308,"stem":1309},"Версіонування API","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fapi-versioning","01.csharp\u002F11.aspnet\u002F12.web-api\u002F04.api-versioning",{"title":1311,"path":1312,"stem":1313},"ProblemDetails та структурована обробка помилок","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fproblemdetails-error-handling","01.csharp\u002F11.aspnet\u002F12.web-api\u002F05.problemdetails-error-handling",{"title":1315,"path":1316,"stem":1317},"Фільтри у Web API контексті","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Ffilters-for-api","01.csharp\u002F11.aspnet\u002F12.web-api\u002F06.filters-for-api",{"title":1319,"path":1320,"stem":1321},"Пагінація, фільтрація та сортування","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fpagination-filtering-sorting","01.csharp\u002F11.aspnet\u002F12.web-api\u002F07.pagination-filtering-sorting",{"title":1323,"path":1324,"stem":1325},"HATEOAS та Resource Expansion","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fhateoas-resource-expansion","01.csharp\u002F11.aspnet\u002F12.web-api\u002F08.hateoas-resource-expansion",{"title":1327,"path":1328,"stem":1329},"Гібридна архітектура - Minimal API + Controllers","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fminimal-api-vs-controllers-hybrid","01.csharp\u002F11.aspnet\u002F12.web-api\u002F09.minimal-api-vs-controllers-hybrid",{"title":1331,"path":1332,"stem":1333},"Документація API - Swashbuckle, NSwag та генерація клієнтів","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fapi-documentation-generation","01.csharp\u002F11.aspnet\u002F12.web-api\u002F10.api-documentation-generation",{"title":1335,"path":1336,"stem":1337},"Health Checks та моніторинг API","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fhealth-checks-monitoring","01.csharp\u002F11.aspnet\u002F12.web-api\u002F11.health-checks-monitoring",{"title":1339,"path":1340,"stem":1341},"Підсумковий проєкт - Production-Ready REST API","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fweb-api-project","01.csharp\u002F11.aspnet\u002F12.web-api\u002F12.web-api-project",{"title":1343,"path":1344,"stem":1345},"План курсу: ASP.NET Core Web API (Controllers)","\u002Fcsharp\u002Faspnet\u002Fweb-api\u002Fplan","01.csharp\u002F11.aspnet\u002F12.web-api\u002Fplan",{"title":1347,"icon":1348,"path":1349,"stem":1350,"children":1351,"page":59},"Моніторинг","i-lucide-activity","\u002Fcsharp\u002Faspnet\u002Fmonitoring","01.csharp\u002F11.aspnet\u002F13.monitoring",[1352,1356,1360],{"title":1353,"path":1354,"stem":1355},"Спостережуваність: від console.log до production-систем","\u002Fcsharp\u002Faspnet\u002Fmonitoring\u002Fobservability-intro","01.csharp\u002F11.aspnet\u002F13.monitoring\u002F01.observability-intro",{"title":1357,"path":1358,"stem":1359},"Health Checks: перший рівень observability","\u002Fcsharp\u002Faspnet\u002Fmonitoring\u002Fhealth-checks","01.csharp\u002F11.aspnet\u002F13.monitoring\u002F02.health-checks",{"title":1361,"path":1362,"stem":1363},"Вбудовані метрики .NET 10 та System.Diagnostics.Metrics","\u002Fcsharp\u002Faspnet\u002Fmonitoring\u002Fdotnet-metrics","01.csharp\u002F11.aspnet\u002F13.monitoring\u002F03.dotnet-metrics",{"title":1365,"icon":1366,"path":1367,"stem":1368,"children":1369,"page":59},"Desktop UI","i-lucide-app-window","\u002Fcsharp\u002Fdesktop-ui","01.csharp\u002F12.desktop-ui",[1370,1374,1378,1382,1386,1390,1394,1398,1402,1406,1410,1414,1418,1422,1426,1430,1434,1438,1442,1446,1450,1454,1458,1462,1466,1470,1474,1478,1482,1486,1490,1494,1498,1502,1506,1510,1514,1518,1522,1526,1530,1534,1538,1542,1546,1550,1554,1558,1562,1566,1570,1574,1578,1582,1586,1590,1594,1598,1602,1606,1610,1614,1618,1622,1626,1630,1634,1638,1642,1646,1650],{"title":1371,"path":1372,"stem":1373},"Що таке десктопна розробка?","\u002Fcsharp\u002Fdesktop-ui\u002Fwhat-is-desktop-dev","01.csharp\u002F12.desktop-ui\u002F01.what-is-desktop-dev",{"title":1375,"path":1376,"stem":1377},"Архітектура WPF — як влаштований графічний інтерфейс","\u002Fcsharp\u002Fdesktop-ui\u002Fwpf-architecture","01.csharp\u002F12.desktop-ui\u002F02.wpf-architecture",{"title":1379,"path":1380,"stem":1381},"Перший WPF-проєкт — від нуля до вікна","\u002Fcsharp\u002Fdesktop-ui\u002Ffirst-wpf-app","01.csharp\u002F12.desktop-ui\u002F03.first-wpf-app",{"title":1383,"path":1384,"stem":1385},"Перший Avalonia-проєкт: WPF для всіх платформ","\u002Fcsharp\u002Fdesktop-ui\u002F03a.first-avalonia-app","01.csharp\u002F12.desktop-ui\u002F03a.first-avalonia-app",{"title":1387,"path":1388,"stem":1389},"XAML: декларативний інтерфейс","\u002Fcsharp\u002Fdesktop-ui\u002Fxaml-basics","01.csharp\u002F12.desktop-ui\u002F04.xaml-basics",{"title":1391,"path":1392,"stem":1393},"Fluent UI у WPF — сучасний дизайн Windows 11","\u002Fcsharp\u002Fdesktop-ui\u002F04a.wpf-fluent-ui","01.csharp\u002F12.desktop-ui\u002F04a.wpf-fluent-ui",{"title":1395,"path":1396,"stem":1397},"WPF UI — сучасна бібліотека Fluent контролів","\u002Fcsharp\u002Fdesktop-ui\u002F04b.wpf-ui-library","01.csharp\u002F12.desktop-ui\u002F04b.wpf-ui-library",{"title":1399,"path":1400,"stem":1401},"HandyControl — велика бібліотека UI контролів для WPF","\u002Fcsharp\u002Fdesktop-ui\u002F04c.handycontrol-library","01.csharp\u002F12.desktop-ui\u002F04c.handycontrol-library",{"title":1403,"path":1404,"stem":1405},"Простори імен та ресурси XAML","\u002Fcsharp\u002Fdesktop-ui\u002Fxaml-namespaces-resources","01.csharp\u002F12.desktop-ui\u002F05.xaml-namespaces-resources",{"title":1407,"path":1408,"stem":1409},"XAML в Avalonia: ключові відмінності від WPF","\u002Fcsharp\u002Fdesktop-ui\u002F05a.avalonia-xaml-differences","01.csharp\u002F12.desktop-ui\u002F05a.avalonia-xaml-differences",{"title":1411,"path":1412,"stem":1413},"Розширення розмітки XAML (Markup Extensions)","\u002Fcsharp\u002Fdesktop-ui\u002Fxaml-markup-extensions","01.csharp\u002F12.desktop-ui\u002F06.xaml-markup-extensions",{"title":1415,"path":1416,"stem":1417},"Панелі Layout: StackPanel, WrapPanel, DockPanel","\u002Fcsharp\u002Fdesktop-ui\u002Flayout-panels-part1","01.csharp\u002F12.desktop-ui\u002F07.layout-panels-part1",{"title":1419,"path":1420,"stem":1421},"Grid, Canvas, UniformGrid","\u002Fcsharp\u002Fdesktop-ui\u002Flayout-panels-part2","01.csharp\u002F12.desktop-ui\u002F07.layout-panels-part2",{"title":1423,"path":1424,"stem":1425},"Просунуті техніки Layout","\u002Fcsharp\u002Fdesktop-ui\u002Flayout-advanced","01.csharp\u002F12.desktop-ui\u002F08.layout-advanced",{"title":1427,"path":1428,"stem":1429},"Адаптивний Layout та найкращі практики","\u002Fcsharp\u002Fdesktop-ui\u002Flayout-responsive","01.csharp\u002F12.desktop-ui\u002F09.layout-responsive",{"title":1431,"path":1432,"stem":1433},"Layout в Avalonia: відмінності та нові можливості","\u002Fcsharp\u002Fdesktop-ui\u002F09a.layout-avalonia","01.csharp\u002F12.desktop-ui\u002F09a.layout-avalonia",{"title":1435,"path":1436,"stem":1437},"Button, Image, ProgressBar та інші базові контроли","\u002Fcsharp\u002Fdesktop-ui\u002Fbasic-controls","01.csharp\u002F12.desktop-ui\u002F10.basic-controls",{"title":1439,"path":1440,"stem":1441},"Контроли в Avalonia: відмінності від WPF","\u002Fcsharp\u002Fdesktop-ui\u002F10a.controls-avalonia","01.csharp\u002F12.desktop-ui\u002F10a.controls-avalonia",{"title":1443,"path":1444,"stem":1445},"Текстові контроли — TextBlock, TextBox, RichTextBox","\u002Fcsharp\u002Fdesktop-ui\u002Ftext-controls","01.csharp\u002F12.desktop-ui\u002F11.text-controls",{"title":1447,"path":1448,"stem":1449},"Контроли вибору — CheckBox, RadioButton, ComboBox, ListBox, DatePicker","\u002Fcsharp\u002Fdesktop-ui\u002Fselection-controls","01.csharp\u002F12.desktop-ui\u002F12.selection-controls",{"title":1451,"path":1452,"stem":1453},"Content Model — GroupBox, Expander, TabControl, StatusBar","\u002Fcsharp\u002Fdesktop-ui\u002Fcontent-controls","01.csharp\u002F12.desktop-ui\u002F13.content-controls",{"title":1455,"path":1456,"stem":1457},"UI\u002FUX принципи десктопних застосунків","\u002Fcsharp\u002Fdesktop-ui\u002F13a.ui-ux-principles","01.csharp\u002F12.desktop-ui\u002F13a.ui-ux-principles",{"title":1459,"path":1460,"stem":1461},"Dependency Properties — Концепція та Value Resolution","\u002Fcsharp\u002Fdesktop-ui\u002Fdependency-properties-part1","01.csharp\u002F12.desktop-ui\u002F14.dependency-properties-part1",{"title":1463,"path":1464,"stem":1465},"Avalonia Property System — StyledProperty та DirectProperty","\u002Fcsharp\u002Fdesktop-ui\u002F14a.avalonia-property-system","01.csharp\u002F12.desktop-ui\u002F14a.avalonia-property-system",{"title":1467,"path":1468,"stem":1469},"Attached Properties — Властивості без меж","\u002Fcsharp\u002Fdesktop-ui\u002Fattached-properties","01.csharp\u002F12.desktop-ui\u002F15.attached-properties",{"title":1471,"path":1472,"stem":1473},"Routed Events — Маршрутизація подій у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Frouted-events","01.csharp\u002F12.desktop-ui\u002F16.routed-events",{"title":1475,"path":1476,"stem":1477},"Data Binding — Від Code-Behind до Декларативності","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-binding-basics-part1","01.csharp\u002F12.desktop-ui\u002F17.data-binding-basics-part1",{"title":1479,"path":1480,"stem":1481},"INotifyPropertyChanged — Живе оновлення UI","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-binding-basics-part2","01.csharp\u002F12.desktop-ui\u002F17.data-binding-basics-part2",{"title":1483,"path":1484,"stem":1485},"Compiled Bindings в Avalonia — Безпека на етапі компіляції","\u002Fcsharp\u002Fdesktop-ui\u002F17a.avalonia-compiled-bindings","01.csharp\u002F12.desktop-ui\u002F17a.avalonia-compiled-bindings",{"title":1487,"path":1488,"stem":1489},"Просунутий Data Binding — ElementName, RelativeSource, MultiBinding","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-binding-advanced","01.csharp\u002F12.desktop-ui\u002F18.data-binding-advanced",{"title":1491,"path":1492,"stem":1493},"Value Converters — Перетворення типів даних у Data Binding","\u002Fcsharp\u002Fdesktop-ui\u002Fvalue-converters","01.csharp\u002F12.desktop-ui\u002F19.value-converters",{"title":1495,"path":1496,"stem":1497},"Data Templates — Візуалізація об'єктів у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-templates","01.csharp\u002F12.desktop-ui\u002F20.data-templates",{"title":1499,"path":1500,"stem":1501},"Collections Binding Part 1 — ObservableCollection та ItemsControl","\u002Fcsharp\u002Fdesktop-ui\u002Fcollections-binding-part1","01.csharp\u002F12.desktop-ui\u002F21.collections-binding-part1",{"title":1503,"path":1504,"stem":1505},"Collections Binding Part 2 — ICollectionView, Filtering, Sorting та Virtualization","\u002Fcsharp\u002Fdesktop-ui\u002Fcollections-binding-part2","01.csharp\u002F12.desktop-ui\u002F21.collections-binding-part2",{"title":1507,"path":1508,"stem":1509},"MVVM Pattern — Від Spaghetti Code до архітектури","\u002Fcsharp\u002Fdesktop-ui\u002Fmvvm-pattern","01.csharp\u002F12.desktop-ui\u002F22.mvvm-pattern",{"title":1511,"path":1512,"stem":1513},"ViewModel Implementation — Від BaseViewModel до валідації","\u002Fcsharp\u002Fdesktop-ui\u002Fviewmodel-implementation","01.csharp\u002F12.desktop-ui\u002F23.viewmodel-implementation",{"title":1515,"path":1516,"stem":1517},"Commands — Від event handlers до декларативних команд","\u002Fcsharp\u002Fdesktop-ui\u002Fcommands","01.csharp\u002F12.desktop-ui\u002F24.commands",{"title":1519,"path":1520,"stem":1521},"MVVM Toolkit — MVVM без boilerplate через Source Generators","\u002Fcsharp\u002Fdesktop-ui\u002Fmvvm-toolkit","01.csharp\u002F12.desktop-ui\u002F25.mvvm-toolkit",{"title":1523,"path":1524,"stem":1525},"Messenger Pattern — Комунікація між ViewModel без прямих посилань","\u002Fcsharp\u002Fdesktop-ui\u002Fmessenger-pattern","01.csharp\u002F12.desktop-ui\u002F26.messenger-pattern",{"title":1527,"path":1528,"stem":1529},"Стилі WPF — CSS для десктопу","\u002Fcsharp\u002Fdesktop-ui\u002Fstyles-basics","01.csharp\u002F12.desktop-ui\u002F27.styles-basics",{"title":1531,"path":1532,"stem":1533},"CSS-like стилі Avalonia","\u002Fcsharp\u002Fdesktop-ui\u002F27a.avalonia-css-styling","01.csharp\u002F12.desktop-ui\u002F27a.avalonia-css-styling",{"title":1535,"path":1536,"stem":1537},"Control Templates — Частина 1. Концепція та TemplateBinding","\u002Fcsharp\u002Fdesktop-ui\u002Fcontrol-templates-part1","01.csharp\u002F12.desktop-ui\u002F28.control-templates-part1",{"title":1539,"path":1540,"stem":1541},"Control Templates — Частина 2. Named Parts та ContentPresenter","\u002Fcsharp\u002Fdesktop-ui\u002Fcontrol-templates-part2","01.csharp\u002F12.desktop-ui\u002F28.control-templates-part2",{"title":1543,"path":1544,"stem":1545},"Control Themes в Avalonia — нова ера стилізації","\u002Fcsharp\u002Fdesktop-ui\u002F28a.avalonia-control-themes","01.csharp\u002F12.desktop-ui\u002F28a.avalonia-control-themes",{"title":1547,"path":1548,"stem":1549},"Triggers та Visual State Manager у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Ftriggers-visual-states","01.csharp\u002F12.desktop-ui\u002F29.triggers-visual-states",{"title":1551,"path":1552,"stem":1553},"Pseudo-classes в Avalonia — замість WPF Triggers","\u002Fcsharp\u002Fdesktop-ui\u002F29a.avalonia-pseudo-classes","01.csharp\u002F12.desktop-ui\u002F29a.avalonia-pseudo-classes",{"title":1555,"path":1556,"stem":1557},"Теми та ресурсні словники у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fresources-themes","01.csharp\u002F12.desktop-ui\u002F30.resources-themes",{"title":1559,"path":1560,"stem":1561},"Avalonia Themes — Fluent Design та система тематизації","\u002Fcsharp\u002Fdesktop-ui\u002F30a.avalonia-themes-fluent","01.csharp\u002F12.desktop-ui\u002F30a.avalonia-themes-fluent",{"title":1563,"path":1564,"stem":1565},"Контроли колекцій — глибоке занурення","\u002Fcsharp\u002Fdesktop-ui\u002Fcollection-controls","01.csharp\u002F12.desktop-ui\u002F31.collection-controls",{"title":1567,"path":1568,"stem":1569},"DataGrid — колонки та базове відображення","\u002Fcsharp\u002Fdesktop-ui\u002Fdatagrid-part1","01.csharp\u002F12.desktop-ui\u002F32.datagrid-part1",{"title":1571,"path":1572,"stem":1573},"DataGrid — сортування, фільтрація, редагування","\u002Fcsharp\u002Fdesktop-ui\u002Fdatagrid-part2","01.csharp\u002F12.desktop-ui\u002F32.datagrid-part2",{"title":1575,"path":1576,"stem":1577},"TreeView та GridView","\u002Fcsharp\u002Fdesktop-ui\u002Ftreeview-listview","01.csharp\u002F12.desktop-ui\u002F33.treeview-listview",{"title":1579,"path":1580,"stem":1581},"Меню, Toolbar, ContextMenu, StatusBar","\u002Fcsharp\u002Fdesktop-ui\u002Fmenus-toolbars","01.csharp\u002F12.desktop-ui\u002F34.menus-toolbars",{"title":1583,"path":1584,"stem":1585},"Навігація та керування вікнами. Частина 1: вікна та сторінки","\u002Fcsharp\u002Fdesktop-ui\u002Fnavigation-windows-part1","01.csharp\u002F12.desktop-ui\u002F35.navigation-windows-part1",{"title":1587,"path":1588,"stem":1589},"Навігація та керування вікнами. Частина 2: MVVM-навігація","\u002Fcsharp\u002Fdesktop-ui\u002Fnavigation-windows-part2","01.csharp\u002F12.desktop-ui\u002F35.navigation-windows-part2",{"title":1591,"path":1592,"stem":1593},"Avalonia — Навігація та діалоги","\u002Fcsharp\u002Fdesktop-ui\u002F35a.avalonia-navigation-dialogs","01.csharp\u002F12.desktop-ui\u002F35a.avalonia-navigation-dialogs",{"title":1595,"path":1596,"stem":1597},"Діалоги та File Pickers у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fdialogs-file-pickers","01.csharp\u002F12.desktop-ui\u002F36.dialogs-file-pickers",{"title":1599,"path":1600,"stem":1601},"UserControl: компонентний підхід у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fuser-controls","01.csharp\u002F12.desktop-ui\u002F37.user-controls",{"title":1603,"path":1604,"stem":1605},"Custom Controls: Lookless Controls у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fcustom-controls","01.csharp\u002F12.desktop-ui\u002F38.custom-controls",{"title":1607,"path":1608,"stem":1609},"Avalonia TemplatedControl — Lookless Controls","\u002Fcsharp\u002Fdesktop-ui\u002F38a.avalonia-templated-controls","01.csharp\u002F12.desktop-ui\u002F38a.avalonia-templated-controls",{"title":1611,"path":1612,"stem":1613},"Анімації у WPF: Storyboard та Easing Functions","\u002Fcsharp\u002Fdesktop-ui\u002Fanimations-transitions","01.csharp\u002F12.desktop-ui\u002F39.animations-transitions",{"title":1615,"path":1616,"stem":1617},"Анімації в Avalonia","\u002Fcsharp\u002Fdesktop-ui\u002F39a.avalonia-animations","01.csharp\u002F12.desktop-ui\u002F39a.avalonia-animations",{"title":1619,"path":1620,"stem":1621},"2D Графіка та Мультимедіа у WPF","\u002Fcsharp\u002Fdesktop-ui\u002Fmedia-graphics","01.csharp\u002F12.desktop-ui\u002F40.media-graphics",{"title":1623,"path":1624,"stem":1625},"Dependency Injection у WPF та Avalonia","\u002Fcsharp\u002Fdesktop-ui\u002Fdi-integration","01.csharp\u002F12.desktop-ui\u002F41.di-integration",{"title":1627,"path":1628,"stem":1629},"SQLite та EF Core у десктопних додатках","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-persistence-part1","01.csharp\u002F12.desktop-ui\u002F42.data-persistence-part1",{"title":1631,"path":1632,"stem":1633},"Repository Pattern та Unit of Work","\u002Fcsharp\u002Fdesktop-ui\u002Fdata-persistence-part2","01.csharp\u002F12.desktop-ui\u002F43.data-persistence-part2",{"title":1635,"path":1636,"stem":1637},"Тестування ViewModels","\u002Fcsharp\u002Fdesktop-ui\u002Fviewmodel-testing","01.csharp\u002F12.desktop-ui\u002F44.viewmodel-testing",{"title":1639,"path":1640,"stem":1641},"Avalonia Headless Testing — тестування UI без вікон","\u002Fcsharp\u002Fdesktop-ui\u002F44a.avalonia-headless-testing","01.csharp\u002F12.desktop-ui\u002F44a.avalonia-headless-testing",{"title":1643,"path":1644,"stem":1645},"Кросплатформна розробка з Avalonia","\u002Fcsharp\u002Fdesktop-ui\u002Favalonia-cross-platform","01.csharp\u002F12.desktop-ui\u002F45.avalonia-cross-platform",{"title":1647,"path":1648,"stem":1649},"Пакування та розгортання Avalonia додатків","\u002Fcsharp\u002Fdesktop-ui\u002Favalonia-packaging-deployment","01.csharp\u002F12.desktop-ui\u002F46.avalonia-packaging-deployment",{"title":1651,"path":1652,"stem":1653},"Розгортання WPF застосунків","\u002Fcsharp\u002Fdesktop-ui\u002Fwpf-packaging-deployment","01.csharp\u002F12.desktop-ui\u002F47.wpf-packaging-deployment",{"title":1655,"icon":658,"path":1656,"stem":1657,"children":1658,"page":59},"Network Programming","\u002Fcsharp\u002Fnetwork-programming","01.csharp\u002F13.network-programming",[1659,1663,1667,1671,1675,1679,1683,1687,1691,1695,1699],{"title":1660,"path":1661,"stem":1662},"Основи комп'ютерних мереж","\u002Fcsharp\u002Fnetwork-programming\u002Ffoundations","01.csharp\u002F13.network-programming\u002F01.foundations",{"title":1664,"path":1665,"stem":1666},"Модель OSI та стек TCP\u002FIP","\u002Fcsharp\u002Fnetwork-programming\u002Fosi-model","01.csharp\u002F13.network-programming\u002F02.osi-model",{"title":1668,"path":1669,"stem":1670},"IP-протокол та адресація","\u002Fcsharp\u002Fnetwork-programming\u002Fip-addressing","01.csharp\u002F13.network-programming\u002F03.ip-addressing",{"title":1672,"path":1673,"stem":1674},"UDP — протокол без з'єднання","\u002Fcsharp\u002Fnetwork-programming\u002Fudp","01.csharp\u002F13.network-programming\u002F05.udp",{"title":1676,"path":1677,"stem":1678},"UDP Broadcast та Multicast","\u002Fcsharp\u002Fnetwork-programming\u002Fudp-broadcast-multicast","01.csharp\u002F13.network-programming\u002F06.udp-broadcast-multicast",{"title":1680,"path":1681,"stem":1682},"HTTP — протокол вебу","\u002Fcsharp\u002Fnetwork-programming\u002Fhttp-fundamentals","01.csharp\u002F13.network-programming\u002F07.http-fundamentals",{"title":1684,"path":1685,"stem":1686},"HttpListener — вбудований HTTP-сервер .NET","\u002Fcsharp\u002Fnetwork-programming\u002F07a.http-listener","01.csharp\u002F13.network-programming\u002F07a.http-listener",{"title":1688,"path":1689,"stem":1690},"HTTP Advanced — cookies, аутентифікація та HTTPS","\u002Fcsharp\u002Fnetwork-programming\u002Fhttp-advanced","01.csharp\u002F13.network-programming\u002F08.http-advanced",{"title":1692,"path":1693,"stem":1694},"SMTP та протоколи електронної пошти","\u002Fcsharp\u002Fnetwork-programming\u002Fsmtp","01.csharp\u002F13.network-programming\u002F09.smtp",{"title":1696,"path":1697,"stem":1698},"WebSocket — повнодуплексний протокол реального часу","\u002Fcsharp\u002Fnetwork-programming\u002Fwebsockets","01.csharp\u002F13.network-programming\u002F10.websockets",{"title":1700,"path":1701,"stem":1702},"TLS\u002FSSL — криптографічний захист мережевих з'єднань","\u002Fcsharp\u002Fnetwork-programming\u002Ftls-ssl","01.csharp\u002F13.network-programming\u002F11.tls-ssl",{"title":1704,"path":1705,"stem":1706},"C# & .NET: The Ultimate Roadmap","\u002Fcsharp\u002Froadmap","01.csharp\u002Froadmap",{"title":1708,"icon":1709,"path":1710,"stem":1711,"children":1712,"page":59},"C++","i-devicon-cplusplus","\u002Fcpp","02.cpp",[1713,1717,1721,1725,1729,1733,1737,1741,1745,1748,1752,1756,1760,1764,1768,1772,1776,1780,1784,1788,1792,1796,1800,1804,1808,1812,1816,1820,1824,1828,1832,1836,1840,1844,1848,1852,1856,1860,1864,1868,1872,1876,1880,1884,1888,1892,1896,1900,1904,1908,1912,1916,1920,1924,1928,1932,1936,1940,1944,1948,1952,1956,1960,1964,1968,1972,1976,1980,1984,1988,1992,1996,2000,2004,2008,2012,2016,2020,2024,2028,2032,2036,2040,2044,2048,2052,2056,2060,2064,2068,2072,2076,2080],{"title":1714,"path":1715,"stem":1716},"Вступ у програмування та алгоритми","\u002Fcpp\u002Fintro-algorithms","02.cpp\u002F01.intro-algorithms",{"title":1718,"path":1719,"stem":1720},"Code Style: угоди про оформлення коду","\u002Fcpp\u002Fcode-style","02.cpp\u002F02.code-style",{"title":1722,"path":1723,"stem":1724},"Середовище розробки та перший проєкт","\u002Fcpp\u002Fide-setup","02.cpp\u002F03.ide-setup",{"title":1726,"path":1727,"stem":1728},"Вивід даних на екран","\u002Fcpp\u002Fdata-output","02.cpp\u002F04.data-output",{"title":1730,"path":1731,"stem":1732},"Типи даних, змінні та константи","\u002Fcpp\u002Fdata-types-variables","02.cpp\u002F05.data-types-variables",{"title":1734,"path":1735,"stem":1736},"Ввід даних з клавіатури","\u002Fcpp\u002Fdata-input","02.cpp\u002F06.data-input",{"title":1738,"path":1739,"stem":1740},"Оператори, перетворення типів та логічні операції","\u002Fcpp\u002Foperators-type-conversion","02.cpp\u002F07.operators-type-conversion",{"title":1742,"path":1743,"stem":1744},"Цикли","\u002Fcpp\u002Floops","02.cpp\u002F08.loops",{"title":32,"path":1746,"stem":1747},"\u002Fcpp\u002Farrays","02.cpp\u002F09.arrays",{"title":1749,"path":1750,"stem":1751},"Алгоритми сортування та аналіз складності","\u002Fcpp\u002Fsorting","02.cpp\u002F10.sorting",{"title":1753,"path":1754,"stem":1755},"Алгоритми пошуку","\u002Fcpp\u002Fsearching","02.cpp\u002F11.searching",{"title":1757,"path":1758,"stem":1759},"Функції: основи","\u002Fcpp\u002Ffunctions-basics","02.cpp\u002F12.functions-basics",{"title":1761,"path":1762,"stem":1763},"Функції: прототипи, область видимості та додаткові можливості","\u002Fcpp\u002Ffunctions-scope","02.cpp\u002F13.functions-scope",{"title":1765,"path":1766,"stem":1767},"Функції: перевантаження та шаблони","\u002Fcpp\u002Ffunctions-overloading-templates","02.cpp\u002F14.functions-overloading-templates",{"title":1769,"path":1770,"stem":1771},"Вказівники: основи","\u002Fcpp\u002Fpointers-basics","02.cpp\u002F15.pointers-basics",{"title":1773,"path":1774,"stem":1775},"Посилання (References)","\u002Fcpp\u002Freferences","02.cpp\u002F16.references",{"title":1777,"path":1778,"stem":1779},"Вказівники, const і масиви","\u002Fcpp\u002Fpointers-const-arrays","02.cpp\u002F17.pointers-const-arrays",{"title":1781,"path":1782,"stem":1783},"Адресна арифметика","\u002Fcpp\u002Fpointer-arithmetic","02.cpp\u002F18.pointer-arithmetic",{"title":1785,"path":1786,"stem":1787},"Динамічна пам'ять","\u002Fcpp\u002Fdynamic-memory","02.cpp\u002F19.dynamic-memory",{"title":1789,"path":1790,"stem":1791},"Вказівники типу void","\u002Fcpp\u002Fvoid-pointers","02.cpp\u002F20.void-pointers",{"title":1793,"path":1794,"stem":1795},"Вказівники на вказівники","\u002Fcpp\u002Fpointers-to-pointers","02.cpp\u002F21.pointers-to-pointers",{"title":1797,"path":1798,"stem":1799},"Оператор доступу до членів через вказівник (->)","\u002Fcpp\u002Fmember-access-operator","02.cpp\u002F22.member-access-operator",{"title":1801,"path":1802,"stem":1803},"Цикл for-each (Range-based for)","\u002Fcpp\u002Fforeach-loop","02.cpp\u002F23.foreach-loop",{"title":1805,"path":1806,"stem":1807},"Вказівники на функції","\u002Fcpp\u002Ffunction-pointers","02.cpp\u002F24.function-pointers",{"title":1809,"path":1810,"stem":1811},"Лямбда-вирази","\u002Fcpp\u002Flambdas","02.cpp\u002F25.lambdas",{"title":1813,"path":1814,"stem":1815},"Лямбда-захоплення","\u002Fcpp\u002Flambda-captures","02.cpp\u002F26.lambda-captures",{"title":1817,"path":1818,"stem":1819},"Еліпсис","\u002Fcpp\u002Fellipsis","02.cpp\u002F27.ellipsis",{"title":1821,"path":1822,"stem":1823},"Безпечні альтернативи еліпсису","\u002Fcpp\u002F27a.ellipsis","02.cpp\u002F27a.ellipsis",{"title":1825,"path":1826,"stem":1827},"Аргументи командного рядка","\u002Fcpp\u002Fcommand-line-arguments","02.cpp\u002F28.command-line-arguments",{"title":1829,"path":1830,"stem":1831},"Перерахування (enum)","\u002Fcpp\u002Fenum","02.cpp\u002F29.enum",{"title":1833,"path":1834,"stem":1835},"Класи-перерахування (enum class)","\u002Fcpp\u002Fenum-class","02.cpp\u002F30.enum-class",{"title":1837,"path":1838,"stem":1839},"Псевдоніми типів (typedef і using)","\u002Fcpp\u002Ftype-aliases","02.cpp\u002F31.type-aliases",{"title":1841,"path":1842,"stem":1843},"Системи числення та двійкова арифметика","\u002Fcpp\u002Fnumber-systems","02.cpp\u002F32.number-systems",{"title":1845,"path":1846,"stem":1847},"Структури (struct): агрегування даних","\u002Fcpp\u002Fstruct","02.cpp\u002F33.struct",{"title":1849,"path":1850,"stem":1851},"Структури у функціях","\u002Fcpp\u002Fstruct-functions","02.cpp\u002F34.struct-functions",{"title":1853,"path":1854,"stem":1855},"Масиви структур і вкладені структури","\u002Fcpp\u002Fstruct-arrays","02.cpp\u002F35.struct-arrays",{"title":1857,"path":1858,"stem":1859},"Патерни struct та межі застосування","\u002Fcpp\u002Fstruct-patterns","02.cpp\u002F36.struct-patterns",{"title":1861,"path":1862,"stem":1863},"Символи та таблиця ASCII","\u002Fcpp\u002Fascii-characters","02.cpp\u002F37.ascii-characters",{"title":1865,"path":1866,"stem":1867},"Unicode та кодування UTF","\u002Fcpp\u002Funicode-utf","02.cpp\u002F38.unicode-utf",{"title":1869,"path":1870,"stem":1871},"C-style рядки","\u002Fcpp\u002Fc-strings","02.cpp\u002F39.c-strings",{"title":1873,"path":1874,"stem":1875},"Вступ до std::string","\u002Fcpp\u002Fstd-string-intro","02.cpp\u002F40.std-string-intro",{"title":1877,"path":1878,"stem":1879},"Довжина, ємність та доступ до символів std::string","\u002Fcpp\u002Fstd-string-capacity-access","02.cpp\u002F41.std-string-capacity-access",{"title":1881,"path":1882,"stem":1883},"Модифікація std::string: присвоювання, додавання, вставка, видалення та заміна","\u002Fcpp\u002Fstd-string-modification","02.cpp\u002F42.std-string-modification",{"title":1885,"path":1886,"stem":1887},"Пошук у std::string: find, npos та практичні патерни","\u002Fcpp\u002Fstd-string-search","02.cpp\u002F43.std-string-search",{"title":1889,"path":1890,"stem":1891},"std::string_view: невласницький погляд на рядок без копіювання","\u002Fcpp\u002Fstd-string-view","02.cpp\u002F44.std-string-view",{"title":1893,"path":1894,"stem":1895},"Об'єднання (union): один блок пам'яті, кілька інтерпретацій","\u002Fcpp\u002Funion","02.cpp\u002F45.union",{"title":1897,"path":1898,"stem":1899},"Організація коду: файли, препроцесор, простори імен","\u002Fcpp\u002Fmultifile-programs","02.cpp\u002F46.multifile-programs",{"title":1901,"path":1902,"stem":1903},"Робота з файлами: C-стиль (stdio.h)","\u002Fcpp\u002Fc-style-files","02.cpp\u002F47.c-style-files",{"title":1905,"path":1906,"stem":1907},"Робота з файлами: C++-стиль (fstream)","\u002Fcpp\u002Fcpp-style-files","02.cpp\u002F48.cpp-style-files",{"title":1909,"path":1910,"stem":1911},"Введення в ООП: від процедур до об'єктів","\u002Fcpp\u002Foop-intro","02.cpp\u002F49.oop-intro",{"title":1913,"path":1914,"stem":1915},"Класи, об'єкти та методи","\u002Fcpp\u002Fclasses-objects-methods","02.cpp\u002F50.classes-objects-methods",{"title":1917,"path":1918,"stem":1919},"Специфікатори доступу та інкапсуляція","\u002Fcpp\u002Faccess-specifiers-encapsulation","02.cpp\u002F51.access-specifiers-encapsulation",{"title":1921,"path":1922,"stem":1923},"Конструктори: гарантована ініціалізація об'єктів","\u002Fcpp\u002Fconstructors","02.cpp\u002F52.constructors",{"title":1925,"path":1926,"stem":1927},"Списки ініціалізації та делегуючі конструктори","\u002Fcpp\u002Finit-lists-delegating","02.cpp\u002F53.init-lists-delegating",{"title":1929,"path":1930,"stem":1931},"Деструктори та ідіома RAII","\u002Fcpp\u002Fdestructors-raii","02.cpp\u002F54.destructors-raii",{"title":1933,"path":1934,"stem":1935},"Прихований покажчик this","\u002Fcpp\u002Fthis-pointer","02.cpp\u002F55.this-pointer",{"title":1937,"path":1938,"stem":1939},"Розподіл класу на заголовковий файл та файл реалізації","\u002Fcpp\u002Fclass-header-source","02.cpp\u002F56.class-header-source",{"title":1941,"path":1942,"stem":1943},"Класи та const","\u002Fcpp\u002Fconst-classes","02.cpp\u002F57.const-classes",{"title":1945,"path":1946,"stem":1947},"Статичні члени класу","\u002Fcpp\u002Fstatic-members","02.cpp\u002F58.static-members",{"title":1949,"path":1950,"stem":1951},"Конструктор копіювання та запобігання копіюванню","\u002Fcpp\u002Fcopy-constructor","02.cpp\u002F59.copy-constructor",{"title":1953,"path":1954,"stem":1955},"Дружні функції та класи","\u002Fcpp\u002Ffriend-functions-classes","02.cpp\u002F60.friend-functions-classes",{"title":1957,"path":1958,"stem":1959},"Анонімні об'єкти та вкладені типи","\u002Fcpp\u002Fanonymous-objects-nested-types","02.cpp\u002F61.anonymous-objects-nested-types",{"title":1961,"path":1962,"stem":1963},"Вимірювання часу виконання: RAII-таймер","\u002Fcpp\u002Ftiming-raii-timer","02.cpp\u002F62.timing-raii-timer",{"title":1965,"path":1966,"stem":1967},"Перевантаження операторів: основи та арифметика","\u002Fcpp\u002Foperator-overloading-basics","02.cpp\u002F63.operator-overloading-basics",{"title":1969,"path":1970,"stem":1971},"Перевантаження операторів: методи класу та спеціальні оператори","\u002Fcpp\u002Foperator-overloading-methods","02.cpp\u002F64.operator-overloading-methods",{"title":1973,"path":1974,"stem":1975},"Приведення типів, explicit та delete","\u002Fcpp\u002Ftypecast-explicit-delete","02.cpp\u002F65.typecast-explicit-delete",{"title":1977,"path":1978,"stem":1979},"Глибоке копіювання та оператор присвоювання","\u002Fcpp\u002Fdeep-copy-assignment","02.cpp\u002F66.deep-copy-assignment",{"title":1981,"path":1982,"stem":1983},"Зв'язки між об'єктами: композиція та агрегація","\u002Fcpp\u002Fcomposition-aggregation","02.cpp\u002F67.composition-aggregation",{"title":1985,"path":1986,"stem":1987},"Асоціація та залежність між об","\u002Fcpp\u002Fassociation-dependency","02.cpp\u002F68.association-dependency",{"title":1989,"path":1990,"stem":1991},"Контейнерні класи та `std::initializer_list`","\u002Fcpp\u002Fcontainer-classes-initializer-list","02.cpp\u002F69.container-classes-initializer-list",{"title":1993,"path":1994,"stem":1995},"Вступ до наслідування: базові поняття та відношення «is-a»","\u002Fcpp\u002Finheritance-intro","02.cpp\u002F70.inheritance-intro",{"title":1997,"path":1998,"stem":1999},"Конструктори, деструктори та порядок ініціалізації в ієрархіях","\u002Fcpp\u002Finheritance-constructors-destructors","02.cpp\u002F71.inheritance-constructors-destructors",{"title":2001,"path":2002,"stem":2003},"Специфікатор `protected` та види наслідування","\u002Fcpp\u002Finheritance-access-specifiers","02.cpp\u002F72.inheritance-access-specifiers",{"title":2005,"path":2006,"stem":2007},"Перевизначення методів та приховування імен","\u002Fcpp\u002Fmethod-overriding-hiding","02.cpp\u002F73.method-overriding-hiding",{"title":2009,"path":2010,"stem":2011},"Множинне наслідування та проблема ромба","\u002Fcpp\u002Fmultiple-inheritance-diamond","02.cpp\u002F74.multiple-inheritance-diamond",{"title":2013,"path":2014,"stem":2015},"Вказівники на базовий клас та віртуальні функції","\u002Fcpp\u002Fvirtual-functions-polymorphism","02.cpp\u002F75.virtual-functions-polymorphism",{"title":2017,"path":2018,"stem":2019},"Специфікатори override, final та віртуальні деструктори","\u002Fcpp\u002Foverride-final-virtual-destructors","02.cpp\u002F76.override-final-virtual-destructors",{"title":2021,"path":2022,"stem":2023},"Внутрішні механізми поліморфізму: vtable, vptr та зв'язування","\u002Fcpp\u002Fvirtual-table-binding","02.cpp\u002F77.virtual-table-binding",{"title":2025,"path":2026,"stem":2027},"Абстрактні класи та чисті віртуальні функції","\u002Fcpp\u002Fabstract-classes-interfaces","02.cpp\u002F78.abstract-classes-interfaces",{"title":2029,"path":2030,"stem":2031},"Зрізка об'єктів, віртуальне наслідування та поліморфний вивід","\u002Fcpp\u002Fslicing-virtual-base-io","02.cpp\u002F79.slicing-virtual-base-io",{"title":2033,"path":2034,"stem":2035},"Динамічне приведення типів (`dynamic_cast`) та RTTI","\u002Fcpp\u002Fdynamic-cast-rtti","02.cpp\u002F80.dynamic-cast-rtti",{"title":2037,"path":2038,"stem":2039},"Шаблони функцій: узагальнене програмування","\u002Fcpp\u002Ffunction-templates","02.cpp\u002F81.function-templates",{"title":2041,"path":2042,"stem":2043},"Шаблони класів та NTTP-параметри","\u002Fcpp\u002Fclass-templates-nttp","02.cpp\u002F82.class-templates-nttp",{"title":2045,"path":2046,"stem":2047},"Повна (явна) спеціалізація шаблонів","\u002Fcpp\u002Ffull-template-specialization","02.cpp\u002F83.full-template-specialization",{"title":2049,"path":2050,"stem":2051},"Часткова спеціалізація шаблонів класів","\u002Fcpp\u002Fpartial-template-specialization","02.cpp\u002F84.partial-template-specialization",{"title":2053,"path":2054,"stem":2055},"Механізм винятків: try, catch, throw та розкручування стеку","\u002Fcpp\u002Fexceptions-basics","02.cpp\u002F85.exceptions-basics",{"title":2057,"path":2058,"stem":2059},"Ієрархія std::exception та власні класи винятків","\u002Fcpp\u002Fexception-hierarchy-custom","02.cpp\u002F86.exception-hierarchy-custom",{"title":2061,"path":2062,"stem":2063},"Повторне генерування винятків та функціональний try-блок","\u002Fcpp\u002Frethrow-function-try","02.cpp\u002F87.rethrow-function-try",{"title":2065,"path":2066,"stem":2067},"Безпека винятків, noexcept та деструктори","\u002Fcpp\u002Fsafety-noexcept","02.cpp\u002F88.safety-noexcept",{"title":2069,"path":2070,"stem":2071},"Стаття 89 — Власні структури даних: стек та черга","\u002Fcpp\u002Fcustom-stack-queue","02.cpp\u002F89.custom-stack-queue",{"title":2073,"path":2074,"stem":2075},"Стаття 90 — Власні структури даних: однозв'язаний список","\u002Fcpp\u002Flinked-list","02.cpp\u002F90.linked-list",{"title":2077,"path":2078,"stem":2079},"Стаття 91 — Власні структури даних: бінарне дерево пошуку","\u002Fcpp\u002Fbinary-search-tree","02.cpp\u002F91.binary-search-tree",{"title":2081,"path":2082,"stem":2083},"Стаття 92 — Власні структури даних: хеш-таблиця","\u002Fcpp\u002Fhash-table","02.cpp\u002F92.hash-table",{"title":2085,"icon":2086,"path":2087,"stem":2088,"children":2089,"page":59},"JavaScript","i-devicon-javascript","\u002Fjavascript","03.javascript",[2090,2116,2170,2192,2496,2534,2552],{"title":2091,"icon":2092,"path":2093,"stem":2094,"children":2095,"page":59},"Events","i-lucide-mouse-pointer-click","\u002Fjavascript\u002Fevents","03.javascript\u002F01.events",[2096,2100,2104,2108,2112],{"title":2097,"path":2098,"stem":2099},"Вступ до подій браузера","\u002Fjavascript\u002Fevents\u002Fintro","03.javascript\u002F01.events\u002F01.intro",{"title":2101,"path":2102,"stem":2103},"Бульбашковий механізм (Bubbling) та занурення (Capturing)","\u002Fjavascript\u002Fevents\u002Fbubbling-capturing","03.javascript\u002F01.events\u002F02.bubbling-capturing",{"title":2105,"path":2106,"stem":2107},"Делегування подій (Event Delegation)","\u002Fjavascript\u002Fevents\u002Fdelegate-events","03.javascript\u002F01.events\u002F03.delegate-events",{"title":2109,"path":2110,"stem":2111},"Типові дії браузера та preventDefault()","\u002Fjavascript\u002Fevents\u002Fprevent-default","03.javascript\u002F01.events\u002F04.prevent-default",{"title":2113,"path":2114,"stem":2115},"Запуск користувацьких подій (Custom Events)","\u002Fjavascript\u002Fevents\u002Fcustom-events","03.javascript\u002F01.events\u002F05.custom-events",{"title":2117,"icon":2118,"path":2119,"stem":2120,"children":2121,"page":59},"Network","i-lucide-globe","\u002Fjavascript\u002Fnetwork","03.javascript\u002F02.network",[2122,2126,2130,2134,2138,2142,2146,2150,2154,2158,2162,2166],{"title":2123,"path":2124,"stem":2125},"Fetch API - Сучасний підхід до HTTP-запитів","\u002Fjavascript\u002Fnetwork\u002F01-fetch-api","03.javascript\u002F02.network\u002F01-fetch-api",{"title":2127,"path":2128,"stem":2129},"FormData - Робота з формами та файлами","\u002Fjavascript\u002Fnetwork\u002F02-formdata","03.javascript\u002F02.network\u002F02-formdata",{"title":2131,"path":2132,"stem":2133},"Відстеження прогресу завантаження","\u002Fjavascript\u002Fnetwork\u002F03-download-progress","03.javascript\u002F02.network\u002F03-download-progress",{"title":2135,"path":2136,"stem":2137},"Переривання fetch-запитів","\u002Fjavascript\u002Fnetwork\u002F04-abort-requests","03.javascript\u002F02.network\u002F04-abort-requests",{"title":2139,"path":2140,"stem":2141},"CORS - Запити між різними джерелами","\u002Fjavascript\u002Fnetwork\u002F05-cors","03.javascript\u002F02.network\u002F05-cors",{"title":2143,"path":2144,"stem":2145},"Fetch API - Повний довідник опцій","\u002Fjavascript\u002Fnetwork\u002F06-fetch-options","03.javascript\u002F02.network\u002F06-fetch-options",{"title":2147,"path":2148,"stem":2149},"URL Objects - Робота з посиланнями","\u002Fjavascript\u002Fnetwork\u002F07-url-objects","03.javascript\u002F02.network\u002F07-url-objects",{"title":2151,"path":2152,"stem":2153},"XMLHttpRequest - AJAX та низькорівневі запити","\u002Fjavascript\u002Fnetwork\u002F08-xmlhttprequest","03.javascript\u002F02.network\u002F08-xmlhttprequest",{"title":2155,"path":2156,"stem":2157},"Відновлюване завантаження файлів","\u002Fjavascript\u002Fnetwork\u002F09-resumable-upload","03.javascript\u002F02.network\u002F09-resumable-upload",{"title":2159,"path":2160,"stem":2161},"Cookies, document.cookie та світ після \"Cookiepocalypse\"","\u002Fjavascript\u002Fnetwork\u002F10-cookies","03.javascript\u002F02.network\u002F10-cookies",{"title":2163,"path":2164,"stem":2165},"js-cookie: Керування Cookies без Болю","\u002Fjavascript\u002Fnetwork\u002F11-js-cookie","03.javascript\u002F02.network\u002F11-js-cookie",{"title":2167,"path":2168,"stem":2169},"Axios: Потужний HTTP-клієнт для JavaScript","\u002Fjavascript\u002Fnetwork\u002F12-axios","03.javascript\u002F02.network\u002F12-axios",{"title":2171,"icon":2172,"path":2173,"stem":2174,"children":2175,"page":59},"Bom","i-lucide-monitor","\u002Fjavascript\u002Fbom","03.javascript\u002F03.bom",[2176,2180,2184,2188],{"title":2177,"path":2178,"stem":2179},"LocalStorage, SessionStorage та patterns збереження даних","\u002Fjavascript\u002Fbom\u002F01-localstorage","03.javascript\u002F03.bom\u002F01-localstorage",{"title":2181,"path":2182,"stem":2183},"Location Object - Керування адресою сторінки","\u002Fjavascript\u002Fbom\u002F02-location-object","03.javascript\u002F03.bom\u002F02-location-object",{"title":2185,"path":2186,"stem":2187},"History API - Керування історією браузера","\u002Fjavascript\u002Fbom\u002F03-history-api","03.javascript\u002F03.bom\u002F03-history-api",{"title":2189,"path":2190,"stem":2191},"Navigator Object - Ідентифікація та Можливості Пристрою","\u002Fjavascript\u002Fbom\u002F04-navigator-object","03.javascript\u002F03.bom\u002F04-navigator-object",{"title":2193,"icon":2194,"path":2195,"stem":2196,"children":2197},"React","i-devicon-react","\u002Fjavascript\u002Freact","03.javascript\u002F04.react\u002Findex",[2198,2199,2203,2207,2211,2215,2278,2313,2465],{"title":2193,"path":2195,"stem":2196},{"title":2200,"path":2201,"stem":2202},"Робота з Формами в React","\u002Fjavascript\u002Freact\u002Freact-forms","03.javascript\u002F04.react\u002F01.react-forms",{"title":2204,"path":2205,"stem":2206},"React Hook Form: Професійна Робота з Формами","\u002Fjavascript\u002Freact\u002Freact-hook-form","03.javascript\u002F04.react\u002F02.react-hook-form",{"title":2208,"path":2209,"stem":2210},"React Hook Form: Глибоке Розуміння Архітектури та Оптимізації","\u002Fjavascript\u002Freact\u002Freact-hook-form-new","03.javascript\u002F04.react\u002F02.react-hook-form-new",{"title":2212,"path":2213,"stem":2214},"Axios та React: Професійна Архітектура Запитів","\u002Fjavascript\u002Freact\u002Fdata-fetching-axios","03.javascript\u002F04.react\u002F03.data-fetching-axios",{"title":2216,"icon":132,"path":2217,"stem":2218,"children":2219},"Tanstack Query","\u002Fjavascript\u002Freact\u002Ftanstack-query","03.javascript\u002F04.react\u002F04.tanstack-query\u002Findex",[2220,2222,2226,2230,2234,2238,2242,2246,2250,2254,2258,2262,2266,2270,2274],{"title":2221,"path":2217,"stem":2218},"TanStack Query: Майстерність Керування Станом Сервера",{"title":2223,"path":2224,"stem":2225},"Парадигма Server State: Чому useEffect недостатньо","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fserver-state-paradigm","03.javascript\u002F04.react\u002F04.tanstack-query\u002F01.server-state-paradigm",{"title":2227,"path":2228,"stem":2229},"Встановлення та Налаштування: Фундамент","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Finstallation-and-devtools","03.javascript\u002F04.react\u002F04.tanstack-query\u002F02.installation-and-devtools",{"title":2231,"path":2232,"stem":2233},"Основи Запитів та Магія Ключів","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fquery-basics-and-keys","03.javascript\u002F04.react\u002F04.tanstack-query\u002F03.query-basics-and-keys",{"title":2235,"path":2236,"stem":2237},"Синхронізація Даних: Життєвий Цикл Запиту","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fdata-synchronization","03.javascript\u002F04.react\u002F04.tanstack-query\u002F04.data-synchronization",{"title":2239,"path":2240,"stem":2241},"Мутації та Інвалідація: Зміна Даних","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fmutations-and-invalidation","03.javascript\u002F04.react\u002F04.tanstack-query\u002F05.mutations-and-invalidation",{"title":2243,"path":2244,"stem":2245},"Оптимістичні Оновлення: Швидше за Світло","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Foptimistic-updates","03.javascript\u002F04.react\u002F04.tanstack-query\u002F06.optimistic-updates",{"title":2247,"path":2248,"stem":2249},"Пагінація та Infinite Scroll","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fpagination-and-load-more","03.javascript\u002F04.react\u002F04.tanstack-query\u002F07.pagination-and-load-more",{"title":2251,"path":2252,"stem":2253},"Просунуті Патерни та Оптимізація","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fadvanced-patterns","03.javascript\u002F04.react\u002F04.tanstack-query\u002F08.advanced-patterns",{"title":2255,"path":2256,"stem":2257},"Архітектура та Best Practices","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Farchitecture-and-best-practices","03.javascript\u002F04.react\u002F04.tanstack-query\u002F09.architecture-and-best-practices",{"title":2259,"path":2260,"stem":2261},"Server-Side Rendering (SSR) та Гідратація","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fserver-side-rendering","03.javascript\u002F04.react\u002F04.tanstack-query\u002F10.server-side-rendering",{"title":2263,"path":2264,"stem":2265},"Стратегії Тестування","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Ftesting-strategies","03.javascript\u002F04.react\u002F04.tanstack-query\u002F11.testing-strategies",{"title":2267,"path":2268,"stem":2269},"Аутентифікація та Обробка Помилок","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fauthentication-and-errors","03.javascript\u002F04.react\u002F04.tanstack-query\u002F12.authentication-and-errors",{"title":2271,"path":2272,"stem":2273},"React Suspense та Майбутнє","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Freact-suspense","03.javascript\u002F04.react\u002F04.tanstack-query\u002F13.react-suspense",{"title":2275,"path":2276,"stem":2277},"Глибоке Занурення в Продуктивність","\u002Fjavascript\u002Freact\u002Ftanstack-query\u002Fperformance-deep-dive","03.javascript\u002F04.react\u002F04.tanstack-query\u002F14.performance-deep-dive",{"title":2279,"icon":2194,"path":2280,"stem":2281,"children":2282},"React Router","\u002Fjavascript\u002Freact\u002Freact-router","03.javascript\u002F04.react\u002F05.react-router\u002Findex",[2283,2285,2289,2293,2297,2301,2305,2309],{"title":2284,"path":2280,"stem":2281},"React Router: Навігаційна система сучасного вебу",{"title":2286,"path":2287,"stem":2288},"Налаштування та Базовий Роутинг","\u002Fjavascript\u002Freact\u002Freact-router\u002Fsetup-and-basic-routing","03.javascript\u002F04.react\u002F05.react-router\u002F01.setup-and-basic-routing",{"title":2290,"path":2291,"stem":2292},"Динамічна Навігація","\u002Fjavascript\u002Freact\u002Freact-router\u002Fnavigation-and-links","03.javascript\u002F04.react\u002F05.react-router\u002F02.navigation-and-links",{"title":2294,"path":2295,"stem":2296},"Вкладені Маршрути та Макети","\u002Fjavascript\u002Freact\u002Freact-router\u002Fnested-routes-and-layouts","03.javascript\u002F04.react\u002F05.react-router\u002F03.nested-routes-and-layouts",{"title":2298,"path":2299,"stem":2300},"Динамічні Маршрути та Параметри","\u002Fjavascript\u002Freact\u002Freact-router\u002Fdynamic-routing","03.javascript\u002F04.react\u002F05.react-router\u002F04.dynamic-routing",{"title":2302,"path":2303,"stem":2304},"Data APIs: Loaders та Actions","\u002Fjavascript\u002Freact\u002Freact-router\u002Fdata-loading","03.javascript\u002F04.react\u002F05.react-router\u002F05.data-loading",{"title":2306,"path":2307,"stem":2308},"Просунуті Патерни","\u002Fjavascript\u002Freact\u002Freact-router\u002Fadvanced-patterns","03.javascript\u002F04.react\u002F05.react-router\u002F06.advanced-patterns",{"title":2310,"path":2311,"stem":2312},"Legacy Routing: Компонентний підхід","\u002Fjavascript\u002Freact\u002Freact-router\u002Flegacy-routing","03.javascript\u002F04.react\u002F05.react-router\u002F07.legacy-routing",{"title":2314,"icon":132,"path":2315,"stem":2316,"children":2317},"Redux","\u002Fjavascript\u002Freact\u002Fredux","03.javascript\u002F04.react\u002F06.redux\u002Findex",[2318,2320,2336,2365,2374,2395,2411,2440],{"title":2319,"path":2315,"stem":2316},"Redux: Еволюція управління станом",{"title":14,"icon":15,"path":2321,"stem":2322,"children":2323,"page":59},"\u002Fjavascript\u002Freact\u002Fredux\u002Ffundamentals","03.javascript\u002F04.react\u002F06.redux\u002F01.fundamentals",[2324,2328,2332],{"title":2325,"path":2326,"stem":2327},"Вступ до State Management","\u002Fjavascript\u002Freact\u002Fredux\u002Ffundamentals\u002Fintro-state-management","03.javascript\u002F04.react\u002F06.redux\u002F01.fundamentals\u002F01.intro-state-management",{"title":2329,"path":2330,"stem":2331},"Філософія Redux та Три Принципи","\u002Fjavascript\u002Freact\u002Fredux\u002Ffundamentals\u002Fredux-philosophy","03.javascript\u002F04.react\u002F06.redux\u002F01.fundamentals\u002F02.redux-philosophy",{"title":2333,"path":2334,"stem":2335},"Чисті функції та Іммутабельність","\u002Fjavascript\u002Freact\u002Fredux\u002Ffundamentals\u002Fpure-functions-immutability","03.javascript\u002F04.react\u002F06.redux\u002F01.fundamentals\u002F03.pure-functions-immutability",{"title":2337,"icon":132,"path":2338,"stem":2339,"children":2340,"page":59},"Classic Redux","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux",[2341,2345,2349,2353,2357,2361],{"title":2342,"path":2343,"stem":2344},"Створення Store (Classic Redux)","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Fstore-setup","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F01.store-setup",{"title":2346,"path":2347,"stem":2348},"Actions, Constants та Action Creators","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Factions-constants","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F02.actions-constants",{"title":2350,"path":2351,"stem":2352},"Логіка Reducers","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Freducers","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F03.reducers",{"title":2354,"path":2355,"stem":2356},"Комбінування Reducers (Root Reducer)","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Fdata-flow","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F04.data-flow",{"title":2358,"path":2359,"stem":2360},"Підключення до React (React-Redux)","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Freact-redux-connection","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F05.react-redux-connection",{"title":2362,"path":2363,"stem":2364},"Middleware та Асинхронність (Redux Thunk)","\u002Fjavascript\u002Freact\u002Fredux\u002Fclassic-redux\u002Fmiddleware-thunk","03.javascript\u002F04.react\u002F06.redux\u002F02.classic-redux\u002F06.middleware-thunk",{"title":2366,"icon":132,"path":2367,"stem":2368,"children":2369,"page":59},"Transition To Rtk","\u002Fjavascript\u002Freact\u002Fredux\u002Ftransition-to-rtk","03.javascript\u002F04.react\u002F06.redux\u002F03.transition-to-rtk",[2370],{"title":2371,"path":2372,"stem":2373},"Проблеми класичного Redux","\u002Fjavascript\u002Freact\u002Fredux\u002Ftransition-to-rtk\u002Fproblems-with-classic","03.javascript\u002F04.react\u002F06.redux\u002F03.transition-to-rtk\u002F01.problems-with-classic",{"title":2375,"icon":132,"path":2376,"stem":2377,"children":2378,"page":59},"Redux Toolkit","\u002Fjavascript\u002Freact\u002Fredux\u002Fredux-toolkit","03.javascript\u002F04.react\u002F06.redux\u002F04.redux-toolkit",[2379,2383,2387,2391],{"title":2380,"path":2381,"stem":2382},"Налаштування Store з configureStore","\u002Fjavascript\u002Freact\u002Fredux\u002Fredux-toolkit\u002Fconfigure-store","03.javascript\u002F04.react\u002F06.redux\u002F04.redux-toolkit\u002F01.configure-store",{"title":2384,"path":2385,"stem":2386},"createSlice: Революція в Redux","\u002Fjavascript\u002Freact\u002Fredux\u002Fredux-toolkit\u002Fcreate-slice","03.javascript\u002F04.react\u002F06.redux\u002F04.redux-toolkit\u002F02.create-slice",{"title":2388,"path":2389,"stem":2390},"Асинхронність з createAsyncThunk","\u002Fjavascript\u002Freact\u002Fredux\u002Fredux-toolkit\u002Fasync-thunks","03.javascript\u002F04.react\u002F06.redux\u002F04.redux-toolkit\u002F03.async-thunks",{"title":2392,"path":2393,"stem":2394},"04. Entity Adapter: Керування нормалізованим станом","\u002Fjavascript\u002Freact\u002Fredux\u002Fredux-toolkit\u002Fentity-adapter","03.javascript\u002F04.react\u002F06.redux\u002F04.redux-toolkit\u002F04.entity-adapter",{"title":2396,"icon":92,"path":2397,"stem":2398,"children":2399,"page":59},"Advanced","\u002Fjavascript\u002Freact\u002Fredux\u002Fadvanced","03.javascript\u002F04.react\u002F06.redux\u002F05.advanced",[2400,2404,2408],{"title":2401,"path":2402,"stem":2403},"Мемоізація та Селектори: Повний Гайд по Reselect","\u002Fjavascript\u002Freact\u002Fredux\u002Fadvanced\u002Fselectors-reselect","03.javascript\u002F04.react\u002F06.redux\u002F05.advanced\u002F01.selectors-reselect",{"title":2405,"path":2406,"stem":2407},"RTK Query: Архітектура Серверного Кешу","\u002Fjavascript\u002Freact\u002Fredux\u002Fadvanced\u002Frtk-query-intro","03.javascript\u002F04.react\u002F06.redux\u002F05.advanced\u002F02.rtk-query-intro",{"title":2255,"path":2409,"stem":2410},"\u002Fjavascript\u002Freact\u002Fredux\u002Fadvanced\u002Farchitecture-best-practices","03.javascript\u002F04.react\u002F06.redux\u002F05.advanced\u002F03.architecture-best-practices",{"title":2412,"icon":132,"path":2413,"stem":2414,"children":2415,"page":59},"Project Kanban","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban",[2416,2420,2424,2428,2432,2436],{"title":2417,"path":2418,"stem":2419},"Проєкт: Kanban Board (Trello Clone)","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Fproject-overview","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F01.project-overview",{"title":2421,"path":2422,"stem":2423},"Налаштування та Типізація","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Fsetup-and-types","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F02.setup-and-types",{"title":2425,"path":2426,"stem":2427},"Board Slice: Серце Дошки","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Fboard-slice","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F03.board-slice",{"title":2429,"path":2430,"stem":2431},"Логіка Drag & Drop","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Fdrag-and-drop-logic","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F04.drag-and-drop-logic",{"title":2433,"path":2434,"stem":2435},"Інтеграція з RTK Query","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Frtk-query-integration","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F05.rtk-query-integration",{"title":2437,"path":2438,"stem":2439},"Optimistic Updates","\u002Fjavascript\u002Freact\u002Fredux\u002Fproject-kanban\u002Foptimistic-updates","03.javascript\u002F04.react\u002F06.redux\u002F06.project-kanban\u002F06.optimistic-updates",{"title":2441,"icon":132,"path":2442,"stem":2443,"children":2444,"page":59},"Testing","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting","03.javascript\u002F04.react\u002F06.redux\u002F07.testing",[2445,2449,2453,2457,2461],{"title":2446,"path":2447,"stem":2448},"Тестування Redux","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting\u002Fintro-testing","03.javascript\u002F04.react\u002F06.redux\u002F07.testing\u002F01.intro-testing",{"title":2450,"path":2451,"stem":2452},"Тестування Reducers","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting\u002Ftesting-reducers","03.javascript\u002F04.react\u002F06.redux\u002F07.testing\u002F02.testing-reducers",{"title":2454,"path":2455,"stem":2456},"Тестування Селекторів","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting\u002Ftesting-selectors","03.javascript\u002F04.react\u002F06.redux\u002F07.testing\u002F03.testing-selectors",{"title":2458,"path":2459,"stem":2460},"Тестування Компонентів (Integration)","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting\u002Ftesting-components","03.javascript\u002F04.react\u002F06.redux\u002F07.testing\u002F04.testing-components",{"title":2462,"path":2463,"stem":2464},"Тестування Async Thunks","\u002Fjavascript\u002Freact\u002Fredux\u002Ftesting\u002Ftesting-thunks","03.javascript\u002F04.react\u002F06.redux\u002F07.testing\u002F05.testing-thunks",{"title":2466,"icon":132,"path":2467,"stem":2468,"children":2469},"Ui Libraries","\u002Fjavascript\u002Freact\u002Fui-libraries","03.javascript\u002F04.react\u002F07.ui-libraries\u002Findex",[2470,2472,2476,2480,2484,2488,2492],{"title":2471,"path":2467,"stem":2468},"UI Бібліотеки в React",{"title":2473,"path":2474,"stem":2475},"Вступ до UI Бібліотек: Навіщо Винаходити Велосипед Двічі?","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fintroduction-to-ui-libraries","03.javascript\u002F04.react\u002F07.ui-libraries\u002F01.introduction-to-ui-libraries",{"title":2477,"path":2478,"stem":2479},"Філософія shadcn\u002Fui: \"Not a Component Library\"","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fshadcn-philosophy","03.javascript\u002F04.react\u002F07.ui-libraries\u002F02.shadcn-philosophy",{"title":2481,"path":2482,"stem":2483},"Установка та Налаштування shadcn\u002Fui","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fshadcn-installation","03.javascript\u002F04.react\u002F07.ui-libraries\u002F03.shadcn-installation",{"title":2485,"path":2486,"stem":2487},"Базові Компоненти shadcn\u002Fui: Фундамент Інтерфейсу","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fshadcn-components-basics","03.javascript\u002F04.react\u002F07.ui-libraries\u002F04.shadcn-components-basics",{"title":2489,"path":2490,"stem":2491},"Компоненти Форм: Побудова Інтерактивних Form","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fshadcn-components-forms","03.javascript\u002F04.react\u002F07.ui-libraries\u002F05.shadcn-components-forms",{"title":2493,"path":2494,"stem":2495},"Складні Компоненти: Dialog, Dropdown, Table та Command","\u002Fjavascript\u002Freact\u002Fui-libraries\u002Fshadcn-components-advanced","03.javascript\u002F04.react\u002F07.ui-libraries\u002F06.shadcn-components-advanced",{"title":2497,"icon":2498,"path":2499,"stem":2500,"children":2501,"page":59},"TypeScript","i-devicon-typescript","\u002Fjavascript\u002Ftypescript","03.javascript\u002F05.typescript",[2502,2506,2510,2514,2518,2522,2526,2530],{"title":2503,"path":2504,"stem":2505},"TypeScript: Броня для вашого коду","\u002Fjavascript\u002Ftypescript\u002Fintro-and-basic-types","03.javascript\u002F05.typescript\u002F01.intro-and-basic-types",{"title":2507,"path":2508,"stem":2509},"Майстерність Моделювання Даних: Інтерфейси та Просунуті Типи","\u002Fjavascript\u002Ftypescript\u002Finterfaces-and-advanced-types","03.javascript\u002F05.typescript\u002F02.interfaces-and-advanced-types",{"title":2511,"path":2512,"stem":2513},"Алхімія Типів: Generics та Utility Types","\u002Fjavascript\u002Ftypescript\u002Fgenerics-and-utilities","03.javascript\u002F05.typescript\u002F03.generics-and-utilities",{"title":2515,"path":2516,"stem":2517},"Архітектура та Шаблони: Класи в TypeScript","\u002Fjavascript\u002Ftypescript\u002Fclasses-and-oop","03.javascript\u002F05.typescript\u002F04.classes-and-oop",{"title":2519,"path":2520,"stem":2521},"Продакшн та Екосистема: Advanced Config & Workflow","\u002Fjavascript\u002Ftypescript\u002Fadvanced-patterns-and-config","03.javascript\u002F05.typescript\u002F05.advanced-patterns-and-config",{"title":2523,"path":2524,"stem":2525},"TypeScript у світі React","\u002Fjavascript\u002Ftypescript\u002Freact-basics","03.javascript\u002F05.typescript\u002F06.react-basics",{"title":2527,"path":2528,"stem":2529},"React + TypeScript: Продвинуті патерни","\u002Fjavascript\u002Ftypescript\u002Freact-advanced","03.javascript\u002F05.typescript\u002F07.react-advanced",{"title":2531,"path":2532,"stem":2533},"React + TypeScript: Екосистема та бібліотеки","\u002Fjavascript\u002Ftypescript\u002Freact-ecosystem","03.javascript\u002F05.typescript\u002F08.react-ecosystem",{"title":2535,"icon":2536,"path":2537,"stem":2538,"children":2539,"page":59},"Асинхронність","i-lucide-refresh-cw","\u002Fjavascript\u002Fasync-programming","03.javascript\u002F06.async-programming",[2540,2544,2548],{"title":2541,"path":2542,"stem":2543},"Event Loop: серце асинхронності в JavaScript","\u002Fjavascript\u002Fasync-programming\u002Fevent-loop-fundamentals","03.javascript\u002F06.async-programming\u002F01.event-loop-fundamentals",{"title":2545,"path":2546,"stem":2547},"Task Queue та Microtask Queue: пріоритети виконання","\u002Fjavascript\u002Fasync-programming\u002Ftask-queues","03.javascript\u002F06.async-programming\u002F02.task-queues",{"title":2549,"path":2550,"stem":2551},"Асинхронні патерни: від Callbacks до Async\u002FAwait","\u002Fjavascript\u002Fasync-programming\u002Fasync-patterns","03.javascript\u002F06.async-programming\u002F03.async-patterns",{"title":2553,"path":2554,"stem":2555},"Atomic Design","\u002Fjavascript\u002Fatomic-design","03.javascript\u002F2.atomic-design",{"title":2557,"icon":2558,"path":2559,"stem":2560,"children":2561,"page":59},"Java","i-devicon-java","\u002Fjava","04.java",[2562,2565,2568,2572,2576,2580,2584],{"title":162,"path":2563,"stem":2564},"\u002Fjava\u002Fdata-mapper-part1","04.java\u002F01.data-mapper-part1",{"title":166,"path":2566,"stem":2567},"\u002Fjava\u002Fdata-mapper-part2","04.java\u002F02.data-mapper-part2",{"title":2569,"path":2570,"stem":2571},"Service Layer: Організація бізнес-логіки","\u002Fjava\u002Fservice-layer","04.java\u002F03.service-layer",{"title":2573,"path":2574,"stem":2575},"Rich Domain Model та State Pattern","\u002Fjava\u002Frich-domain-model","04.java\u002F04.rich-domain-model",{"title":2577,"path":2578,"stem":2579},"Патерни для складної бізнес-логіки","\u002Fjava\u002Fbusiness-logic-patterns","04.java\u002F05.business-logic-patterns",{"title":2581,"path":2582,"stem":2583},"Обробка помилок та валідація","\u002Fjava\u002Ferror-handling-validation","04.java\u002F06.error-handling-validation",{"title":2585,"path":2586,"stem":2587,"children":2588,"page":59},"Проектування баз даних","\u002Fjava\u002Fpr2","04.java\u002Fpr2",[2589,2593,2597,2601,2605,2609,2613,2617,2621,2625,2629,2633,2637,2641,2645,2649,2653,2657,2661,2665,2669,2673,2677,2681,2685,2689,2693,2697,2701,2705,2709,2713,2717,2721,2725,2729,2733],{"title":2590,"path":2591,"stem":2592},"Концептуальне моделювання: Мистецтво розуміння предметної області","\u002Fjava\u002Fpr2\u002Fconceptual-modeling","04.java\u002Fpr2\u002F01.conceptual-modeling",{"title":2594,"path":2595,"stem":2596},"Логічне моделювання: Від бізнес-ідей до структур даних","\u002Fjava\u002Fpr2\u002Flogical-modeling","04.java\u002Fpr2\u002F02.logical-modeling",{"title":2598,"path":2599,"stem":2600},"Нормалізація: Гігієна даних та боротьба з аномаліями","\u002Fjava\u002Fpr2\u002Fnormalization","04.java\u002Fpr2\u002F03.normalization",{"title":2602,"path":2603,"stem":2604},"Фізична схема: Від абстракції до DDL","\u002Fjava\u002Fpr2\u002Fphysical-schema","04.java\u002Fpr2\u002F04.physical-schema",{"title":2606,"path":2607,"stem":2608},"Архітектурна класифікація таблиць","\u002Fjava\u002Fpr2\u002Ftable-classification","04.java\u002Fpr2\u002F05.table-classification",{"title":2610,"path":2611,"stem":2612},"Database Migrations: Версіонування схеми з Flyway","\u002Fjava\u002Fpr2\u002Fdatabase-migrations","04.java\u002Fpr2\u002F06.database-migrations",{"title":2614,"path":2615,"stem":2616},"А що, якби це була не реляційна БД?","\u002Fjava\u002Fpr2\u002Fbeyond-relational","04.java\u002Fpr2\u002F07.beyond-relational",{"title":2618,"path":2619,"stem":2620},"Object-Relational Impedance Mismatch: Два світи, що не хочуть дружити","\u002Fjava\u002Fpr2\u002Fimpedance-mismatch","04.java\u002Fpr2\u002F09.impedance-mismatch",{"title":2622,"path":2623,"stem":2624},"JDBC: Перший контакт із базою даних","\u002Fjava\u002Fpr2\u002Fjdbc-fundamentals","04.java\u002Fpr2\u002F10.jdbc-fundamentals",{"title":2626,"path":2627,"stem":2628},"Якість коду: Spotless, SpotBugs та SonarQube","\u002Fjava\u002Fpr2\u002F10a.code-quality","04.java\u002Fpr2\u002F10a.code-quality",{"title":2630,"path":2631,"stem":2632},"Connection Pool: Патерн Object Pool для JDBC-з'єднань","\u002Fjava\u002Fpr2\u002Fconnection-pool","04.java\u002Fpr2\u002F11.connection-pool",{"title":2634,"path":2635,"stem":2636},"Row Data Gateway: Об'єкт як обгортка рядка таблиці","\u002Fjava\u002Fpr2\u002Frow-data-gateway","04.java\u002Fpr2\u002F12.row-data-gateway",{"title":2638,"path":2639,"stem":2640},"Table Data Gateway: Фасад таблиці як архітектурний відступ","\u002Fjava\u002Fpr2\u002Ftable-data-gateway","04.java\u002Fpr2\u002F13.table-data-gateway",{"title":2642,"path":2643,"stem":2644},"Repository + Data Mapper: Правильна шарова архітектура з JDBC","\u002Fjava\u002Fpr2\u002Frepository-data-mapper","04.java\u002Fpr2\u002F14.repository-data-mapper",{"title":2646,"path":2647,"stem":2648},"Identity Map: Кешування сутностей у рамках сесії","\u002Fjava\u002Fpr2\u002Fidentity-map","04.java\u002Fpr2\u002F15.identity-map",{"title":2650,"path":2651,"stem":2652},"Unit of Work: Відстеження змін і координація JDBC-транзакцій","\u002Fjava\u002Fpr2\u002Funit-of-work","04.java\u002Fpr2\u002F16.unit-of-work",{"title":2654,"path":2655,"stem":2656},"Strategy: Замінювані SQL-стратегії для підтримки різних СУБД","\u002Fjava\u002Fpr2\u002Fstrategy-sql","04.java\u002Fpr2\u002F17.strategy-sql",{"title":2658,"path":2659,"stem":2660},"Proxy: Lazy Loading для One-To-Many колекцій","\u002Fjava\u002Fpr2\u002Fproxy-lazy-loading","04.java\u002Fpr2\u002F18.proxy-lazy-loading",{"title":2662,"path":2663,"stem":2664},"Generic Repository через Java Reflection: анотації та динамічний SQL","\u002Fjava\u002Fpr2\u002Fgeneric-repository-reflection","04.java\u002Fpr2\u002F19.generic-repository-reflection",{"title":2666,"path":2667,"stem":2668},"Specification Pattern: Композиція бізнес-правил для складних запитів","\u002Fjava\u002Fpr2\u002Fspecification-pattern","04.java\u002Fpr2\u002F20.specification-pattern",{"title":2670,"path":2671,"stem":2672},"Розширені можливості Specification Pattern: підзапити, агрегації та гібридний підхід","\u002Fjava\u002Fpr2\u002F20a.advanced-specifications","04.java\u002Fpr2\u002F20a.advanced-specifications",{"title":2674,"path":2675,"stem":2676},"Асинхронність у JDBC: Від блокуючих викликів до CompletableFuture","\u002Fjava\u002Fpr2\u002Fasynchronous-jdbc","04.java\u002Fpr2\u002F21.asynchronous-jdbc",{"title":2678,"path":2679,"stem":2680},"Інтеграційне тестування JDBC-репозиторіїв: Embedded H2 та патерн AAA","\u002Fjava\u002Fpr2\u002Fintegration-testing-h2","04.java\u002Fpr2\u002F22.integration-testing-h2",{"title":2682,"path":2683,"stem":2684},"Testcontainers: Тестування з реальною PostgreSQL у Docker-контейнерах","\u002Fjava\u002Fpr2\u002Fintegration-testing-testcontainers","04.java\u002Fpr2\u002F23.integration-testing-testcontainers",{"title":2686,"path":2687,"stem":2688},"Google Guice: Впровадження залежностей у JavaFX-проєкті","\u002Fjava\u002Fpr2\u002Fdependency-injection-guice","04.java\u002Fpr2\u002F24.dependency-injection-guice",{"title":2690,"path":2691,"stem":2692},"JavaFX: Основи побудови графічних інтерфейсів","\u002Fjava\u002Fpr2\u002Fjavafx-fundamentals","04.java\u002Fpr2\u002F25.javafx-fundamentals",{"title":2694,"path":2695,"stem":2696},"Properties та Bindings: Реактивність у JavaFX","\u002Fjava\u002Fpr2\u002Fjavafx-properties-bindings","04.java\u002Fpr2\u002F26.javafx-properties-bindings",{"title":2698,"path":2699,"stem":2700},"MVC vs MVP vs MVVM: Еволюція архітектурних патернів UI","\u002Fjava\u002Fpr2\u002Fui-architecture-patterns","04.java\u002Fpr2\u002F27.ui-architecture-patterns",{"title":2702,"path":2703,"stem":2704},"MVVM на практиці: Побудова ViewModel","\u002Fjava\u002Fpr2\u002Fmvvm-viewmodel-implementation","04.java\u002Fpr2\u002F28.mvvm-viewmodel-implementation",{"title":2706,"path":2707,"stem":2708},"View та Controller: Зв'язування з ViewModel через FXML","\u002Fjava\u002Fpr2\u002Fmvvm-view-controller","04.java\u002Fpr2\u002F29.mvvm-view-controller",{"title":2710,"path":2711,"stem":2712},"Інтеграція MVVM з Guice: Автоматична ін'єкція залежностей","\u002Fjava\u002Fpr2\u002Fmvvm-guice-integration","04.java\u002Fpr2\u002F30.mvvm-guice-integration",{"title":2714,"path":2715,"stem":2716},"Валідація та обробка помилок у MVVM","\u002Fjava\u002Fpr2\u002Fmvvm-validation-error-handling","04.java\u002Fpr2\u002F31.mvvm-validation-error-handling",{"title":2718,"path":2719,"stem":2720},"Навігація та управління екранами у JavaFX MVVM","\u002Fjava\u002Fpr2\u002Fmvvm-navigation-screen-management","04.java\u002Fpr2\u002F32.mvvm-navigation-screen-management",{"title":2722,"path":2723,"stem":2724},"Тестування JavaFX MVVM-додатків","\u002Fjava\u002Fpr2\u002Fmvvm-testing","04.java\u002Fpr2\u002F33.mvvm-testing",{"title":2726,"path":2727,"stem":2728},"Стилізація та теми у JavaFX: CSS та User Experience","\u002Fjava\u002Fpr2\u002Fjavafx-styling-themes","04.java\u002Fpr2\u002F34.javafx-styling-themes",{"title":2730,"path":2731,"stem":2732},"AtlantaFX: Сучасні теми для JavaFX додатків","\u002Fjava\u002Fpr2\u002Fatlantafx-modern-themes","04.java\u002Fpr2\u002F35.atlantafx-modern-themes",{"title":2734,"path":2735,"stem":2736},"Пакування та розповсюдження JavaFX-додатків","\u002Fjava\u002Fpr2\u002Fjar-packaging-distribution","04.java\u002Fpr2\u002F36.jar-packaging-distribution",{"title":2738,"icon":2739,"path":2740,"stem":2741,"children":2742,"page":59},"Python","i-devicon-python","\u002Fpython","05.python",[2743,2747,2750,2754,2758,2762,2766,2770,2774,2778,2782,2786,2790,2794,2798,2859],{"title":2744,"path":2745,"stem":2746},"Модулі, Пакети та Віртуальні Середовища","\u002Fpython\u002Fmodules-packages-venv","05.python\u002F00.modules-packages-venv",{"title":71,"path":2748,"stem":2749},"\u002Fpython\u002Fclasses-objects","05.python\u002F01.classes-objects",{"title":2751,"path":2752,"stem":2753},"Інкапсуляція, Керування Доступом та Властивості","\u002Fpython\u002Fencapsulation","05.python\u002F02.encapsulation",{"title":2755,"path":2756,"stem":2757},"Наслідування, MRO та суперсила super()","\u002Fpython\u002Finheritance-mro","05.python\u002F03.inheritance-mro",{"title":2759,"path":2760,"stem":2761},"Абстракція — ABC проти Статичних Протоколів (PEP 544)","\u002Fpython\u002Fabstraction-protocols","05.python\u002F04.abstraction-protocols",{"title":2763,"path":2764,"stem":2765},"Магічні методи (Dunder) та Емуляція протоколів","\u002Fpython\u002Fdunder-methods","05.python\u002F05.dunder-methods",{"title":2767,"path":2768,"stem":2769},"Декоратори та Керування життєвим циклом методів","\u002Fpython\u002Fdecorators-static-class","05.python\u002F06.decorators-static-class",{"title":2771,"path":2772,"stem":2773},"Дескриптори — Магія доступу до атрибутів","\u002Fpython\u002Fdescriptors","05.python\u002F07.descriptors",{"title":2775,"path":2776,"stem":2777},"Метакласи — Динамічне створення класів під капотом CPython","\u002Fpython\u002Fmetaclasses","05.python\u002F08.metaclasses",{"title":2779,"path":2780,"stem":2781},"Dataclasses, NamedTuple та сучасні контейнери Python","\u002Fpython\u002Fmodern-containers","05.python\u002F09.modern-containers",{"title":2783,"path":2784,"stem":2785},"GIL та модель конкурентності CPython — фундамент перед потоками і процесами","\u002Fpython\u002Fgil-concurrency-intro","05.python\u002F11.gil-concurrency-intro",{"title":2787,"path":2788,"stem":2789},"Threading — конкурентність для I\u002FO-bound задач","\u002Fpython\u002Fthreading","05.python\u002F12.threading",{"title":2791,"path":2792,"stem":2793},"Multiprocessing — справжній паралелізм для CPU-bound задач","\u002Fpython\u002Fmultiprocessing","05.python\u002F13.multiprocessing",{"title":2795,"path":2796,"stem":2797},"asyncio — кооперативна конкурентність та event loop","\u002Fpython\u002Fasyncio","05.python\u002F14.asyncio",{"title":2799,"icon":92,"path":2800,"stem":2801,"children":2802,"page":59},"FastAPI","\u002Fpython\u002Ffastapi","05.python\u002Ffastapi",[2803,2807,2811,2815,2819,2823,2827,2831,2835,2839,2843,2847,2851,2855],{"title":2804,"path":2805,"stem":2806},"Глибокий Typing та Pydantic v2 — від анотацій до валідації","\u002Fpython\u002Ffastapi\u002Ftyping-pydantic","05.python\u002Ffastapi\u002F15.typing-pydantic",{"title":2808,"path":2809,"stem":2810},"WSGI, ASGI та Python Web-екосистема","\u002Fpython\u002Ffastapi\u002Fwsgi-asgi-ecosystem","05.python\u002Ffastapi\u002F16.wsgi-asgi-ecosystem",{"title":2812,"path":2813,"stem":2814},"FastAPI: Перший додаток, Uvicorn та OpenAPI","\u002Fpython\u002Ffastapi\u002Ffastapi-intro","05.python\u002Ffastapi\u002F17.fastapi-intro",{"title":2816,"path":2817,"stem":2818},"Маршрутизація, параметри запитів та APIRouter","\u002Fpython\u002Ffastapi\u002Ffastapi-routing-params","05.python\u002Ffastapi\u002F18.fastapi-routing-params",{"title":2820,"path":2821,"stem":2822},"Pydantic v2 у FastAPI — схеми, валідація та серіалізація","\u002Fpython\u002Ffastapi\u002Ffastapi-pydantic-schemas","05.python\u002Ffastapi\u002F19.fastapi-pydantic-schemas",{"title":2824,"path":2825,"stem":2826},"Dependency Injection — серце архітектури FastAPI","\u002Fpython\u002Ffastapi\u002Ffastapi-dependency-injection","05.python\u002Ffastapi\u002F20.fastapi-dependency-injection",{"title":2828,"path":2829,"stem":2830},"Обробка помилок, Middleware та CORS у FastAPI","\u002Fpython\u002Ffastapi\u002Ffastapi-errors-middleware","05.python\u002Ffastapi\u002F21.fastapi-errors-middleware",{"title":2832,"path":2833,"stem":2834},"SQLAlchemy 2.0 — ORM, Core та Async Engine","\u002Fpython\u002Ffastapi\u002Fsqlalchemy-orm","05.python\u002Ffastapi\u002F22.sqlalchemy-orm",{"title":2836,"path":2837,"stem":2838},"Alembic — міграції бази даних","\u002Fpython\u002Ffastapi\u002Falembic-migrations","05.python\u002Ffastapi\u002F23.alembic-migrations",{"title":2840,"path":2841,"stem":2842},"Repository Pattern та Clean Architecture у FastAPI","\u002Fpython\u002Ffastapi\u002Ffastapi-repository-clean-arch","05.python\u002Ffastapi\u002F24.fastapi-repository-clean-arch",{"title":2844,"path":2845,"stem":2846},"Автентифікація та авторизація — JWT, OAuth2, RBAC","\u002Fpython\u002Ffastapi\u002Ffastapi-auth-security","05.python\u002Ffastapi\u002F25.fastapi-auth-security",{"title":2848,"path":2849,"stem":2850},"Тестування FastAPI — pytest, httpx, fixtures","\u002Fpython\u002Ffastapi\u002Ffastapi-testing","05.python\u002Ffastapi\u002F26.fastapi-testing",{"title":2852,"path":2853,"stem":2854},"Async на повну — Background Tasks, WebSockets, SSE та Celery","\u002Fpython\u002Ffastapi\u002Ffastapi-async-advanced","05.python\u002Ffastapi\u002F27.fastapi-async-advanced",{"title":2856,"path":2857,"stem":2858},"Deployment — Docker, CI\u002FCD, Monitoring","\u002Fpython\u002Ffastapi\u002Ffastapi-deployment","05.python\u002Ffastapi\u002F28.fastapi-deployment",{"title":2860,"path":2861,"stem":2862},"[object Object]","\u002Fpython\u002Foop-plan","05.python\u002Foop-plan",{"title":2864,"icon":2865,"path":2866,"stem":2867,"children":2868,"page":59},"Бази даних","i-lucide-database","\u002Fdatabases","06.databases",[2869,2899,2922,2959,2988,3006,3040,3052,3061],{"title":2870,"icon":2871,"path":2872,"stem":2873,"children":2874,"page":59},"Intro","i-lucide-play","\u002Fdatabases\u002Fintro","06.databases\u002F01.intro",[2875,2879,2883,2887,2891,2895],{"title":2876,"path":2877,"stem":2878},"Введення в теорію баз даних","\u002Fdatabases\u002Fintro\u002Fintroduction-to-databases","06.databases\u002F01.intro\u002F01.introduction-to-databases",{"title":2880,"path":2881,"stem":2882},"Реляційна модель даних","\u002Fdatabases\u002Fintro\u002Frelational-model-theory","06.databases\u002F01.intro\u002F02.relational-model-theory",{"title":2884,"path":2885,"stem":2886},"ER-моделювання","\u002Fdatabases\u002Fintro\u002Fer-modeling","06.databases\u002F01.intro\u002F03.er-modeling",{"title":2888,"path":2889,"stem":2890},"Логічне проектування БД","\u002Fdatabases\u002Fintro\u002Flogical-schema","06.databases\u002F01.intro\u002F04.logical-schema",{"title":2892,"path":2893,"stem":2894},"Класифікація таблиць","\u002Fdatabases\u002Fintro\u002Ftable-classification","06.databases\u002F01.intro\u002F05.table-classification",{"title":2896,"path":2897,"stem":2898},"PlantUML для баз даних","\u002Fdatabases\u002Fintro\u002Fplantuml-diagrams","06.databases\u002F01.intro\u002F06.plantuml-diagrams",{"title":2900,"icon":2865,"path":2901,"stem":2902,"children":2903,"page":59},"MS SQL Server Start","\u002Fdatabases\u002Fms-sql-server-start","06.databases\u002F02.ms-sql-server-start",[2904,2908,2914,2918],{"title":2905,"path":2906,"stem":2907},"Типи даних у MS SQL Server","\u002Fdatabases\u002Fms-sql-server-start\u002Fdata-types","06.databases\u002F02.ms-sql-server-start\u002F01.data-types",{"title":2909,"path":2910,"stem":2911,"children":2912},"Індекси у MS SQL Server","\u002Fdatabases\u002Fms-sql-server-start\u002Fsql-indexes","06.databases\u002F02.ms-sql-server-start\u002F02.sql-indexes",[2913],{"title":2909,"path":2910,"stem":2911},{"title":2915,"path":2916,"stem":2917},"Системні бази даних MS SQL Server","\u002Fdatabases\u002Fms-sql-server-start\u002Fsystem-databases","06.databases\u002F02.ms-sql-server-start\u002F03.system-databases",{"title":2919,"path":2920,"stem":2921},"Огляд мови SQL та запитів","\u002Fdatabases\u002Fms-sql-server-start\u002Fsql-queries-overview","06.databases\u002F02.ms-sql-server-start\u002F04.sql-queries-overview",{"title":2923,"icon":2865,"path":2924,"stem":2925,"children":2926,"page":59},"SQL","\u002Fdatabases\u002Fsql","06.databases\u002F03.sql",[2927,2931,2935,2939,2943,2947,2951,2955],{"title":2928,"path":2929,"stem":2930},"Налаштування демонстраційної бази даних","\u002Fdatabases\u002Fsql\u002Fsample-database-setup","06.databases\u002F03.sql\u002F00.sample-database-setup",{"title":2932,"path":2933,"stem":2934},"DDL - Створення таблиць (CREATE TABLE)","\u002Fdatabases\u002Fsql\u002Fddl-create-table","06.databases\u002F03.sql\u002F01.ddl-create-table",{"title":2936,"path":2937,"stem":2938},"DDL - Зміна та видалення таблиць (ALTER, DROP)","\u002Fdatabases\u002Fsql\u002Fddl-alter-drop-table","06.databases\u002F03.sql\u002F02.ddl-alter-drop-table",{"title":2940,"path":2941,"stem":2942},"SELECT запити - Основи","\u002Fdatabases\u002Fsql\u002Fselect-queries-fundamentals","06.databases\u002F03.sql\u002F03.select-queries-fundamentals",{"title":2944,"path":2945,"stem":2946},"SELECT запити - Розширені можливості","\u002Fdatabases\u002Fsql\u002Fselect-queries-advanced","06.databases\u002F03.sql\u002F04.select-queries-advanced",{"title":2948,"path":2949,"stem":2950},"INSERT запити - Додавання даних","\u002Fdatabases\u002Fsql\u002Finsert-queries","06.databases\u002F03.sql\u002F05.insert-queries",{"title":2952,"path":2953,"stem":2954},"UPDATE та DELETE запити","\u002Fdatabases\u002Fsql\u002Fupdate-delete-queries","06.databases\u002F03.sql\u002F06.update-delete-queries",{"title":2956,"path":2957,"stem":2958},"Транзакції в SQL","\u002Fdatabases\u002Fsql\u002Ftransactions","06.databases\u002F03.sql\u002F07.transactions",{"title":2960,"icon":2865,"path":2961,"stem":2962,"children":2963,"page":59},"Multi Table Databases","\u002Fdatabases\u002Fmulti-table-databases","06.databases\u002F04.multi-table-databases",[2964,2968,2972,2976,2980,2984],{"title":2965,"path":2966,"stem":2967},"Зв'язки та нормалізація БД","\u002Fdatabases\u002Fmulti-table-databases\u002Frelationships-and-normalization","06.databases\u002F04.multi-table-databases\u002F00.relationships-and-normalization",{"title":2969,"path":2970,"stem":2971},"INNER JOIN - З'єднання таблиць","\u002Fdatabases\u002Fmulti-table-databases\u002Finner-join","06.databases\u002F04.multi-table-databases\u002F01.inner-join",{"title":2973,"path":2974,"stem":2975},"OUTER JOINs - LEFT, RIGHT, FULL","\u002Fdatabases\u002Fmulti-table-databases\u002Fouter-joins","06.databases\u002F04.multi-table-databases\u002F02.outer-joins",{"title":2977,"path":2978,"stem":2979},"CROSS та SELF JOINs","\u002Fdatabases\u002Fmulti-table-databases\u002Fcross-self-joins","06.databases\u002F04.multi-table-databases\u002F03.cross-self-joins",{"title":2981,"path":2982,"stem":2983},"Підзапити (Subqueries)","\u002Fdatabases\u002Fmulti-table-databases\u002Fsubqueries","06.databases\u002F04.multi-table-databases\u002F04.subqueries",{"title":2985,"path":2986,"stem":2987},"Агрегації з JOIN","\u002Fdatabases\u002Fmulti-table-databases\u002Faggregations-with-joins","06.databases\u002F04.multi-table-databases\u002F05.aggregations-with-joins",{"title":2989,"icon":2990,"path":2991,"stem":2992,"children":2993,"page":59},"Aggregate Functions","i-lucide-calculator","\u002Fdatabases\u002Faggregate-functions","06.databases\u002F05.aggregate-functions",[2994,2998,3002],{"title":2995,"path":2996,"stem":2997},"Функції агрегування в MS SQL Server","\u002Fdatabases\u002Faggregate-functions\u002Fintroduction-aggregate-functions","06.databases\u002F05.aggregate-functions\u002F01.introduction-aggregate-functions",{"title":2999,"path":3000,"stem":3001},"Групування даних в MS SQL Server","\u002Fdatabases\u002Faggregate-functions\u002Fgrouping-data","06.databases\u002F05.aggregate-functions\u002F02.grouping-data",{"title":3003,"path":3004,"stem":3005},"Підзапити з агрегатними функціями","\u002Fdatabases\u002Faggregate-functions\u002Fsubqueries-aggregates","06.databases\u002F05.aggregate-functions\u002F03.subqueries-aggregates",{"title":3007,"icon":3008,"path":3009,"stem":3010,"children":3011,"page":59},"Тригери та зберігаємі процедури","i-lucide-database-zap","\u002Fdatabases\u002Ftriggers-stored-procedures","06.databases\u002F07.triggers-stored-procedures",[3012,3016,3020,3024,3028,3032,3036],{"title":3013,"path":3014,"stem":3015},"DML-тригери","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Fdml-triggers","06.databases\u002F07.triggers-stored-procedures\u002F01.dml-triggers",{"title":3017,"path":3018,"stem":3019},"DDL-тригери","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Fddl-triggers","06.databases\u002F07.triggers-stored-procedures\u002F02.ddl-triggers",{"title":3021,"path":3022,"stem":3023},"Transact-SQL розширення","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Ftransact-sql-extensions","06.databases\u002F07.triggers-stored-procedures\u002F03.transact-sql-extensions",{"title":3025,"path":3026,"stem":3027},"Транзакції","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Ftransactions","06.databases\u002F07.triggers-stored-procedures\u002F04.transactions",{"title":3029,"path":3030,"stem":3031},"Зберігаємі процедури","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Fstored-procedures","06.databases\u002F07.triggers-stored-procedures\u002F05.stored-procedures",{"title":3033,"path":3034,"stem":3035},"Користувацькі функції","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Fuser-defined-functions","06.databases\u002F07.triggers-stored-procedures\u002F06.user-defined-functions",{"title":3037,"path":3038,"stem":3039},"Безпека баз даних","\u002Fdatabases\u002Ftriggers-stored-procedures\u002Fsecurity","06.databases\u002F07.triggers-stored-procedures\u002F08.security",{"title":3037,"icon":793,"path":3041,"stem":3042,"children":3043,"page":59},"\u002Fdatabases\u002Fsecurity","06.databases\u002F08.security",[3044,3048],{"title":3045,"path":3046,"stem":3047},"Вступ до безпеки баз даних","\u002Fdatabases\u002Fsecurity\u002Fintroduction","06.databases\u002F08.security\u002F01.introduction",{"title":3049,"path":3050,"stem":3051},"Системні представлення та метадані","\u002Fdatabases\u002Fsecurity\u002Fsystem-views","06.databases\u002F08.security\u002F02.system-views",{"title":3053,"icon":3054,"path":3055,"stem":3056,"children":3057,"page":59},"Резервне копіювання та відновлення","i-lucide-database-backup","\u002Fdatabases\u002Fbackup-recovery","06.databases\u002F09.backup-recovery",[3058],{"title":3053,"path":3059,"stem":3060},"\u002Fdatabases\u002Fbackup-recovery\u002Fbackup-restore","06.databases\u002F09.backup-recovery\u002F01.backup-restore",{"title":3062,"icon":3063,"path":3064,"stem":3065,"children":3066,"page":59},"Повнотекстовий пошук","i-lucide-search","\u002Fdatabases\u002Ffull-text-search","06.databases\u002F10.full-text-search",[3067],{"title":3062,"path":3068,"stem":3069},"\u002Fdatabases\u002Ffull-text-search\u002Ffull-text-search","06.databases\u002F10.full-text-search\u002F01.full-text-search",{"title":3071,"icon":3072,"path":3073,"stem":3074,"children":3075,"page":59},"Tools","i-lucide-wrench","\u002Ftools","07.tools",[3076,3152],{"title":3077,"icon":3078,"path":3079,"stem":3080,"children":3081},"Docker","i-simple-icons-docker","\u002Ftools\u002Fdocker","07.tools\u002F01.docker\u002Findex",[3082,3084,3088,3092,3096,3100,3104,3108,3112,3116,3120,3124,3128,3132,3136,3140,3144,3148],{"title":3083,"path":3079,"stem":3080},"Docker: від нуля до production",{"title":3085,"path":3086,"stem":3087},"Контейнеризація — від проблеми до рішення","\u002Ftools\u002Fdocker\u002Fcontainerization-concept","07.tools\u002F01.docker\u002F01.containerization-concept",{"title":3089,"path":3090,"stem":3091},"Docker — що це і навіщо?","\u002Ftools\u002Fdocker\u002Fdocker-what-and-why","07.tools\u002F01.docker\u002F02.docker-what-and-why",{"title":3093,"path":3094,"stem":3095},"Архітектура Docker Engine","\u002Ftools\u002Fdocker\u002Fdocker-architecture","07.tools\u002F01.docker\u002F03.docker-architecture",{"title":3097,"path":3098,"stem":3099},"Встановлення Docker","\u002Ftools\u002Fdocker\u002Finstallation","07.tools\u002F01.docker\u002F04.installation",{"title":3101,"path":3102,"stem":3103},"Перший контейнер — docker run","\u002Ftools\u002Fdocker\u002Ffirst-container","07.tools\u002F01.docker\u002F05.first-container",{"title":3105,"path":3106,"stem":3107},"Життєвий цикл контейнера","\u002Ftools\u002Fdocker\u002Fcontainer-lifecycle","07.tools\u002F01.docker\u002F06.container-lifecycle",{"title":3109,"path":3110,"stem":3111},"Docker Images — фундаментальні концепції","\u002Ftools\u002Fdocker\u002Fdocker-images-fundamentals","07.tools\u002F01.docker\u002F07.docker-images-fundamentals",{"title":3113,"path":3114,"stem":3115},"Dockerfile — основи","\u002Ftools\u002Fdocker\u002Fdockerfile-basics","07.tools\u002F01.docker\u002F08.dockerfile-basics",{"title":3117,"path":3118,"stem":3119},"Dockerfile — просунуті техніки","\u002Ftools\u002Fdocker\u002Fdockerfile-advanced","07.tools\u002F01.docker\u002F09.dockerfile-advanced",{"title":3121,"path":3122,"stem":3123},"Build Context та кешування шарів","\u002Ftools\u002Fdocker\u002Fbuild-context-and-cache","07.tools\u002F01.docker\u002F10.build-context-and-cache",{"title":3125,"path":3126,"stem":3127},"Реєстри Docker-образів","\u002Ftools\u002Fdocker\u002Fimage-registries","07.tools\u002F01.docker\u002F11.image-registries",{"title":3129,"path":3130,"stem":3131},"Контейнеризація .NET додатків","\u002Ftools\u002Fdocker\u002Fdotnet-containerization","07.tools\u002F01.docker\u002F12.dotnet-containerization",{"title":3133,"path":3134,"stem":3135},"Томи та збереження даних","\u002Ftools\u002Fdocker\u002Fvolumes-and-data","07.tools\u002F01.docker\u002F13.volumes-and-data",{"title":3137,"path":3138,"stem":3139},"Основи мережі в Docker","\u002Ftools\u002Fdocker\u002Fnetworking-basics","07.tools\u002F01.docker\u002F14.networking-basics",{"title":3141,"path":3142,"stem":3143},"Змінні оточення та конфігурація","\u002Ftools\u002Fdocker\u002Fenvironment-and-configuration","07.tools\u002F01.docker\u002F15.environment-and-configuration",{"title":3145,"path":3146,"stem":3147},"Docker Compose — оркестрація контейнерів","\u002Ftools\u002Fdocker\u002Fdocker-compose-basics","07.tools\u002F01.docker\u002F16.docker-compose-basics",{"title":3149,"path":3150,"stem":3151},"Docker Compose — Multi-Service застосунки","\u002Ftools\u002Fdocker\u002Fcompose-multi-service","07.tools\u002F01.docker\u002F17.compose-multi-service",{"title":3153,"icon":3154,"path":3155,"stem":3156,"children":3157},"Kubernetes","simple-icons:kubernetes","\u002Ftools\u002Fkubernetes","07.tools\u002F02.kubernetes\u002Findex",[3158,3160,3164,3168,3172,3176,3180,3184,3188],{"title":3159,"path":3155,"stem":3156},"Kubernetes: від розробки до production",{"title":3161,"path":3162,"stem":3163},"Kubernetes — коли Docker Compose більше не вистачає","\u002Ftools\u002Fkubernetes\u002Fwhy-kubernetes","07.tools\u002F02.kubernetes\u002F01.why-kubernetes",{"title":3165,"path":3166,"stem":3167},"Архітектура Kubernetes — анатомія кластера","\u002Ftools\u002Fkubernetes\u002Fkubernetes-architecture","07.tools\u002F02.kubernetes\u002F02.kubernetes-architecture",{"title":3169,"path":3170,"stem":3171},"Локальне середовище — minikube, kind та k3s","\u002Ftools\u002Fkubernetes\u002Flocal-environment","07.tools\u002F02.kubernetes\u002F03.local-environment",{"title":3173,"path":3174,"stem":3175},"Pod — атомарна одиниця Kubernetes","\u002Ftools\u002Fkubernetes\u002Fpods-and-containers","07.tools\u002F02.kubernetes\u002F04.pods-and-containers",{"title":3177,"path":3178,"stem":3179},"Патерни використання Pod","\u002Ftools\u002Fkubernetes\u002Fpod-patterns","07.tools\u002F02.kubernetes\u002F05.pod-patterns",{"title":3181,"path":3182,"stem":3183},"Deployment — декларативне управління Pod","\u002Ftools\u002Fkubernetes\u002Fdeployment-basics","07.tools\u002F02.kubernetes\u002F06.deployment-basics",{"title":3185,"path":3186,"stem":3187},"Rolling Updates та управління життєвим циклом Deployment","\u002Ftools\u002Fkubernetes\u002Fdeployment-rolling-updates","07.tools\u002F02.kubernetes\u002F07.deployment-rolling-updates",{"title":3189,"path":3190,"stem":3191},"Service — мережева абстракція для Pod","\u002Ftools\u002Fkubernetes\u002Fservices-networking","07.tools\u002F02.kubernetes\u002F08.services-networking",{"title":3193,"icon":3194,"path":3195,"stem":3196,"children":3197,"page":59},"Software Engineering","i-lucide-code-2","\u002Fsoftware-engineering","09.software-engineering",[3198,3202,3206,3210,3214,3218,3222,3226,3230,3234,3238],{"title":3199,"path":3200,"stem":3201},"1. Аналіз предметної області. Експертні знання та складність","\u002Fsoftware-engineering\u002Fintro-subdomains","09.software-engineering\u002F01.intro-subdomains",{"title":3203,"path":3204,"stem":3205},"2. Обмежені контексти. Інтеграція обмежених контекстів","\u002Fsoftware-engineering\u002Fintegrating-limited-contexts","09.software-engineering\u002F02.integrating-limited-contexts",{"title":3207,"path":3208,"stem":3209},"3. Реалізація простої бізнес-логіки","\u002Fsoftware-engineering\u002Fsimple","09.software-engineering\u002F03.simple",{"title":3211,"path":3212,"stem":3213},"4. Опрацювання складної бізнес-логіки","\u002Fsoftware-engineering\u002Fcomplex-business-logic","09.software-engineering\u002F04.complex-business-logic",{"title":3215,"path":3216,"stem":3217},"5. Моделювання фактора часу. Подієво-орієнтована архітектура.","\u002Fsoftware-engineering\u002Fmodelling-the-time-factor","09.software-engineering\u002F05.modelling-the-time-factor",{"title":3219,"path":3220,"stem":3221},"6. Архітектурні патерни","\u002Fsoftware-engineering\u002Farchitectural-patterns","09.software-engineering\u002F06.architectural-patterns",{"title":3223,"path":3224,"stem":3225},"Паттерни взаємодії","\u002Fsoftware-engineering\u002Fpatterns-of-interaction","09.software-engineering\u002F07.patterns-of-interaction",{"title":3227,"path":3228,"stem":3229},"Евристика проєктування","\u002Fsoftware-engineering\u002Fdesign-heuristics","09.software-engineering\u002F08.design-heuristics",{"title":3231,"path":3232,"stem":3233},"Еволюція проєктних рішень","\u002Fsoftware-engineering\u002Fevolution-of-design-solutions","09.software-engineering\u002F09.evolution-of-design-solutions",{"title":3235,"path":3236,"stem":3237},"EventStorming","\u002Fsoftware-engineering\u002Feventstorming","09.software-engineering\u002F10.eventstorming",{"title":3239,"path":3240,"stem":3241},"DDD на практиці","\u002Fsoftware-engineering\u002Fddd-in-practice","09.software-engineering\u002F11.ddd-in-practice",{"title":3243,"icon":943,"path":3244,"stem":3245,"children":3246,"page":59},"DDD","\u002Fddd","10.ddd",[3247,3251,3255,3259,3263,3267,3271,3275,3279,3283,3287,3291,3295],{"title":3248,"path":3249,"stem":3250},"Аналіз предметної області","\u002Fddd\u002Fdomain-analysis","10.ddd\u002F01.domain-analysis",{"title":3252,"path":3253,"stem":3254},"Експертні знання про предметну область","\u002Fddd\u002Fdomain-expert-knowledge","10.ddd\u002F02.domain-expert-knowledge",{"title":3256,"path":3257,"stem":3258},"Як осмислити складність предметної області","\u002Fddd\u002Fmanaging-domain-complexity","10.ddd\u002F03.managing-domain-complexity",{"title":3260,"path":3261,"stem":3262},"Інтеграція обмежених контекстів","\u002Fddd\u002Fbounded-context-integration","10.ddd\u002F04.bounded-context-integration",{"title":3264,"path":3265,"stem":3266},"Реалізація простої бізнес-логіки","\u002Fddd\u002Fsimple-business-logic","10.ddd\u002F05.simple-business-logic",{"title":3268,"path":3269,"stem":3270},"Обробка складної бізнес-логіки","\u002Fddd\u002Fcomplex-business-logic","10.ddd\u002F06.complex-business-logic",{"title":3272,"path":3273,"stem":3274},"Моделювання фактора часу","\u002Fddd\u002Ftime-modeling","10.ddd\u002F07.time-modeling",{"title":3276,"path":3277,"stem":3278},"Глава 8. Архітектурні Патерни","\u002Fddd\u002Farchitectural-patterns","10.ddd\u002F08.architectural-patterns",{"title":3280,"path":3281,"stem":3282},"Глава 9. Патерни Взаємодії","\u002Fddd\u002Finteraction-patterns","10.ddd\u002F09.interaction-patterns",{"title":3284,"path":3285,"stem":3286},"Глава 10. Проектні Евристики","\u002Fddd\u002Fdesign-heuristics","10.ddd\u002F10.design-heuristics",{"title":3288,"path":3289,"stem":3290},"Глава 11. Еволюція Проектних Рішень","\u002Fddd\u002Fevolution-of-design-decisions","10.ddd\u002F11.evolution-of-design-decisions",{"title":3292,"path":3293,"stem":3294},"Глава 12. EventStorming","\u002Fddd\u002Fevent-storming","10.ddd\u002F12.event-storming",{"title":3296,"path":3297,"stem":3298},"Глава 13. DDD на Практиці","\u002Fddd\u002Fddd-in-practice","10.ddd\u002F13.ddd-in-practice",{"title":3300,"icon":3301,"path":3302,"stem":3303,"children":3304,"page":59},"Media Streaming","i-lucide-video","\u002Fmedia-streaming","11.media-streaming",[3305,3309,3313,3317,3321,3325,3329],{"title":3306,"path":3307,"stem":3308},"01. Магія Стрімінгу: Що відбувається, коли ви натискаєте \"Play\"","\u002Fmedia-streaming\u002Fintroduction","11.media-streaming\u002F01.introduction",{"title":3310,"path":3311,"stem":3312},"02. Анатомія Медіа: Кодеки, Контейнери та Стиснення","\u002Fmedia-streaming\u002Faudio-video-anatomy","11.media-streaming\u002F02.audio-video-anatomy",{"title":3314,"path":3315,"stem":3316},"03. The Gym: FFmpeg Deep Dive","\u002Fmedia-streaming\u002Fffmpeg-gym","11.media-streaming\u002F03.ffmpeg-gym",{"title":3318,"path":3319,"stem":3320},"04. HLS Protocol: HTTP Live Streaming у Деталях","\u002Fmedia-streaming\u002Fhls-protocol","11.media-streaming\u002F04.hls-protocol",{"title":3322,"path":3323,"stem":3324},"05. DASH Protocol: Відкритий Стандарт","\u002Fmedia-streaming\u002Fdash-protocol","11.media-streaming\u002F05.dash-protocol",{"title":3326,"path":3327,"stem":3328},"06. Масштабування: CDN та Adaptive Bitrate","\u002Fmedia-streaming\u002Fcdn-and-adaptive-bitrate","11.media-streaming\u002F06.cdn-and-adaptive-bitrate",{"title":3330,"path":3331,"stem":3332},"07. Війна із Затримкою (Latency)","\u002Fmedia-streaming\u002Frealtime-latency","11.media-streaming\u002F07.realtime-latency",{"title":3334,"icon":3335,"path":3336,"stem":3337,"children":3338,"page":59},"HTML & CSS","i-devicon-html5","\u002Fhtml-css","12.html-css",[3339,3343,3347,3351,3355,3359,3363,3367,3371,3375,3379,3383,3387,3391,3395,3399,3403,3407,3411,3415,3419,3423,3427,3431,3435,3439,3443,3447,3451,3455],{"title":3340,"path":3341,"stem":3342},"Вступ до HTML. Структура документа","\u002Fhtml-css\u002Fintro-html-structure","12.html-css\u002F01.intro-html-structure",{"title":3344,"path":3345,"stem":3346},"Форматування тексту в HTML","\u002Fhtml-css\u002Fhtml-text-formatting","12.html-css\u002F02.html-text-formatting",{"title":3348,"path":3349,"stem":3350},"Посилання та зображення в HTML","\u002Fhtml-css\u002Fhtml-links-images","12.html-css\u002F03.html-links-images",{"title":3352,"path":3353,"stem":3354},"Списки та таблиці в HTML","\u002Fhtml-css\u002Fhtml-lists-tables","12.html-css\u002F04.html-lists-tables",{"title":3356,"path":3357,"stem":3358},"Форми в HTML","\u002Fhtml-css\u002Fhtml-forms","12.html-css\u002F05.html-forms",{"title":3360,"path":3361,"stem":3362},"Семантичні елементи HTML5","\u002Fhtml-css\u002Fhtml-semantic-elements","12.html-css\u002F06.html-semantic-elements",{"title":3364,"path":3365,"stem":3366},"Мультимедіа та розширені елементи HTML","\u002Fhtml-css\u002Fhtml-multimedia-advanced","12.html-css\u002F07.html-multimedia-advanced",{"title":3368,"path":3369,"stem":3370},"Мікророзмітка та SEO в HTML","\u002Fhtml-css\u002Fhtml-microdata-seo","12.html-css\u002F08.html-microdata-seo",{"title":3372,"path":3373,"stem":3374},"Вступ до CSS. Селектори та специфічність","\u002Fhtml-css\u002Fcss-intro-selectors","12.html-css\u002F09.css-intro-selectors",{"title":3376,"path":3377,"stem":3378},"Блокова модель CSS. Відступи. Box Sizing","\u002Fhtml-css\u002Fcss-box-model","12.html-css\u002F10.css-box-model",{"title":3380,"path":3381,"stem":3382},"Розміри у CSS: повний довідник одиниць і ключових слів","\u002Fhtml-css\u002F10a.css-sizing","12.html-css\u002F10a.css-sizing",{"title":3384,"path":3385,"stem":3386},"Типографіка в CSS. Шрифти та текст","\u002Fhtml-css\u002Fcss-typography","12.html-css\u002F11.css-typography",{"title":3388,"path":3389,"stem":3390},"Кольори та фони в CSS","\u002Fhtml-css\u002Fcss-colors-backgrounds","12.html-css\u002F12.css-colors-backgrounds",{"title":3392,"path":3393,"stem":3394},"Тіні та фільтри в CSS","\u002Fhtml-css\u002F12b.css-shadows-filters","12.html-css\u002F12b.css-shadows-filters",{"title":3396,"path":3397,"stem":3398},"CSS Flexbox: Фундамент гнучких макетів","\u002Fhtml-css\u002Fcss-flexbox-fundamentals","12.html-css\u002F13.css-flexbox-fundamentals",{"title":3400,"path":3401,"stem":3402},"CSS Flexbox: Вирівнювання та Позиціонування","\u002Fhtml-css\u002Fcss-flexbox-alignment-sizing-and-patterns","12.html-css\u002F14.css-flexbox-alignment-sizing-and-patterns",{"title":3404,"path":3405,"stem":3406},"CSS Grid. Двовимірний макет. Частина 1","\u002Fhtml-css\u002Fcss-layout-grid","12.html-css\u002F15.css-layout-grid",{"title":3408,"path":3409,"stem":3410},"CSS Grid. Двовимірний макет. Частина 2","\u002Fhtml-css\u002Fcss-layout-grid-advanced","12.html-css\u002F16.css-layout-grid-advanced",{"title":3412,"path":3413,"stem":3414},"Позиціонування в CSS. Z-index. Stacking Context","\u002Fhtml-css\u002Fcss-positioning","12.html-css\u002F17.css-positioning",{"title":3416,"path":3417,"stem":3418},"CSS Анімації та Переходи","\u002Fhtml-css\u002Fcss-animations-transitions","12.html-css\u002F18.css-animations-transitions",{"title":3420,"path":3421,"stem":3422},"Адаптивний дизайн. Media Queries. Частина 1","\u002Fhtml-css\u002Fcss-responsive-media-queries","12.html-css\u002F19.css-responsive-media-queries",{"title":3424,"path":3425,"stem":3426},"Адаптивний дизайн. Частина 2: clamp(), Container Queries, @layer","\u002Fhtml-css\u002Fcss-responsive-advanced","12.html-css\u002F20.css-responsive-advanced",{"title":3428,"path":3429,"stem":3430},"CSS Custom Properties. Методології. Сучасний CSS","\u002Fhtml-css\u002Fcss-variables-methodologies","12.html-css\u002F21.css-variables-methodologies",{"title":3432,"path":3433,"stem":3434},"Сучасний CSS 2023–2025: Нові можливості","\u002Fhtml-css\u002Fcss-modern-features","12.html-css\u002F22.css-modern-features",{"title":3436,"path":3437,"stem":3438},"CSS Nesting, @layer, @scope та @property: нативний препроцесор","\u002Fhtml-css\u002F22a.css-nesting-modern-syntax","12.html-css\u002F22a.css-nesting-modern-syntax",{"title":3440,"path":3441,"stem":3442},"CSS для форм та інтерактивних станів","\u002Fhtml-css\u002Fcss-forms-interactive-states","12.html-css\u002F23.css-forms-interactive-states",{"title":3444,"path":3445,"stem":3446},"Доступність у CSS (CSS Accessibility)","\u002Fhtml-css\u002Fcss-accessibility","12.html-css\u002F24.css-accessibility",{"title":3448,"path":3449,"stem":3450},"CSS-функції та сучасні sizing primitives","\u002Fhtml-css\u002Fcss-functions-sizing","12.html-css\u002F25.css-functions-sizing",{"title":3452,"path":3453,"stem":3454},"Rendering Pipeline і CSS Performance","\u002Fhtml-css\u002Fcss-rendering-performance","12.html-css\u002F26.css-rendering-performance",{"title":3456,"path":3457,"stem":3458},"CSS Best Practices: типові ситуації та правильні рішення","\u002Fhtml-css\u002Fcss-best-practices","12.html-css\u002F27.css-best-practices",{"title":3460,"path":3461,"stem":3462,"children":3463,"page":59},"AWS","\u002Faws","13.aws",[3464,3468,3472,3476,3480,3484,3488,3492,3496,3500,3504,3508,3512,3516,3520,3524,3528,3532],{"title":3465,"path":3466,"stem":3467},"Реєстрація AWS акаунту та студентські програми","\u002Faws\u002Faccount-registration","13.aws\u002F00.account-registration",{"title":3469,"path":3470,"stem":3471},"Вступ до хмарних обчислень та AWS","\u002Faws\u002Fintroduction-to-cloud","13.aws\u002F01.introduction-to-cloud",{"title":3473,"path":3474,"stem":3475},"AWS IAM — Identity and Access Management","\u002Faws\u002Fiam","13.aws\u002F02.iam",{"title":3477,"path":3478,"stem":3479},"AWS IAM CLI — Довідник команд","\u002Faws\u002F02a.iam-doc","13.aws\u002F02a.iam-doc",{"title":3481,"path":3482,"stem":3483},"Docker та контейнеризація в AWS — ECR, ECS та Fargate","\u002Faws\u002Fdocker-ecs","13.aws\u002F03.docker-ecs",{"title":3485,"path":3486,"stem":3487},"AWS ECR \u002F ECS CLI — Довідник команд","\u002Faws\u002F03a.docker-ecs-doc","13.aws\u002F03a.docker-ecs-doc",{"title":3489,"path":3490,"stem":3491},"Amazon EC2 — Elastic Compute Cloud","\u002Faws\u002Fec2","13.aws\u002F04.ec2",{"title":3493,"path":3494,"stem":3495},"AWS EC2 CLI — Довідник команд","\u002Faws\u002F04a.ec2-doc","13.aws\u002F04a.ec2-doc",{"title":3497,"path":3498,"stem":3499},"Elastic Load Balancing та Auto Scaling","\u002Faws\u002Falb-asg","13.aws\u002F05.alb-asg",{"title":3501,"path":3502,"stem":3503},"Amazon S3 — Simple Storage Service","\u002Faws\u002Fs3","13.aws\u002F06.s3",{"title":3505,"path":3506,"stem":3507},"Amazon CloudFront — Content Delivery Network","\u002Faws\u002Fcloudfront","13.aws\u002F07.cloudfront",{"title":3509,"path":3510,"stem":3511},"Amazon RDS — Relational Database Service","\u002Faws\u002Frds","13.aws\u002F08.rds",{"title":3513,"path":3514,"stem":3515},"Amazon DynamoDB — NoSQL Database","\u002Faws\u002Fdynamodb","13.aws\u002F09.dynamodb",{"title":3517,"path":3518,"stem":3519},"AWS Lambda та Serverless Compute","\u002Faws\u002Flambda","13.aws\u002F10.lambda",{"title":3521,"path":3522,"stem":3523},"Amazon Bedrock - Foundation Models, RAG та Agents","\u002Faws\u002Fbedrock","13.aws\u002F22.bedrock",{"title":3525,"path":3526,"stem":3527},"Amazon Rekognition - Комп'ютерний зір","\u002Faws\u002Frekognition","13.aws\u002F23.rekognition",{"title":3529,"path":3530,"stem":3531},"Amazon Textract - Інтелектуальний аналіз документів","\u002Faws\u002Ftextract","13.aws\u002F24.textract",{"title":3533,"path":3534,"stem":3535},"Amazon Polly, Transcribe, Comprehend та Translate","\u002Faws\u002Faudio-nlp-services","13.aws\u002F25.audio-nlp-services",{"title":3537,"path":3538,"stem":3539,"children":3540,"page":59},"Ai Development","\u002Fai-development","14.ai-development",[3541],{"title":3542,"path":3543,"stem":3544,"children":3545,"page":59},"Foundations","\u002Fai-development\u002Ffoundations","14.ai-development\u002F00.foundations",[3546],{"title":3547,"path":3548,"stem":3549},"Модуль 0.1. Що таке Large Language Model (LLM)","\u002Fai-development\u002Ffoundations\u002Fwhat-is-llm","14.ai-development\u002F00.foundations\u002F01.what-is-llm",{"title":3551,"path":3552,"stem":3553,"children":3554,"page":59},"React Native","\u002Freact-native","15.react-native",[3555,3576],{"title":3556,"path":3557,"stem":3558,"children":3559,"page":59},"Version1","\u002Freact-native\u002Fversion1","15.react-native\u002Fversion1",[3560,3564,3568,3572],{"title":3561,"path":3562,"stem":3563},"Що таке React Native","\u002Freact-native\u002Fversion1\u002Fwhat-is-react-native","15.react-native\u002Fversion1\u002F01.what-is-react-native",{"title":3565,"path":3566,"stem":3567},"Як влаштований React Native «під капотом»","\u002Freact-native\u002Fversion1\u002Freact-native-architecture","15.react-native\u002Fversion1\u002F02.react-native-architecture",{"title":3569,"path":3570,"stem":3571},"Від React до React Native: ключові відмінності","\u002Freact-native\u002Fversion1\u002Freact-native-vs-react","15.react-native\u002Fversion1\u002F03.react-native-vs-react",{"title":3573,"path":3574,"stem":3575},"View та Text — фундаментальні будівельні блоки","\u002Freact-native\u002Fversion1\u002Fview-and-text","15.react-native\u002Fversion1\u002F04.view-and-text",{"title":3577,"path":3578,"stem":3579,"children":3580,"page":59},"Version2","\u002Freact-native\u002Fversion2","15.react-native\u002Fversion2",[3581,3585,3589,3593,3597,3601,3605,3609,3613,3617,3621,3625,3629,3633,3637,3641,3645,3649,3653,3657,3661,3665,3669,3673,3677,3681,3685],{"title":3582,"path":3583,"stem":3584},"React Native — навіщо він потрібен","\u002Freact-native\u002Fversion2\u002Fwhy-react-native","15.react-native\u002Fversion2\u002F01.why-react-native",{"title":3586,"path":3587,"stem":3588},"Налаштування середовища розробки","\u002Freact-native\u002Fversion2\u002Fenvironment-setup","15.react-native\u002Fversion2\u002F02.environment-setup",{"title":3590,"path":3591,"stem":3592},"Expo і класичний React Native — два шляхи одного фреймворку","\u002Freact-native\u002Fversion2\u002Fexpo-vs-cli-landscape","15.react-native\u002Fversion2\u002F03.expo-vs-cli-landscape",{"title":3594,"path":3595,"stem":3596},"Середовище Expo — перший запуск","\u002Freact-native\u002Fversion2\u002Fexpo-setup-and-tooling","15.react-native\u002Fversion2\u002F04.expo-setup-and-tooling",{"title":3598,"path":3599,"stem":3600},"Структура проєкту та перші UI-примітиви","\u002Freact-native\u002Fversion2\u002Fproject-structure-and-conventions","15.react-native\u002Fversion2\u002F05.project-structure-and-conventions",{"title":3602,"path":3603,"stem":3604},"Базові компоненти React Native","\u002Freact-native\u002Fversion2\u002Fcore-components","15.react-native\u002Fversion2\u002F06.core-components",{"title":3606,"path":3607,"stem":3608},"Flexbox і layout у React Native","\u002Freact-native\u002Fversion2\u002Fflexbox-and-layout","15.react-native\u002Fversion2\u002F07.flexbox-and-layout",{"title":3610,"path":3611,"stem":3612},"StyleSheet і теми (light \u002F dark)","\u002Freact-native\u002Fversion2\u002Fstylesheet-and-theming","15.react-native\u002Fversion2\u002F08.stylesheet-and-theming",{"title":3614,"path":3615,"stem":3616},"Списки та віртуалізація","\u002Freact-native\u002Fversion2\u002Flists-and-virtualization","15.react-native\u002Fversion2\u002F09.lists-and-virtualization",{"title":3618,"path":3619,"stem":3620},"Форми, ввід і валідація","\u002Freact-native\u002Fversion2\u002Fforms-input-validation","15.react-native\u002Fversion2\u002F10.forms-input-validation",{"title":3622,"path":3623,"stem":3624},"Основи Expo Router","\u002Freact-native\u002Fversion2\u002Fexpo-router-basics","15.react-native\u002Fversion2\u002F11.expo-router-basics",{"title":3626,"path":3627,"stem":3628},"Вкладені навігатори та модалки","\u002Freact-native\u002Fversion2\u002Fnested-navigators-and-modals","15.react-native\u002Fversion2\u002F12.nested-navigators-and-modals",{"title":3630,"path":3631,"stem":3632},"Deep linking і параметри маршрутів","\u002Freact-native\u002Fversion2\u002Fdeep-linking-and-params","15.react-native\u002Fversion2\u002F13.deep-linking-and-params",{"title":3634,"path":3635,"stem":3636},"Робота з мережею та життєвий цикл застосунку","\u002Freact-native\u002Fversion2\u002Fnetworking-and-app-lifecycle","15.react-native\u002Fversion2\u002F14.networking-and-app-lifecycle",{"title":3638,"path":3639,"stem":3640},"Redux Toolkit на мобільних платформах","\u002Freact-native\u002Fversion2\u002Fredux-toolkit-on-mobile","15.react-native\u002Fversion2\u002F15.redux-toolkit-on-mobile",{"title":3642,"path":3643,"stem":3644},"RTK Query на мобільних платформах","\u002Freact-native\u002Fversion2\u002Frtk-query-mobile","15.react-native\u002Fversion2\u002F16.rtk-query-mobile",{"title":3646,"path":3647,"stem":3648},"Автентифікація та Безпечне Зберігання","\u002Freact-native\u002Fversion2\u002Fauth-secure-storage","15.react-native\u002Fversion2\u002F18.auth-secure-storage",{"title":3650,"path":3651,"stem":3652},"Локальне сховище — AsyncStorage, MMKV, SQLite","\u002Freact-native\u002Fversion2\u002Flocal-storage-mmkv-sqlite","15.react-native\u002Fversion2\u002F19.local-storage-mmkv-sqlite",{"title":3654,"path":3655,"stem":3656},"Офлайн-First і синхронізація","\u002Freact-native\u002Fversion2\u002Foffline-first-sync","15.react-native\u002Fversion2\u002F20.offline-first-sync",{"title":3658,"path":3659,"stem":3660},"Камера, медіа та файлова система","\u002Freact-native\u002Fversion2\u002Fcamera-media-filesystem","15.react-native\u002Fversion2\u002F21.camera-media-filesystem",{"title":3662,"path":3663,"stem":3664},"Карти та геолокація","\u002Freact-native\u002Fversion2\u002Fmaps-and-location","15.react-native\u002Fversion2\u002F22.maps-and-location",{"title":3666,"path":3667,"stem":3668},"Жести та дотики","\u002Freact-native\u002Fversion2\u002Fgestures-and-touch","15.react-native\u002Fversion2\u002F23.gestures-and-touch",{"title":3670,"path":3671,"stem":3672},"Анімації з Reanimated","\u002Freact-native\u002Fversion2\u002Freanimated-animations","15.react-native\u002Fversion2\u002F24.reanimated-animations",{"title":3674,"path":3675,"stem":3676},"Push і локальні сповіщення","\u002Freact-native\u002Fversion2\u002Fpush-and-local-notifications","15.react-native\u002Fversion2\u002F25.push-and-local-notifications",{"title":3678,"path":3679,"stem":3680},"Інтернаціоналізація та доступність","\u002Freact-native\u002Fversion2\u002Faccessibility-and-i18n","15.react-native\u002Fversion2\u002F26.accessibility-and-i18n",{"title":3682,"path":3683,"stem":3684},"EAS Build та профілі збірки","\u002Freact-native\u002Fversion2\u002Feas-build-and-profiles","15.react-native\u002Fversion2\u002F29.eas-build-and-profiles",{"title":3686,"path":3687,"stem":3688},"Публікація в App Store та Google Play","\u002Freact-native\u002Fversion2\u002Fapp-store-play-release","15.react-native\u002Fversion2\u002F30.app-store-play-release",{"title":3690,"path":3691,"stem":3692,"children":3693,"page":59},"Ai Python","\u002Fai-python","16.ai-python",[3694,3703,3712,3721,3750,3776,3801,3834,3851,3864,3873,3886,3895,3916,3929,3950],{"title":3695,"path":3696,"stem":3697,"children":3698,"page":59},"Intro To Ai","\u002Fai-python\u002Fintro-to-ai","16.ai-python\u002F01.intro-to-ai",[3699],{"title":3700,"path":3701,"stem":3702},"Вступ до штучного інтелекту та машинного навчання","\u002Fai-python\u002Fintro-to-ai\u002Fintro-to-ai","16.ai-python\u002F01.intro-to-ai\u002F01.intro-to-ai",{"title":3704,"path":3705,"stem":3706,"children":3707,"page":59},"Jupyter Notebook","\u002Fai-python\u002Fjupyter-notebook","16.ai-python\u002F02.jupyter-notebook",[3708],{"title":3709,"path":3710,"stem":3711},"Знайомство з Jupyter Notebook та JupyterLab","\u002Fai-python\u002Fjupyter-notebook\u002Fjupyter-notebook","16.ai-python\u002F02.jupyter-notebook\u002F02.jupyter-notebook",{"title":3713,"path":3714,"stem":3715,"children":3716,"page":59},"Numpy Pandas","\u002Fai-python\u002Fnumpy-pandas","16.ai-python\u002F03.numpy-pandas",[3717],{"title":3718,"path":3719,"stem":3720},"Робота з даними з використанням NumPy і pandas","\u002Fai-python\u002Fnumpy-pandas\u002Fnumpy-pandas","16.ai-python\u002F03.numpy-pandas\u002F03.numpy-pandas",{"title":3722,"path":3723,"stem":3724,"children":3725,"page":59},"Statistics Basics","\u002Fai-python\u002Fstatistics-basics","16.ai-python\u002F04.statistics-basics",[3726,3730,3734,3738,3742,3746],{"title":3727,"path":3728,"stem":3729},"Випадкові величини та їх типи","\u002Fai-python\u002Fstatistics-basics\u002Frandom-variables","16.ai-python\u002F04.statistics-basics\u002F01.random-variables",{"title":3731,"path":3732,"stem":3733},"Міри центральної тенденції","\u002Fai-python\u002Fstatistics-basics\u002Fcentral-tendency","16.ai-python\u002F04.statistics-basics\u002F02.central-tendency",{"title":3735,"path":3736,"stem":3737},"Міри варіації (розсіювання)","\u002Fai-python\u002Fstatistics-basics\u002Fvariability","16.ai-python\u002F04.statistics-basics\u002F03.variability",{"title":3739,"path":3740,"stem":3741},"Розподіли випадкових величин","\u002Fai-python\u002Fstatistics-basics\u002Fdistributions","16.ai-python\u002F04.statistics-basics\u002F04.distributions",{"title":3743,"path":3744,"stem":3745},"Кореляція та взаємозв'язки","\u002Fai-python\u002Fstatistics-basics\u002Fcorrelation","16.ai-python\u002F04.statistics-basics\u002F05.correlation",{"title":3747,"path":3748,"stem":3749},"Викиди та аномалії","\u002Fai-python\u002Fstatistics-basics\u002Foutliers","16.ai-python\u002F04.statistics-basics\u002F06.outliers",{"title":3751,"path":3752,"stem":3753,"children":3754},"Візуалізація даних за допомогою matplotlib","\u002Fai-python\u002Fdata-visualization","16.ai-python\u002F05.data-visualization\u002Findex",[3755,3756,3760,3764,3768,3772],{"title":3751,"path":3752,"stem":3753},{"title":3757,"path":3758,"stem":3759},"Основи matplotlib — Figure, Axes та перший графік","\u002Fai-python\u002Fdata-visualization\u002Fmatplotlib-basics","16.ai-python\u002F05.data-visualization\u002F01.matplotlib-basics",{"title":3761,"path":3762,"stem":3763},"Візуалізація розподілів — гістограми та box plots","\u002Fai-python\u002Fdata-visualization\u002Fdistributions","16.ai-python\u002F05.data-visualization\u002F02.distributions",{"title":3765,"path":3766,"stem":3767},"Візуалізація залежностей — scatter plots та кореляція","\u002Fai-python\u002Fdata-visualization\u002Frelationships","16.ai-python\u002F05.data-visualization\u002F03.relationships",{"title":3769,"path":3770,"stem":3771},"Візуалізація категоріальних даних — bar charts та pie charts","\u002Fai-python\u002Fdata-visualization\u002Fcategorical","16.ai-python\u002F05.data-visualization\u002F04.categorical",{"title":3773,"path":3774,"stem":3775},"Композиції та стилізація — subplots та багатопанельні дашборди","\u002Fai-python\u002Fdata-visualization\u002Fsubplots-styling","16.ai-python\u002F05.data-visualization\u002F05.subplots-styling",{"title":3777,"path":3778,"stem":3779,"children":3780,"page":59},"Linear Regression","\u002Fai-python\u002Flinear-regression","16.ai-python\u002F06.linear-regression",[3781,3785,3789,3793,3797],{"title":3782,"path":3783,"stem":3784},"Регресійна задача та лінійна регресія з однією змінною","\u002Fai-python\u002Flinear-regression\u002Fregression-task","16.ai-python\u002F06.linear-regression\u002F01.regression-task",{"title":3786,"path":3787,"stem":3788},"Метрики якості регресії — як оцінити модель","\u002Fai-python\u002Flinear-regression\u002Fquality-metrics","16.ai-python\u002F06.linear-regression\u002F02.quality-metrics",{"title":3790,"path":3791,"stem":3792},"Градієнтний спуск — як модель навчається","\u002Fai-python\u002Flinear-regression\u002Fgradient-descent","16.ai-python\u002F06.linear-regression\u002F03.gradient-descent",{"title":3794,"path":3795,"stem":3796},"Множинна лінійна регресія — модель з багатьма ознаками","\u002Fai-python\u002Flinear-regression\u002Fmultiple-regression","16.ai-python\u002F06.linear-regression\u002F04.multiple-regression",{"title":3798,"path":3799,"stem":3800},"Практичні завдання та резюме модуля","\u002Fai-python\u002Flinear-regression\u002Fpractice","16.ai-python\u002F06.linear-regression\u002F05.practice",{"title":3802,"path":3803,"stem":3804,"children":3805,"page":59},"Practical Regression","\u002Fai-python\u002Fpractical-regression","16.ai-python\u002F07.practical-regression",[3806,3810,3814,3818,3822,3826,3830],{"title":3807,"path":3808,"stem":3809},"Знайомство з scikit-learn","\u002Fai-python\u002Fpractical-regression\u002Fintro-scikit-learn","16.ai-python\u002F07.practical-regression\u002F01.intro-scikit-learn",{"title":3811,"path":3812,"stem":3813},"Exploratory Data Analysis датасету Housing Prices","\u002Fai-python\u002Fpractical-regression\u002Fhousing-dataset-eda","16.ai-python\u002F07.practical-regression\u002F02.housing-dataset-eda",{"title":3815,"path":3816,"stem":3817},"Попередня обробка даних (Data Preprocessing)","\u002Fai-python\u002Fpractical-regression\u002Fdata-preprocessing","16.ai-python\u002F07.practical-regression\u002F03.data-preprocessing",{"title":3819,"path":3820,"stem":3821},"Train\u002FTest Split та перша повноцінна модель","\u002Fai-python\u002Fpractical-regression\u002Ftrain-test-split","16.ai-python\u002F07.practical-regression\u002F04.train-test-split",{"title":3823,"path":3824,"stem":3825},"Перенавчання та недонавчання","\u002Fai-python\u002Fpractical-regression\u002Foverfitting-underfitting","16.ai-python\u002F07.practical-regression\u002F05.overfitting-underfitting",{"title":3827,"path":3828,"stem":3829},"Крос-валідація (Cross-Validation)","\u002Fai-python\u002Fpractical-regression\u002Fcross-validation","16.ai-python\u002F07.practical-regression\u002F06.cross-validation",{"title":3831,"path":3832,"stem":3833},"Гіперпараметри та їх оптимізація","\u002Fai-python\u002Fpractical-regression\u002Fhyperparameter-tuning","16.ai-python\u002F07.practical-regression\u002F07.hyperparameter-tuning",{"title":3835,"path":3836,"stem":3837,"children":3838,"page":59},"Polynomial Regression","\u002Fai-python\u002Fpolynomial-regression","16.ai-python\u002F08.polynomial-regression",[3839,3843,3847],{"title":3840,"path":3841,"stem":3842},"Нелінійні залежності та поліноміальна регресія","\u002Fai-python\u002Fpolynomial-regression\u002Fnonlinear-patterns","16.ai-python\u002F08.polynomial-regression\u002F01.nonlinear-patterns",{"title":3844,"path":3845,"stem":3846},"Регуляризація в регресії — Ridge та Lasso","\u002Fai-python\u002Fpolynomial-regression\u002Fregularization-methods","16.ai-python\u002F08.polynomial-regression\u002F02.regularization-methods",{"title":3848,"path":3849,"stem":3850},"Практика — поліноміальна регресія та регуляризація на Housing Prices","\u002Fai-python\u002Fpolynomial-regression\u002Fhousing-prices-practice","16.ai-python\u002F08.polynomial-regression\u002F03.housing-prices-practice",{"title":3852,"path":3853,"stem":3854,"children":3855,"page":59},"Decision Trees Random Forest","\u002Fai-python\u002Fdecision-trees-random-forest","16.ai-python\u002F09.decision-trees-random-forest",[3856,3860],{"title":3857,"path":3858,"stem":3859},"Дерева рішень — моделі з прозорою та зрозумілою логікою","\u002Fai-python\u002Fdecision-trees-random-forest\u002Fdecision-trees","16.ai-python\u002F09.decision-trees-random-forest\u002F01.decision-trees",{"title":3861,"path":3862,"stem":3863},"Random Forest — ансамблі дерев рішень","\u002Fai-python\u002Fdecision-trees-random-forest\u002Frandom-forest","16.ai-python\u002F09.decision-trees-random-forest\u002F02.random-forest",{"title":3865,"path":3866,"stem":3867,"children":3868,"page":59},"Gradient Boosting","\u002Fai-python\u002Fgradient-boosting","16.ai-python\u002F10.gradient-boosting",[3869],{"title":3870,"path":3871,"stem":3872},"Градієнтний бустинг та XGBoost — послідовне виправлення помилок","\u002Fai-python\u002Fgradient-boosting\u002Fgradient-boosting-xgboost","16.ai-python\u002F10.gradient-boosting\u002F01.gradient-boosting-xgboost",{"title":3874,"path":3875,"stem":3876,"children":3877,"page":59},"Logistic Regression Classification","\u002Fai-python\u002Flogistic-regression-classification","16.ai-python\u002F11.logistic-regression-classification",[3878,3882],{"title":3879,"path":3880,"stem":3881},"Основи класифікації та логістична регресія","\u002Fai-python\u002Flogistic-regression-classification\u002Fclassification-basics","16.ai-python\u002F11.logistic-regression-classification\u002F01.classification-basics",{"title":3883,"path":3884,"stem":3885},"Метрики якості класифікації","\u002Fai-python\u002Flogistic-regression-classification\u002Fclassification-metrics","16.ai-python\u002F11.logistic-regression-classification\u002F02.classification-metrics",{"title":3887,"path":3888,"stem":3889,"children":3890,"page":59},"Neural Networks Basics","\u002Fai-python\u002Fneural-networks-basics","16.ai-python\u002F12.neural-networks-basics",[3891],{"title":3892,"path":3893,"stem":3894},"Вступ до нейронних мереж — від персептрона до багатошарових мереж","\u002Fai-python\u002Fneural-networks-basics\u002Fperceptron-to-mlp","16.ai-python\u002F12.neural-networks-basics\u002F01.perceptron-to-mlp",{"title":3896,"path":3897,"stem":3898,"children":3899,"page":59},"Pytorch Intro","\u002Fai-python\u002Fpytorch-intro","16.ai-python\u002F13.pytorch-intro",[3900,3904,3908,3912],{"title":3901,"path":3902,"stem":3903},"Тензори та автоматичне диференціювання в PyTorch","\u002Fai-python\u002Fpytorch-intro\u002Ftensors-and-autograd","16.ai-python\u002F13.pytorch-intro\u002F01.tensors-and-autograd",{"title":3905,"path":3906,"stem":3907},"Побудова та тренування нейронних мереж у PyTorch","\u002Fai-python\u002Fpytorch-intro\u002Fbuilding-and-training","16.ai-python\u002F13.pytorch-intro\u002F02.building-and-training",{"title":3909,"path":3910,"stem":3911},"Робота з даними та регуляризація в PyTorch","\u002Fai-python\u002Fpytorch-intro\u002Fdata-and-regularization","16.ai-python\u002F13.pytorch-intro\u002F03.data-and-regularization",{"title":3913,"path":3914,"stem":3915},"Просунуті теми PyTorch — GPU, оптимізація та deployment","\u002Fai-python\u002Fpytorch-intro\u002Fadvanced-topics","16.ai-python\u002F13.pytorch-intro\u002F04.advanced-topics",{"title":3917,"path":3918,"stem":3919,"children":3920,"page":59},"Activation Functions Heart Disease","\u002Fai-python\u002Factivation-functions-heart-disease","16.ai-python\u002F14.activation-functions-heart-disease",[3921,3925],{"title":3922,"path":3923,"stem":3924},"Функції активації та побудова нейронної мережі для передбачення вад серця","\u002Fai-python\u002Factivation-functions-heart-disease\u002Fheart-disease-prediction","16.ai-python\u002F14.activation-functions-heart-disease\u002F01.heart-disease-prediction",{"title":3926,"path":3927,"stem":3928},"Бонус — Повний приклад Student Performance Prediction","\u002Fai-python\u002Factivation-functions-heart-disease\u002Fstudent-performance-bonus","16.ai-python\u002F14.activation-functions-heart-disease\u002F02.student-performance-bonus",{"title":3930,"path":3931,"stem":3932,"children":3933,"page":59},"Cnn Image Classification","\u002Fai-python\u002Fcnn-image-classification","16.ai-python\u002F15.cnn-image-classification",[3934,3938,3942,3946],{"title":3935,"path":3936,"stem":3937},"Основи згорткових нейронних мереж — чому не MLP?","\u002Fai-python\u002Fcnn-image-classification\u002Fcnn-fundamentals","16.ai-python\u002F15.cnn-image-classification\u002F01.cnn-fundamentals",{"title":3939,"path":3940,"stem":3941},"Практична імплементація CNN для класифікації MNIST","\u002Fai-python\u002Fcnn-image-classification\u002Fmnist-classification","16.ai-python\u002F15.cnn-image-classification\u002F02.mnist-classification",{"title":3943,"path":3944,"stem":3945},"Глибші CNN та аугментація даних для CIFAR-10","\u002Fai-python\u002Fcnn-image-classification\u002Fcifar10-and-data-augmentation","16.ai-python\u002F15.cnn-image-classification\u002F03.cifar10-and-data-augmentation",{"title":3947,"path":3948,"stem":3949},"Transfer Learning та візуалізація внутрішніх представлень CNN","\u002Fai-python\u002Fcnn-image-classification\u002Ftransfer-learning-and-visualization","16.ai-python\u002F15.cnn-image-classification\u002F04.transfer-learning-and-visualization",{"title":3951,"path":3952,"stem":3953,"children":3954,"page":59},"Batching Normalization Deep Networks","\u002Fai-python\u002Fbatching-normalization-deep-networks","16.ai-python\u002F16.batching-normalization-deep-networks",[3955,3959,3963,3967,3971,3975,3979],{"title":3956,"path":3957,"stem":3958},"Mini-batch Gradient Descent та ефективна обробка даних","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fmini-batch-gradient-descent","16.ai-python\u002F16.batching-normalization-deep-networks\u002F01.mini-batch-gradient-descent",{"title":3960,"path":3961,"stem":3962},"Ініціалізація ваг — фундамент стабільного навчання","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fweight-initialization","16.ai-python\u002F16.batching-normalization-deep-networks\u002F02.weight-initialization",{"title":3964,"path":3965,"stem":3966},"Batch Normalization — прорив у глибокому навчанні","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fbatch-normalization","16.ai-python\u002F16.batching-normalization-deep-networks\u002F03.batch-normalization",{"title":3968,"path":3969,"stem":3970},"Dropout та комбіновані стратегії регуляризації","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fdropout-and-regularization","16.ai-python\u002F16.batching-normalization-deep-networks\u002F04.dropout-and-regularization",{"title":3972,"path":3973,"stem":3974},"Проєктування глибоких мереж — від теорії до практики","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Fdeep-networks-architectures","16.ai-python\u002F16.batching-normalization-deep-networks\u002F05.deep-networks-architectures",{"title":3976,"path":3977,"stem":3978},"Планування learning rate — коли та як зменшувати крок навчання","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Flearning-rate-scheduling","16.ai-python\u002F16.batching-normalization-deep-networks\u002F06.learning-rate-scheduling",{"title":3980,"path":3981,"stem":3982},"Підсумковий проєкт — побудова сучасного класифікатора зображень","\u002Fai-python\u002Fbatching-normalization-deep-networks\u002Ffinal-project-deep-classifier","16.ai-python\u002F16.batching-normalization-deep-networks\u002F07.final-project-deep-classifier",{"title":3984,"icon":658,"path":3985,"stem":3986,"children":3987,"page":59},"Клієнт-серверна архітектура","\u002Fclient-server-architecture","17.client-server-architecture",[3988,3992,3996,4000,4004,4008,4012,4016,4020,4024,4028,4032,4036,4040,4044,4048,4052,4056],{"title":3989,"path":3990,"stem":3991},"Архітектура клієнт-серверних систем та основи Go","\u002Fclient-server-architecture\u002Fclient-server-architecture-and-go","17.client-server-architecture\u002F01.client-server-architecture-and-go",{"title":3993,"path":3994,"stem":3995},"Система типів та модель пам’яті мови Go","\u002Fclient-server-architecture\u002Ftype-system-and-memory-model","17.client-server-architecture\u002F02.type-system-and-memory-model",{"title":3997,"path":3998,"stem":3999},"Інтерфейси та модель конкурентності мови Go","\u002Fclient-server-architecture\u002Finterfaces-and-concurrency-model","17.client-server-architecture\u002F03.interfaces-and-concurrency-model",{"title":4001,"path":4002,"stem":4003},"Сокетне програмування та протокол TCP у Go","\u002Fclient-server-architecture\u002Ftcp-socket-programming","17.client-server-architecture\u002F04.tcp-socket-programming",{"title":4005,"path":4006,"stem":4007},"Протокол UDP та датаграмна передача даних","\u002Fclient-server-architecture\u002Fudp-datagram-transmission","17.client-server-architecture\u002F05.udp-datagram-transmission",{"title":4009,"path":4010,"stem":4011},"Криптографічний захист каналів зв","\u002Fclient-server-architecture\u002Ftls-cryptographic-channel-protection","17.client-server-architecture\u002F06.tls-cryptographic-channel-protection",{"title":4013,"path":4014,"stem":4015},"Прикладні мережеві протоколи DNS та SMTP","\u002Fclient-server-architecture\u002Fdns-smtp-application-protocols","17.client-server-architecture\u002F07.dns-smtp-application-protocols",{"title":4017,"path":4018,"stem":4019},"Протокол HTTP та стандартний вебсервер Go","\u002Fclient-server-architecture\u002Fhttp-protocol-and-web-server","17.client-server-architecture\u002F08.http-protocol-and-web-server",{"title":4021,"path":4022,"stem":4023},"Проєктування REST API та маршрутизація засобами Chi","\u002Fclient-server-architecture\u002Frest-api-design-and-chi-routing","17.client-server-architecture\u002F09.rest-api-design-and-chi-routing",{"title":4025,"path":4026,"stem":4027},"Лекція 10. Шарувата архітектура та конвеєри обробки запитів","\u002Fclient-server-architecture\u002Flayered-architecture-and-middleware-pipelines","17.client-server-architecture\u002F10.layered-architecture-and-middleware-pipelines",{"title":4029,"path":4030,"stem":4031},"Лекція 11. Архітектура та маршрутизація фреймворку Gin","\u002Fclient-server-architecture\u002Fgin-framework-architecture-and-routing","17.client-server-architecture\u002F11.gin-framework-architecture-and-routing",{"title":4033,"path":4034,"stem":4035},"Лекція 12. Валідація даних, безпека та документування у Gin","\u002Fclient-server-architecture\u002Fdata-validation-security-and-documentation-in-gin","17.client-server-architecture\u002F12.data-validation-security-and-documentation-in-gin",{"title":4037,"path":4038,"stem":4039},"Лекція 13. Взаємодія з реляційними СУБД та технології ORM","\u002Fclient-server-architecture\u002Frelational-databases-and-orm","17.client-server-architecture\u002F13.relational-databases-and-orm",{"title":4041,"path":4042,"stem":4043},"Потокова передача даних та протокол WebSocket","\u002Fclient-server-architecture\u002Fstreaming-data-and-websockets","17.client-server-architecture\u002F14.streaming-data-and-websockets",{"title":4045,"path":4046,"stem":4047},"Міжсервісна взаємодія на основі протоколу gRPC","\u002Fclient-server-architecture\u002Fgrpc-inter-service-communication","17.client-server-architecture\u002F15.grpc-inter-service-communication",{"title":4049,"path":4050,"stem":4051},"Асинхронний обмін повідомленнями та протоколи черг","\u002Fclient-server-architecture\u002Fasynchronous-message-exchange-and-queue-protocols","17.client-server-architecture\u002F16.asynchronous-message-exchange-and-queue-protocols",{"title":4053,"path":4054,"stem":4055},"Протоколи потокового медіа та технологія WebRTC","\u002Fclient-server-architecture\u002Fstreaming-media-protocols-and-webrtc","17.client-server-architecture\u002F17.streaming-media-protocols-and-webrtc",{"title":4057,"path":4058,"stem":4059},"Моніторинг, безпека та контейнеризація застосунків","\u002Fclient-server-architecture\u002Fmonitoring-security-and-containerization","17.client-server-architecture\u002F18.monitoring-security-and-containerization",{"title":4061,"icon":2118,"path":4062,"stem":4063,"children":4064,"page":59},"Розробка WEB-застосувань","\u002Fweb-development","18.web-development",[4065,4110,4148,4177,4206,4263,4313,4407,4473,4555,4588,4616,4658,4704,4747],{"title":4066,"icon":658,"path":4067,"stem":4068,"children":4069,"page":59},"Архітектура комп'ютерних мереж та мережеві протоколи","\u002Fweb-development\u002Fnetwork-architecture-and-protocols","18.web-development\u002F01.network-architecture-and-protocols",[4070,4074,4078,4082,4086,4090,4094,4098,4102,4106],{"title":4071,"path":4072,"stem":4073},"Еволюція веброзробки та модель клієнт-сервер","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fweb-evolution-client-server","18.web-development\u002F01.network-architecture-and-protocols\u002F01.web-evolution-client-server",{"title":4075,"path":4076,"stem":4077},"Еталонна модель OSI","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fosi-model","18.web-development\u002F01.network-architecture-and-protocols\u002F02.osi-model",{"title":4079,"path":4080,"stem":4081},"Стек протоколів TCP\u002FIP","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Ftcp-ip-stack","18.web-development\u002F01.network-architecture-and-protocols\u002F03.tcp-ip-stack",{"title":4083,"path":4084,"stem":4085},"IP-адресація, порти та сокети","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fip-addressing-ports-sockets","18.web-development\u002F01.network-architecture-and-protocols\u002F04.ip-addressing-ports-sockets",{"title":4087,"path":4088,"stem":4089},"Протоколи TCP та UDP","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Ftcp-udp-protocols","18.web-development\u002F01.network-architecture-and-protocols\u002F05.tcp-udp-protocols",{"title":4091,"path":4092,"stem":4093},"Система доменних імен DNS","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fdns-system","18.web-development\u002F01.network-architecture-and-protocols\u002F06.dns-system",{"title":4095,"path":4096,"stem":4097},"Протокол SMTP та поштові протоколи","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fsmtp-email-protocols","18.web-development\u002F01.network-architecture-and-protocols\u002F07.smtp-email-protocols",{"title":4099,"path":4100,"stem":4101},"Протокол WebSocket","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fwebsocket-protocol","18.web-development\u002F01.network-architecture-and-protocols\u002F08.websocket-protocol",{"title":4103,"path":4104,"stem":4105},"Протокол SSH","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fssh-protocol","18.web-development\u002F01.network-architecture-and-protocols\u002F09.ssh-protocol",{"title":4107,"path":4108,"stem":4109},"Огляд сучасних серверних технологій","\u002Fweb-development\u002Fnetwork-architecture-and-protocols\u002Fmodern-backend-technologies","18.web-development\u002F01.network-architecture-and-protocols\u002F10.modern-backend-technologies",{"title":4111,"icon":4112,"path":4113,"stem":4114,"children":4115,"page":59},"Протокол HTTP та захищена передача даних HTTPS","i-lucide-lock","\u002Fweb-development\u002Fhttp-and-https","18.web-development\u002F02.http-and-https",[4116,4120,4124,4128,4132,4136,4140,4144],{"title":4117,"path":4118,"stem":4119},"Вступ до протоколу HTTP та еволюція веб-технологій","\u002Fweb-development\u002Fhttp-and-https\u002Fintroduction-and-evolution","18.web-development\u002F02.http-and-https\u002F01.introduction-and-evolution",{"title":4121,"path":4122,"stem":4123},"Анатомія HTTP-запиту","\u002Fweb-development\u002Fhttp-and-https\u002Fhttp-request-structure","18.web-development\u002F02.http-and-https\u002F02.http-request-structure",{"title":4125,"path":4126,"stem":4127},"Анатомія HTTP-відповіді","\u002Fweb-development\u002Fhttp-and-https\u002Fhttp-response-structure","18.web-development\u002F02.http-and-https\u002F03.http-response-structure",{"title":4129,"path":4130,"stem":4131},"Методи HTTP та їхня семантика","\u002Fweb-development\u002Fhttp-and-https\u002Fhttp-methods","18.web-development\u002F02.http-and-https\u002F04.http-methods",{"title":4133,"path":4134,"stem":4135},"Коди статусу HTTP та їхнє призначення","\u002Fweb-development\u002Fhttp-and-https\u002Fhttp-status-codes","18.web-development\u002F02.http-and-https\u002F05.http-status-codes",{"title":4137,"path":4138,"stem":4139},"HTTP-заголовки та їхнє призначення","\u002Fweb-development\u002Fhttp-and-https\u002Fhttp-headers","18.web-development\u002F02.http-and-https\u002F06.http-headers",{"title":4141,"path":4142,"stem":4143},"CORS та механізми безпеки HTTP","\u002Fweb-development\u002Fhttp-and-https\u002Fcors-and-security","18.web-development\u002F02.http-and-https\u002F07.cors-and-security",{"title":4145,"path":4146,"stem":4147},"HTTPS та криптографічні основи TLS","\u002Fweb-development\u002Fhttp-and-https\u002Fhttps-and-tls","18.web-development\u002F02.http-and-https\u002F08.https-and-tls",{"title":4149,"icon":2498,"path":4150,"stem":4151,"children":4152,"page":59},"Система типів мови TypeScript","\u002Fweb-development\u002Ftypescript-type-system","18.web-development\u002F03.typescript-type-system",[4153,4157,4161,4165,4169,4173],{"title":4154,"path":4155,"stem":4156},"Знайомство з TypeScript Compiler","\u002Fweb-development\u002Ftypescript-type-system\u002Fintroduction-compiler-config","18.web-development\u002F03.typescript-type-system\u002F01.introduction-compiler-config",{"title":4158,"path":4159,"stem":4160},"Примітивні типи даних: string, number, boolean","\u002Fweb-development\u002Ftypescript-type-system\u002Fprimitive-special-types","18.web-development\u002F03.typescript-type-system\u002F02.primitive-special-types",{"title":4162,"path":4163,"stem":4164},"Масиви, кортежі та об","\u002Fweb-development\u002Ftypescript-type-system\u002Farrays-tuples-objects","18.web-development\u002F03.typescript-type-system\u002F03.arrays-tuples-objects",{"title":4166,"path":4167,"stem":4168},"Псевдоніми типів, Union типи, Intersection типи та літеральні типи","\u002Fweb-development\u002Ftypescript-type-system\u002Funion-intersection-literals","18.web-development\u002F03.typescript-type-system\u002F04.union-intersection-literals",{"title":4170,"path":4171,"stem":4172},"Type Narrowing (звуження типів)","\u002Fweb-development\u002Ftypescript-type-system\u002Ftype-narrowing","18.web-development\u002F03.typescript-type-system\u002F05.type-narrowing",{"title":4174,"path":4175,"stem":4176},"Типізація функцій","\u002Fweb-development\u002Ftypescript-type-system\u002Ffunctions-typing","18.web-development\u002F03.typescript-type-system\u002F06.functions-typing",{"title":4178,"icon":2498,"path":4179,"stem":4180,"children":4181,"page":59},"Розширені засоби мови TypeScript","\u002Fweb-development\u002Ftypescript-advanced","18.web-development\u002F04.typescript-advanced",[4182,4186,4190,4194,4198,4202],{"title":4183,"path":4184,"stem":4185},"Interfaces та Classes","\u002Fweb-development\u002Ftypescript-advanced\u002Finterfaces-classes","18.web-development\u002F04.typescript-advanced\u002F01.interfaces-classes",{"title":4187,"path":4188,"stem":4189},"Основи Generic типів","\u002Fweb-development\u002Ftypescript-advanced\u002Fgenerics-fundamentals","18.web-development\u002F04.typescript-advanced\u002F02.generics-fundamentals",{"title":4191,"path":4192,"stem":4193},"Enums та Decorators","\u002Fweb-development\u002Ftypescript-advanced\u002Fenums-decorators","18.web-development\u002F04.typescript-advanced\u002F03.enums-decorators",{"title":4195,"path":4196,"stem":4197},"Utility Types","\u002Fweb-development\u002Ftypescript-advanced\u002Futility-types","18.web-development\u002F04.typescript-advanced\u002F04.utility-types",{"title":4199,"path":4200,"stem":4201},"Mapped та Conditional Types","\u002Fweb-development\u002Ftypescript-advanced\u002Fmapped-conditional-types","18.web-development\u002F04.typescript-advanced\u002F05.mapped-conditional-types",{"title":4203,"path":4204,"stem":4205},"Модулі та Strict Mode","\u002Fweb-development\u002Ftypescript-advanced\u002Fmodules-strict-mode","18.web-development\u002F04.typescript-advanced\u002F06.modules-strict-mode",{"title":4207,"icon":4208,"path":4209,"stem":4210,"children":4211,"page":59},"Платформа Node.js як середовище виконання","i-devicon-nodejs","\u002Fweb-development\u002Fnodejs-platform","18.web-development\u002F05.nodejs-platform",[4212,4216,4220,4224,4228,4232,4236,4240,4244,4248,4252,4255,4259],{"title":4213,"path":4214,"stem":4215},"Що таке Node.js та його архітектура","\u002Fweb-development\u002Fnodejs-platform\u002Fwhat-is-nodejs","18.web-development\u002F05.nodejs-platform\u002F01.what-is-nodejs",{"title":4217,"path":4218,"stem":4219},"Event Loop — серце Node.js","\u002Fweb-development\u002Fnodejs-platform\u002Fevent-loop","18.web-development\u002F05.nodejs-platform\u002F02.event-loop",{"title":4221,"path":4222,"stem":4223},"Модульні системи: CommonJS vs ES Modules","\u002Fweb-development\u002Fnodejs-platform\u002Fmodule-systems","18.web-development\u002F05.nodejs-platform\u002F03.module-systems",{"title":4225,"path":4226,"stem":4227},"npm та package.json","\u002Fweb-development\u002Fnodejs-platform\u002Fnpm-package-json","18.web-development\u002F05.nodejs-platform\u002F04.npm-package-json",{"title":4229,"path":4230,"stem":4231},"Глобальні об\\","\u002Fweb-development\u002Fnodejs-platform\u002Fglobal-objects","18.web-development\u002F05.nodejs-platform\u002F05.global-objects",{"title":4233,"path":4234,"stem":4235},"Вбудований модуль fs (File System)","\u002Fweb-development\u002Fnodejs-platform\u002Fbuilt-in-modules-fs","18.web-development\u002F05.nodejs-platform\u002F06.built-in-modules-fs",{"title":4237,"path":4238,"stem":4239},"Вбудований модуль path","\u002Fweb-development\u002Fnodejs-platform\u002Fbuilt-in-modules-path","18.web-development\u002F05.nodejs-platform\u002F07.built-in-modules-path",{"title":4241,"path":4242,"stem":4243},"Вбудований модуль http","\u002Fweb-development\u002Fnodejs-platform\u002Fbuilt-in-modules-http","18.web-development\u002F05.nodejs-platform\u002F08.built-in-modules-http",{"title":4245,"path":4246,"stem":4247},"Streams — потоки даних у Node.js","\u002Fweb-development\u002Fnodejs-platform\u002Fstreams","18.web-development\u002F05.nodejs-platform\u002F09.streams",{"title":4249,"path":4250,"stem":4251},"Вбудований модуль util (Utilities)","\u002Fweb-development\u002Fnodejs-platform\u002Fbuilt-in-modules-util","18.web-development\u002F05.nodejs-platform\u002F10.built-in-modules-util",{"title":3141,"path":4253,"stem":4254},"\u002Fweb-development\u002Fnodejs-platform\u002Fenvironment-variables","18.web-development\u002F05.nodejs-platform\u002F11.environment-variables",{"title":4256,"path":4257,"stem":4258},"Інструменти налагодження та розробки","\u002Fweb-development\u002Fnodejs-platform\u002Fdebugging-tools","18.web-development\u002F05.nodejs-platform\u002F12.debugging-tools",{"title":4260,"path":4261,"stem":4262},"Продуктивність та Best Practices","\u002Fweb-development\u002Fnodejs-platform\u002Fperformance-best-practices","18.web-development\u002F05.nodejs-platform\u002F13.performance-best-practices",{"title":4264,"icon":4265,"path":4266,"stem":4267,"children":4268,"page":59},"Асинхронне програмування у Node.js","i-lucide-clock","\u002Fweb-development\u002Fasync-programming-nodejs","18.web-development\u002F06.async-programming-nodejs",[4269,4273,4277,4281,4285,4289,4293,4297,4301,4305,4309],{"title":4270,"path":4271,"stem":4272},"Синхронний vs асинхронний код","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fsync-vs-async","18.web-development\u002F06.async-programming-nodejs\u002F01.sync-vs-async",{"title":4274,"path":4275,"stem":4276},"Callbacks — перша парадигма асинхронності","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fcallbacks","18.web-development\u002F06.async-programming-nodejs\u002F02.callbacks",{"title":4278,"path":4279,"stem":4280},"Promises — стандарт асинхронності","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fpromises","18.web-development\u002F06.async-programming-nodejs\u002F03.promises",{"title":4282,"path":4283,"stem":4284},"Promise комбінатори","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fpromise-combinators","18.web-development\u002F06.async-programming-nodejs\u002F04.promise-combinators",{"title":4286,"path":4287,"stem":4288},"Async\u002FAwait — синтаксичний цукор над Promises","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fasync-await","18.web-development\u002F06.async-programming-nodejs\u002F05.async-await",{"title":4290,"path":4291,"stem":4292},"Паралельне vs послідовне виконання","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fparallel-vs-sequential","18.web-development\u002F06.async-programming-nodejs\u002F06.parallel-vs-sequential",{"title":4294,"path":4295,"stem":4296},"EventEmitter — подієва модель Node.js","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fevent-emitter","18.web-development\u002F06.async-programming-nodejs\u002F07.event-emitter",{"title":4298,"path":4299,"stem":4300},"Worker Threads — багатопотоковість у Node.js","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fworker-threads","18.web-development\u002F06.async-programming-nodejs\u002F08.worker-threads",{"title":4302,"path":4303,"stem":4304},"Child Processes — запуск зовнішніх процесів","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fchild-processes","18.web-development\u002F06.async-programming-nodejs\u002F09.child-processes",{"title":4306,"path":4307,"stem":4308},"Обробка помилок у асинхронному коді","\u002Fweb-development\u002Fasync-programming-nodejs\u002Ferror-handling","18.web-development\u002F06.async-programming-nodejs\u002F10.error-handling",{"title":4310,"path":4311,"stem":4312},"Порівняння Node.js фреймворків","\u002Fweb-development\u002Fasync-programming-nodejs\u002Fnodejs-frameworks","18.web-development\u002F06.async-programming-nodejs\u002F11.nodejs-frameworks",{"title":4314,"icon":4315,"path":4316,"stem":4317,"children":4318,"page":59},"Тема 7. Фреймворк NestJS. Контролери та маршрутизація","i-lucide-route","\u002Fweb-development\u002Fnestjs-controllers-routing","18.web-development\u002F07.nestjs-controllers-routing",[4319,4323,4327,4331,4335,4339,4343,4347,4351,4355,4359,4363,4367,4371,4375,4379,4383,4387,4391,4395,4399,4403],{"title":4320,"path":4321,"stem":4322},"Філософія та архітектура NestJS","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fnestjs-philosophy","18.web-development\u002F07.nestjs-controllers-routing\u002F01.nestjs-philosophy",{"title":4324,"path":4325,"stem":4326},"Три стовпи архітектури: модулі, контролери, провайдери","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fthree-pillars","18.web-development\u002F07.nestjs-controllers-routing\u002F02.three-pillars",{"title":4328,"path":4329,"stem":4330},"Інверсія керування (IoC) та ін","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fioc-and-di","18.web-development\u002F07.nestjs-controllers-routing\u002F03.ioc-and-di",{"title":4332,"path":4333,"stem":4334},"Встановлення NestJS CLI та створення проєкту","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fnestjs-cli-setup","18.web-development\u002F07.nestjs-controllers-routing\u002F04.nestjs-cli-setup",{"title":4336,"path":4337,"stem":4338},"Структура проєкту NestJS та конвенції","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fproject-structure","18.web-development\u002F07.nestjs-controllers-routing\u002F05.project-structure",{"title":4340,"path":4341,"stem":4342},"Контролери: основи маршрутизації","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fcontrollers-basics","18.web-development\u002F07.nestjs-controllers-routing\u002F06.controllers-basics",{"title":4344,"path":4345,"stem":4346},"Декоратори маршрутизації HTTP-методів","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Froute-decorators","18.web-development\u002F07.nestjs-controllers-routing\u002F07.route-decorators",{"title":4348,"path":4349,"stem":4350},"Параметри маршруту та декоратор @Param","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Froute-parameters","18.web-development\u002F07.nestjs-controllers-routing\u002F08.route-parameters",{"title":4352,"path":4353,"stem":4354},"Query-параметри та декоратор @Query","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fquery-parameters","18.web-development\u002F07.nestjs-controllers-routing\u002F09.query-parameters",{"title":4356,"path":4357,"stem":4358},"Тіло запиту та декоратор @Body","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Frequest-body","18.web-development\u002F07.nestjs-controllers-routing\u002F10.request-body",{"title":4360,"path":4361,"stem":4362},"Робота з заголовками запиту та відповіді","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fheaders-decorators","18.web-development\u002F07.nestjs-controllers-routing\u002F11.headers-decorators",{"title":4364,"path":4365,"stem":4366},"Data Transfer Objects (DTO): визначення та призначення","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fdto-introduction","18.web-development\u002F07.nestjs-controllers-routing\u002F12.dto-introduction",{"title":4368,"path":4369,"stem":4370},"Об'єкти Request та Response","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Frequest-response-objects","18.web-development\u002F07.nestjs-controllers-routing\u002F13.request-response-objects",{"title":4372,"path":4373,"stem":4374},"HTTP-статус коди та декоратор @HttpCode","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fhttp-status-codes","18.web-development\u002F07.nestjs-controllers-routing\u002F14.http-status-codes",{"title":4376,"path":4377,"stem":4378},"Перенаправлення (Redirects) та декоратор @Redirect","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fredirects","18.web-development\u002F07.nestjs-controllers-routing\u002F15.redirects",{"title":4380,"path":4381,"stem":4382},"Асинхронні обробники та Observables","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fasync-handlers","18.web-development\u002F07.nestjs-controllers-routing\u002F16.async-handlers",{"title":4384,"path":4385,"stem":4386},"Маршрутизація за піддоменами та версіонування API","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fsub-domain-routing","18.web-development\u002F07.nestjs-controllers-routing\u002F17.sub-domain-routing",{"title":4388,"path":4389,"stem":4390},"Області видимості контролерів (Scopes)","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fcontroller-scopes","18.web-development\u002F07.nestjs-controllers-routing\u002F18.controller-scopes",{"title":4392,"path":4393,"stem":4394},"Основні команди NestJS CLI","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fnestjs-cli-commands","18.web-development\u002F07.nestjs-controllers-routing\u002F19.nestjs-cli-commands",{"title":4396,"path":4397,"stem":4398},"Практичний приклад: створення CRUD-контролера","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fcrud-example","18.web-development\u002F07.nestjs-controllers-routing\u002F20.crud-example",{"title":4400,"path":4401,"stem":4402},"Тестування контролерів","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Ftesting-controllers","18.web-development\u002F07.nestjs-controllers-routing\u002F21.testing-controllers",{"title":4404,"path":4405,"stem":4406},"Best Practices для контролерів та маршрутизації","\u002Fweb-development\u002Fnestjs-controllers-routing\u002Fbest-practices","18.web-development\u002F07.nestjs-controllers-routing\u002F22.best-practices",{"title":4408,"icon":4409,"path":4410,"stem":4411,"children":4412,"page":59},"Тема 8. Провайдери, сервіси та модульна система NestJS","i-lucide-package","\u002Fweb-development\u002Fnestjs-providers-modules","18.web-development\u002F08.nestjs-providers-modules",[4413,4417,4421,4425,4429,4433,4437,4441,4445,4449,4453,4457,4461,4465,4469],{"title":4414,"path":4415,"stem":4416},"Концепція провайдерів у NestJS","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fproviders-concept","18.web-development\u002F08.nestjs-providers-modules\u002F01.providers-concept",{"title":4418,"path":4419,"stem":4420},"Сервіси: інкапсуляція бізнес-логіки","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fservices-business-logic","18.web-development\u002F08.nestjs-providers-modules\u002F02.services-business-logic",{"title":4422,"path":4423,"stem":4424},"Практика ін","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fdependency-injection-practice","18.web-development\u002F08.nestjs-providers-modules\u002F03.dependency-injection-practice",{"title":4426,"path":4427,"stem":4428},"Custom Providers: useValue, useClass, useFactory, useExisting","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fcustom-providers","18.web-development\u002F08.nestjs-providers-modules\u002F04.custom-providers",{"title":4430,"path":4431,"stem":4432},"Injection Tokens: рядкові та символьні токени","\u002Fweb-development\u002Fnestjs-providers-modules\u002Finjection-tokens","18.web-development\u002F08.nestjs-providers-modules\u002F05.injection-tokens",{"title":4434,"path":4435,"stem":4436},"Опціональні провайдери та декоратор @Optional","\u002Fweb-development\u002Fnestjs-providers-modules\u002Foptional-providers","18.web-development\u002F08.nestjs-providers-modules\u002F07.optional-providers",{"title":4438,"path":4439,"stem":4440},"Структура модулів: imports, controllers, providers, exports","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fmodules-structure","18.web-development\u002F08.nestjs-providers-modules\u002F08.modules-structure",{"title":4442,"path":4443,"stem":4444},"Feature Modules: ізоляція функціональності","\u002Fweb-development\u002Fnestjs-providers-modules\u002Ffeature-modules","18.web-development\u002F08.nestjs-providers-modules\u002F09.feature-modules",{"title":4446,"path":4447,"stem":4448},"Shared Modules: перевикористання провайдерів","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fshared-modules","18.web-development\u002F08.nestjs-providers-modules\u002F10.shared-modules",{"title":4450,"path":4451,"stem":4452},"Global Modules та декоратор @Global","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fglobal-modules","18.web-development\u002F08.nestjs-providers-modules\u002F11.global-modules",{"title":4454,"path":4455,"stem":4456},"Dynamic Modules: конфігурація під час виконання","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fdynamic-modules","18.web-development\u002F08.nestjs-providers-modules\u002F12.dynamic-modules",{"title":4458,"path":4459,"stem":4460},"Циклічні залежності та forwardRef","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fcircular-dependencies","18.web-development\u002F08.nestjs-providers-modules\u002F13.circular-dependencies",{"title":4462,"path":4463,"stem":4464},"Lifecycle Hooks: хуки життєвого циклу","\u002Fweb-development\u002Fnestjs-providers-modules\u002Flifecycle-hooks","18.web-development\u002F08.nestjs-providers-modules\u002F14.lifecycle-hooks",{"title":4466,"path":4467,"stem":4468},"ModuleRef: динамічний доступ до провайдерів","\u002Fweb-development\u002Fnestjs-providers-modules\u002Fmodule-reference","18.web-development\u002F08.nestjs-providers-modules\u002F15.module-reference",{"title":4470,"path":4471,"stem":4472},"Тестування сервісів та провайдерів","\u002Fweb-development\u002Fnestjs-providers-modules\u002Ftesting-services","18.web-development\u002F08.nestjs-providers-modules\u002F16.testing-services",{"title":4474,"icon":4475,"path":4476,"stem":4477,"children":4478,"page":59},"Тема 9. Валідація даних та конвеєр обробки запитів у NestJS","i-lucide-filter","\u002Fweb-development\u002Fnestjs-validation-pipeline","18.web-development\u002F09.nestjs-validation-pipeline",[4479,4483,4487,4491,4495,4499,4503,4507,4511,4515,4519,4523,4527,4531,4535,4539,4543,4547,4551],{"title":4480,"path":4481,"stem":4482},"Request Pipeline: конвеєр обробки запитів","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Frequest-pipeline","18.web-development\u002F09.nestjs-validation-pipeline\u002F01.request-pipeline",{"title":4484,"path":4485,"stem":4486},"Pipes: концепція трансформації та валідації","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fpipes-concept","18.web-development\u002F09.nestjs-validation-pipeline\u002F02.pipes-concept",{"title":4488,"path":4489,"stem":4490},"Вбудовані pipes: ParseIntPipe, ParseBoolPipe, ParseUUIDPipe","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fbuilt-in-pipes","18.web-development\u002F09.nestjs-validation-pipeline\u002F03.built-in-pipes",{"title":4492,"path":4493,"stem":4494},"ValidationPipe: автоматична валідація DTO","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fvalidation-pipe","18.web-development\u002F09.nestjs-validation-pipeline\u002F04.validation-pipe",{"title":4496,"path":4497,"stem":4498},"Декоратори class-validator для DTO","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fclass-validator-decorators","18.web-development\u002F09.nestjs-validation-pipeline\u002F05.class-validator-decorators",{"title":4500,"path":4501,"stem":4502},"Створення кастомних валідаторів","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fcustom-validators","18.web-development\u002F09.nestjs-validation-pipeline\u002F06.custom-validators",{"title":4504,"path":4505,"stem":4506},"Створення власних Pipes","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fcustom-pipes","18.web-development\u002F09.nestjs-validation-pipeline\u002F07.custom-pipes",{"title":4508,"path":4509,"stem":4510},"Основи Middleware","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fmiddleware-basics","18.web-development\u002F09.nestjs-validation-pipeline\u002F08.middleware-basics",{"title":4512,"path":4513,"stem":4514},"Практичні приклади Middleware","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fmiddleware-examples","18.web-development\u002F09.nestjs-validation-pipeline\u002F09.middleware-examples",{"title":4516,"path":4517,"stem":4518},"Guards: захисні перехоплювачі доступу","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fguards-concept","18.web-development\u002F09.nestjs-validation-pipeline\u002F10.guards-concept",{"title":4520,"path":4521,"stem":4522},"Створення кастомних Guards","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fcustom-guards","18.web-development\u002F09.nestjs-validation-pipeline\u002F11.custom-guards",{"title":4524,"path":4525,"stem":4526},"Interceptors: перехоплення та трансформація відповідей","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Finterceptors-concept","18.web-development\u002F09.nestjs-validation-pipeline\u002F12.interceptors-concept",{"title":4528,"path":4529,"stem":4530},"Практичні приклади Interceptors","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Finterceptor-examples","18.web-development\u002F09.nestjs-validation-pipeline\u002F13.interceptor-examples",{"title":4532,"path":4533,"stem":4534},"Exception Filters: обробка виключень","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fexception-filters","18.web-development\u002F09.nestjs-validation-pipeline\u002F14.exception-filters",{"title":4536,"path":4537,"stem":4538},"Custom Exception Filters: спеціалізовані фільтри","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fcustom-exception-filters","18.web-development\u002F09.nestjs-validation-pipeline\u002F15.custom-exception-filters",{"title":4540,"path":4541,"stem":4542},"Execution Context: контекст виконання","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fexecution-context","18.web-development\u002F09.nestjs-validation-pipeline\u002F16.execution-context",{"title":4544,"path":4545,"stem":4546},"Custom Decorators: власні декоратори","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fcustom-decorators","18.web-development\u002F09.nestjs-validation-pipeline\u002F17.custom-decorators",{"title":4548,"path":4549,"stem":4550},"Global Components: глобальні компоненти","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fglobal-components","18.web-development\u002F09.nestjs-validation-pipeline\u002F18.global-components",{"title":4552,"path":4553,"stem":4554},"Pipeline Best Practices: найкращі практики","\u002Fweb-development\u002Fnestjs-validation-pipeline\u002Fpipeline-best-practices","18.web-development\u002F09.nestjs-validation-pipeline\u002F19.pipeline-best-practices",{"title":4556,"icon":2865,"path":4557,"stem":4558,"children":4559,"page":59},"Інтеграція реляційних баз даних засобами TypeORM","\u002Fweb-development\u002Ftypeorm-integration","18.web-development\u002F10.typeorm-integration",[4560,4564,4568,4572,4576,4580,4584],{"title":4561,"path":4562,"stem":4563},"Робота з базами даних у Node.js через нативні драйвери","\u002Fweb-development\u002Ftypeorm-integration\u002F01-nodejs-database-drivers","18.web-development\u002F10.typeorm-integration\u002F01-nodejs-database-drivers",{"title":4565,"path":4566,"stem":4567},"ORM та знайомство з TypeORM","\u002Fweb-development\u002Ftypeorm-integration\u002F02-orm-and-typeorm-intro","18.web-development\u002F10.typeorm-integration\u002F02-orm-and-typeorm-intro",{"title":4569,"path":4570,"stem":4571},"Налаштування TypeORM у NestJS проєкті","\u002Fweb-development\u002Ftypeorm-integration\u002F03-typeorm-setup-nestjs","18.web-development\u002F10.typeorm-integration\u002F03-typeorm-setup-nestjs",{"title":4573,"path":4574,"stem":4575},"Entity класи та декоратори TypeORM","\u002Fweb-development\u002Ftypeorm-integration\u002F04-entities-and-decorators","18.web-development\u002F10.typeorm-integration\u002F04-entities-and-decorators",{"title":4577,"path":4578,"stem":4579},"Repository Pattern та CRUD операції","\u002Fweb-development\u002Ftypeorm-integration\u002F05-repository-pattern-crud","18.web-development\u002F10.typeorm-integration\u002F05-repository-pattern-crud",{"title":4581,"path":4582,"stem":4583},"Пагінація та фільтрація даних","\u002Fweb-development\u002Ftypeorm-integration\u002F06-pagination-filtering","18.web-development\u002F10.typeorm-integration\u002F06-pagination-filtering",{"title":4585,"path":4586,"stem":4587},"QueryBuilder для складних запитів","\u002Fweb-development\u002Ftypeorm-integration\u002F07-query-builder","18.web-development\u002F10.typeorm-integration\u002F07-query-builder",{"title":4589,"icon":4590,"path":4591,"stem":4592,"children":4593,"page":59},"Зв'язки між сутностями, міграції та оптимізація запитів","i-lucide-git-branch","\u002Fweb-development\u002Fentity-relations-migrations","18.web-development\u002F11.entity-relations-migrations",[4594,4598,4602,4606,4610],{"title":4595,"path":4596,"stem":4597},"Зв'язки One-to-Many та Many-to-One","\u002Fweb-development\u002Fentity-relations-migrations\u002F01-one-to-many-many-to-one","18.web-development\u002F11.entity-relations-migrations\u002F01-one-to-many-many-to-one",{"title":4599,"path":4600,"stem":4601},"Зв'язки One-to-One та Many-to-Many","\u002Fweb-development\u002Fentity-relations-migrations\u002F02-one-to-one-many-to-many","18.web-development\u002F11.entity-relations-migrations\u002F02-one-to-one-many-to-many",{"title":4603,"path":4604,"stem":4605},"Керування міграціями бази даних","\u002Fweb-development\u002Fentity-relations-migrations\u002F03-migrations-management","18.web-development\u002F11.entity-relations-migrations\u002F03-migrations-management",{"title":4607,"path":4608,"stem":4609},"Транзакції у TypeORM","\u002Fweb-development\u002Fentity-relations-migrations\u002F04-transactions","18.web-development\u002F11.entity-relations-migrations\u002F04-transactions",{"title":4611,"path":4612,"stem":4613,"children":4614},"Індекси та оптимізація запитів","\u002Fweb-development\u002Fentity-relations-migrations\u002F05-indexes-optimization","18.web-development\u002F11.entity-relations-migrations\u002F05-indexes-optimization",[4615],{"title":4611,"path":4612,"stem":4613},{"title":4617,"icon":4618,"path":4619,"stem":4620,"children":4621,"page":59},"Механізми автентифікації у вебзастосунках","i-lucide-key","\u002Fweb-development\u002Fauthentication","18.web-development\u002F12.authentication",[4622,4626,4630,4634,4638,4642,4646,4650,4654],{"title":4623,"path":4624,"stem":4625},"Автентифікація vs Авторизація","\u002Fweb-development\u002Fauthentication\u002F01-authentication-vs-authorization","18.web-development\u002F12.authentication\u002F01-authentication-vs-authorization",{"title":4627,"path":4628,"stem":4629},"Стратегії автентифікації","\u002Fweb-development\u002Fauthentication\u002F02-authentication-strategies","18.web-development\u002F12.authentication\u002F02-authentication-strategies",{"title":4631,"path":4632,"stem":4633},"Автентифікація на основі сесій","\u002Fweb-development\u002Fauthentication\u002F03-session-based-authentication","18.web-development\u002F12.authentication\u002F03-session-based-authentication",{"title":4635,"path":4636,"stem":4637},"Структура JSON Web Token (JWT)","\u002Fweb-development\u002Fauthentication\u002F04-jwt-structure","18.web-development\u002F12.authentication\u002F04-jwt-structure",{"title":4639,"path":4640,"stem":4641},"Інтеграція JWT у NestJS","\u002Fweb-development\u002Fauthentication\u002F05-nestjs-jwt-integration","18.web-development\u002F12.authentication\u002F05-nestjs-jwt-integration",{"title":4643,"path":4644,"stem":4645},"Passport.js стратегії у NestJS","\u002Fweb-development\u002Fauthentication\u002F06-passport-strategies","18.web-development\u002F12.authentication\u002F06-passport-strategies",{"title":4647,"path":4648,"stem":4649},"Безпечне зберігання паролів: хешування та криптографічний захист","\u002Fweb-development\u002Fauthentication\u002F07-password-hashing","18.web-development\u002F12.authentication\u002F07-password-hashing",{"title":4651,"path":4652,"stem":4653},"Refresh Token та безпечне оновлення доступу","\u002Fweb-development\u002Fauthentication\u002F08-refresh-tokens","18.web-development\u002F12.authentication\u002F08-refresh-tokens",{"title":4655,"path":4656,"stem":4657},"OAuth 2.0 та OpenID Connect: делегована автентифікація","\u002Fweb-development\u002Fauthentication\u002F09-oauth2-openid","18.web-development\u002F12.authentication\u002F09-oauth2-openid",{"title":4659,"icon":4660,"path":4661,"stem":4662,"children":4663,"page":59},"Авторизація та безпека серверних застосунків","i-lucide-shield","\u002Fweb-development\u002Fauthorization-security","18.web-development\u002F13.authorization-security",[4664,4668,4672,4676,4680,4684,4688,4692,4696,4700],{"title":4665,"path":4666,"stem":4667},"Моделі авторизації","\u002Fweb-development\u002Fauthorization-security\u002F01-authorization-models","18.web-development\u002F13.authorization-security\u002F01-authorization-models",{"title":4669,"path":4670,"stem":4671},"Реалізація RBAC у NestJS","\u002Fweb-development\u002Fauthorization-security\u002F02-rbac-implementation","18.web-development\u002F13.authorization-security\u002F02-rbac-implementation",{"title":4673,"path":4674,"stem":4675},"Permission-Based Access Control","\u002Fweb-development\u002Fauthorization-security\u002F03-permission-based-access","18.web-development\u002F13.authorization-security\u002F03-permission-based-access",{"title":4677,"path":4678,"stem":4679},"ABAC та бібліотека CASL","\u002Fweb-development\u002Fauthorization-security\u002F04-abac-casl","18.web-development\u002F13.authorization-security\u002F04-abac-casl",{"title":4681,"path":4682,"stem":4683},"Кастомні декоратори та метадані","\u002Fweb-development\u002Fauthorization-security\u002F05-custom-decorators-metadata","18.web-development\u002F13.authorization-security\u002F05-custom-decorators-metadata",{"title":4685,"path":4686,"stem":4687},"Конфігурація CORS","\u002Fweb-development\u002Fauthorization-security\u002F06-cors-configuration","18.web-development\u002F13.authorization-security\u002F06-cors-configuration",{"title":4689,"path":4690,"stem":4691},"Захист через HTTP Security Headers (Helmet)","\u002Fweb-development\u002Fauthorization-security\u002F07-helmet-security-headers","18.web-development\u002F13.authorization-security\u002F07-helmet-security-headers",{"title":4693,"path":4694,"stem":4695},"Rate Limiting та Throttling","\u002Fweb-development\u002Fauthorization-security\u002F08-rate-limiting-throttling","18.web-development\u002F13.authorization-security\u002F08-rate-limiting-throttling",{"title":4697,"path":4698,"stem":4699},"Захист від поширених атак","\u002Fweb-development\u002Fauthorization-security\u002F09-common-attacks-protection","18.web-development\u002F13.authorization-security\u002F09-common-attacks-protection",{"title":4701,"path":4702,"stem":4703},"HTTPS у продакшені","\u002Fweb-development\u002Fauthorization-security\u002F10-https-production","18.web-development\u002F13.authorization-security\u002F10-https-production",{"title":4705,"icon":871,"path":4706,"stem":4707,"children":4708,"page":59},"Комунікація у реальному часі, нотифікації та фонові задачі","\u002Fweb-development\u002Frealtime-notifications-jobs","18.web-development\u002F14.realtime-notifications-jobs",[4709,4713,4717,4721,4725,4729,4732,4735,4739,4743],{"title":4710,"path":4711,"stem":4712},"Методи комунікації у реальному часі","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F01-realtime-communication-methods","18.web-development\u002F14.realtime-notifications-jobs\u002F01-realtime-communication-methods",{"title":4714,"path":4715,"stem":4716},"WebSocket Gateway у NestJS","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F02-websocket-gateway","18.web-development\u002F14.realtime-notifications-jobs\u002F02-websocket-gateway",{"title":4718,"path":4719,"stem":4720},"Lifecycle та Rooms у WebSocket","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F03-websocket-lifecycle-rooms","18.web-development\u002F14.realtime-notifications-jobs\u002F03-websocket-lifecycle-rooms",{"title":4722,"path":4723,"stem":4724},"Server-Sent Events (SSE)","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F04-server-sent-events","18.web-development\u002F14.realtime-notifications-jobs\u002F04-server-sent-events",{"title":4726,"path":4727,"stem":4728},"Архітектура системи нотифікацій","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F05-notification-system","18.web-development\u002F14.realtime-notifications-jobs\u002F05-notification-system",{"title":904,"path":4730,"stem":4731},"\u002Fweb-development\u002Frealtime-notifications-jobs\u002F06-email-notifications","18.web-development\u002F14.realtime-notifications-jobs\u002F06-email-notifications",{"title":900,"path":4733,"stem":4734},"\u002Fweb-development\u002Frealtime-notifications-jobs\u002F07-web-push-notifications","18.web-development\u002F14.realtime-notifications-jobs\u002F07-web-push-notifications",{"title":4736,"path":4737,"stem":4738},"Фонові задачі та черги","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F08-background-jobs-queues","18.web-development\u002F14.realtime-notifications-jobs\u002F08-background-jobs-queues",{"title":4740,"path":4741,"stem":4742},"Планувальники та Cron jobs","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F09-schedulers-cron","18.web-development\u002F14.realtime-notifications-jobs\u002F09-schedulers-cron",{"title":4744,"path":4745,"stem":4746},"Практичні сценарії застосування","\u002Fweb-development\u002Frealtime-notifications-jobs\u002F10-practical-scenarios","18.web-development\u002F14.realtime-notifications-jobs\u002F10-practical-scenarios",{"title":4748,"icon":4749,"path":4750,"stem":4751,"children":4752,"page":59},"Тестування, документування та розгортання застосунків","i-lucide-rocket","\u002Fweb-development\u002Ftesting-documentation-deployment","18.web-development\u002F15.testing-documentation-deployment",[4753,4757,4761,4765,4769,4773,4777,4781,4785,4789],{"title":4754,"path":4755,"stem":4756},"Піраміда тестування та стратегія","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F01-testing-pyramid-strategy","18.web-development\u002F15.testing-documentation-deployment\u002F01-testing-pyramid-strategy",{"title":4758,"path":4759,"stem":4760},"Основи Jest у NestJS","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F02-jest-nestjs-basics","18.web-development\u002F15.testing-documentation-deployment\u002F02-jest-nestjs-basics",{"title":4762,"path":4763,"stem":4764},"Unit-тестування сервісів","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F03-unit-testing-services","18.web-development\u002F15.testing-documentation-deployment\u002F03-unit-testing-services",{"title":4766,"path":4767,"stem":4768},"E2E тестування та покриття коду","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F04-e2e-testing-coverage","18.web-development\u002F15.testing-documentation-deployment\u002F04-e2e-testing-coverage",{"title":4770,"path":4771,"stem":4772},"Swagger, OpenAPI, Scalar та Arazzo","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F05-swagger-openapi","18.web-development\u002F15.testing-documentation-deployment\u002F05-swagger-openapi",{"title":4774,"path":4775,"stem":4776},"Керування конфігурацією","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F06-configuration-management","18.web-development\u002F15.testing-documentation-deployment\u002F06-configuration-management",{"title":4778,"path":4779,"stem":4780},"Docker та контейнеризація","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F07-docker-containerization","18.web-development\u002F15.testing-documentation-deployment\u002F07-docker-containerization",{"title":4782,"path":4783,"stem":4784},"CI\u002FCD Pipelines","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F08-cicd-pipelines","18.web-development\u002F15.testing-documentation-deployment\u002F08-cicd-pipelines",{"title":4786,"path":4787,"stem":4788},"Логування та моніторинг","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F09-logging-monitoring","18.web-development\u002F15.testing-documentation-deployment\u002F09-logging-monitoring",{"title":4790,"path":4791,"stem":4792},"Серіалізація та компресія","\u002Fweb-development\u002Ftesting-documentation-deployment\u002F10-serialization-compression","18.web-development\u002F15.testing-documentation-deployment\u002F10-serialization-compression",{"title":4794,"icon":4795,"path":4796,"stem":4797,"children":4798,"page":59},"AI Core: мислення AI","i-lucide-brain","\u002Fai-core","19.ai-core",[4799,4840,4889,4927],{"title":4800,"icon":4749,"path":4801,"stem":4802,"children":4803,"page":59},"Вхід у професію AI Native Developer","\u002Fai-core\u002Fai-native-developer","19.ai-core\u002F01.ai-native-developer",[4804,4808,4812,4816,4820,4824,4828,4832,4836],{"title":4805,"path":4806,"stem":4807},"Вступ до професії розробника цифрових продуктів","\u002Fai-core\u002Fai-native-developer\u002Fdigital-products","19.ai-core\u002F01.ai-native-developer\u002F01.digital-products",{"title":4809,"path":4810,"stem":4811},"Професія розробника програмного забезпечення","\u002Fai-core\u002Fai-native-developer\u002Fsoftware-developer","19.ai-core\u002F01.ai-native-developer\u002F02.software-developer",{"title":4813,"path":4814,"stem":4815},"Професія AI Native Developer","\u002Fai-core\u002Fai-native-developer\u002Fai-native-developer","19.ai-core\u002F01.ai-native-developer\u002F03.ai-native-developer",{"title":4817,"path":4818,"stem":4819},"Вплив AI на розробку програмного забезпечення","\u002Fai-core\u002Fai-native-developer\u002Fai-impact-on-development","19.ai-core\u002F01.ai-native-developer\u002F04.ai-impact-on-development",{"title":4821,"path":4822,"stem":4823},"Життєвий цикл цифрового продукту","\u002Fai-core\u002Fai-native-developer\u002Fproduct-lifecycle","19.ai-core\u002F01.ai-native-developer\u002F05.product-lifecycle",{"title":4825,"path":4826,"stem":4827},"Застосування AI на етапах створення цифрового продукту","\u002Fai-core\u002Fai-native-developer\u002Fai-in-product-creation","19.ai-core\u002F01.ai-native-developer\u002F06.ai-in-product-creation",{"title":4829,"path":4830,"stem":4831},"Розподіл завдань між людиною та AI","\u002Fai-core\u002Fai-native-developer\u002Fhuman-vs-ai-tasks","19.ai-core\u002F01.ai-native-developer\u002F07.human-vs-ai-tasks",{"title":4833,"path":4834,"stem":4835},"Компетенції AI Native Developer","\u002Fai-core\u002Fai-native-developer\u002Fcompetencies","19.ai-core\u002F01.ai-native-developer\u002F08.competencies",{"title":4837,"path":4838,"stem":4839},"Карта професійного розвитку AI Native Developer","\u002Fai-core\u002Fai-native-developer\u002Fcareer-roadmap","19.ai-core\u002F01.ai-native-developer\u002F09.career-roadmap",{"title":4841,"icon":255,"path":4842,"stem":4843,"children":4844,"page":59},"Штучний інтелект і машинне навчання","\u002Fai-core\u002Fai-and-machine-learning","19.ai-core\u002F02.ai-and-machine-learning",[4845,4849,4853,4857,4861,4865,4869,4873,4877,4881,4885],{"title":4846,"path":4847,"stem":4848},"Штучний інтелект","\u002Fai-core\u002Fai-and-machine-learning\u002Fwhat-is-ai","19.ai-core\u002F02.ai-and-machine-learning\u002F01.what-is-ai",{"title":4850,"path":4851,"stem":4852},"Відмінність AI від інших програмних систем","\u002Fai-core\u002Fai-and-machine-learning\u002Fai-vs-automation","19.ai-core\u002F02.ai-and-machine-learning\u002F02.ai-vs-automation",{"title":4854,"path":4855,"stem":4856},"Завдання штучного інтелекту","\u002Fai-core\u002Fai-and-machine-learning\u002Fai-tasks","19.ai-core\u002F02.ai-and-machine-learning\u002F03.ai-tasks",{"title":4858,"path":4859,"stem":4860},"Machine Learning","\u002Fai-core\u002Fai-and-machine-learning\u002Fmachine-learning","19.ai-core\u002F02.ai-and-machine-learning\u002F04.machine-learning",{"title":4862,"path":4863,"stem":4864},"Machine Learning Workflow","\u002Fai-core\u002Fai-and-machine-learning\u002Fml-workflow","19.ai-core\u002F02.ai-and-machine-learning\u002F05.ml-workflow",{"title":4866,"path":4867,"stem":4868},"Типи машинного навчання","\u002Fai-core\u002Fai-and-machine-learning\u002Fml-types","19.ai-core\u002F02.ai-and-machine-learning\u002F06.ml-types",{"title":4870,"path":4871,"stem":4872},"Generative AI","\u002Fai-core\u002Fai-and-machine-learning\u002Fgenerative-ai","19.ai-core\u002F02.ai-and-machine-learning\u002F07.generative-ai",{"title":4874,"path":4875,"stem":4876},"Типи контенту, створюваного AI","\u002Fai-core\u002Fai-and-machine-learning\u002Fai-content-types","19.ai-core\u002F02.ai-and-machine-learning\u002F08.ai-content-types",{"title":4878,"path":4879,"stem":4880},"Великі мовні моделі","\u002Fai-core\u002Fai-and-machine-learning\u002Flarge-language-models","19.ai-core\u002F02.ai-and-machine-learning\u002F09.large-language-models",{"title":4882,"path":4883,"stem":4884},"Можливості та обмеження Generative AI","\u002Fai-core\u002Fai-and-machine-learning\u002Fcapabilities-and-limitations","19.ai-core\u002F02.ai-and-machine-learning\u002F10.capabilities-and-limitations",{"title":4886,"path":4887,"stem":4888},"Сучасні AI-асистенти","\u002Fai-core\u002Fai-and-machine-learning\u002Fmodern-ai-assistants","19.ai-core\u002F02.ai-and-machine-learning\u002F11.modern-ai-assistants",{"title":4890,"icon":4891,"path":4892,"stem":4893,"children":4894,"page":59},"Постановка завдань для AI: принципи створення промптів","i-lucide-message-square-text","\u002Fai-core\u002Fprompt-engineering","19.ai-core\u002F03.prompt-engineering",[4895,4899,4903,4907,4911,4915,4919,4923],{"title":4896,"path":4897,"stem":4898},"Промпт як інструмент","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-as-tool","19.ai-core\u002F03.prompt-engineering\u002F01.prompt-as-tool",{"title":4900,"path":4901,"stem":4902},"Принципи створення промптів","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-principles","19.ai-core\u002F03.prompt-engineering\u002F02.prompt-principles",{"title":4904,"path":4905,"stem":4906},"Структура промпта","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-structure","19.ai-core\u002F03.prompt-engineering\u002F03.prompt-structure",{"title":4908,"path":4909,"stem":4910},"Види промптів за типом задачі","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-types","19.ai-core\u002F03.prompt-engineering\u002F04.prompt-types",{"title":4912,"path":4913,"stem":4914},"Прийоми посилення промпта","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-enhancement","19.ai-core\u002F03.prompt-engineering\u002F05.prompt-enhancement",{"title":4916,"path":4917,"stem":4918},"Розбір і покращення промпта","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-analysis","19.ai-core\u002F03.prompt-engineering\u002F06.prompt-analysis",{"title":4920,"path":4921,"stem":4922},"Типові помилки під час створення промптів","\u002Fai-core\u002Fprompt-engineering\u002Fcommon-mistakes","19.ai-core\u002F03.prompt-engineering\u002F07.common-mistakes",{"title":4924,"path":4925,"stem":4926},"Практикум: особиста бібліотека промптів","\u002Fai-core\u002Fprompt-engineering\u002Fprompt-library","19.ai-core\u002F03.prompt-engineering\u002F08.prompt-library",{"title":4928,"icon":793,"path":4929,"stem":4930,"children":4931,"page":59},"Перевірка результатів, безпека та AI Native Workflow","\u002Fai-core\u002Fverification-security-workflow","19.ai-core\u002F04.verification-security-workflow",[4932,4936,4940,4944,4948,4952,4956,4960,4964],{"title":4933,"path":4934,"stem":4935},"Межі можливостей AI","\u002Fai-core\u002Fverification-security-workflow\u002Fai-limitations","19.ai-core\u002F04.verification-security-workflow\u002F01.ai-limitations",{"title":4937,"path":4938,"stem":4939},"Галюцинації AI","\u002Fai-core\u002Fverification-security-workflow\u002Fai-hallucinations","19.ai-core\u002F04.verification-security-workflow\u002F02.ai-hallucinations",{"title":4941,"path":4942,"stem":4943},"Критичне мислення під час роботи з AI","\u002Fai-core\u002Fverification-security-workflow\u002Fcritical-thinking","19.ai-core\u002F04.verification-security-workflow\u002F03.critical-thinking",{"title":4945,"path":4946,"stem":4947},"Перевірка результатів роботи AI","\u002Fai-core\u002Fverification-security-workflow\u002Fresult-verification","19.ai-core\u002F04.verification-security-workflow\u002F04.result-verification",{"title":4949,"path":4950,"stem":4951},"Захист даних під час роботи з AI","\u002Fai-core\u002Fverification-security-workflow\u002Fdata-protection","19.ai-core\u002F04.verification-security-workflow\u002F05.data-protection",{"title":4953,"path":4954,"stem":4955},"Авторське право та навчальна доброчесність","\u002Fai-core\u002Fverification-security-workflow\u002Fcopyright-integrity","19.ai-core\u002F04.verification-security-workflow\u002F06.copyright-integrity",{"title":4957,"path":4958,"stem":4959},"Відповідальне використання AI","\u002Fai-core\u002Fverification-security-workflow\u002Fresponsible-use","19.ai-core\u002F04.verification-security-workflow\u002F07.responsible-use",{"title":4961,"path":4962,"stem":4963},"AI Native Workflow","\u002Fai-core\u002Fverification-security-workflow\u002Fai-native-workflow","19.ai-core\u002F04.verification-security-workflow\u002F08.ai-native-workflow",{"title":4965,"path":4966,"stem":4967},"Застосування AI Native Workflow під час створення цифрового продукту","\u002Fai-core\u002Fverification-security-workflow\u002Fworkflow-in-practice","19.ai-core\u002F04.verification-security-workflow\u002F09.workflow-in-practice",{"title":4969,"icon":4970,"path":4971,"stem":4972,"children":4973,"page":59},"AI Developer: Vibe Coding Sprint","i-lucide-code-xml","\u002Fai-developer","20.ai-developer",[4974,5000,5022,5043],{"title":4975,"icon":4976,"path":4977,"stem":4978,"children":4979,"page":59},"Проєктування і чорнова версія","i-lucide-pencil-ruler","\u002Fai-developer\u002Fdraft-creation","20.ai-developer\u002F01.draft-creation",[4980,4984,4988,4992,4996],{"title":4981,"path":4982,"stem":4983},"Парадигма Vibe Coding Workflow","\u002Fai-developer\u002Fdraft-creation\u002Fvibe-coding-workflow","20.ai-developer\u002F01.draft-creation\u002F01.vibe-coding-workflow",{"title":4985,"path":4986,"stem":4987},"AI-середовище швидкої розробки","\u002Fai-developer\u002Fdraft-creation\u002Fai-ide-environment","20.ai-developer\u002F01.draft-creation\u002F02.ai-ide-environment",{"title":4989,"path":4990,"stem":4991},"Користувацьке завдання та межі першої версії","\u002Fai-developer\u002Fdraft-creation\u002Fproduct-scope-and-mvp","20.ai-developer\u002F01.draft-creation\u002F03.product-scope-and-mvp",{"title":4993,"path":4994,"stem":4995},"Архітектура інтерфейсу та стани застосунку","\u002Fai-developer\u002Fdraft-creation\u002Fapplication-architecture-and-states","20.ai-developer\u002F01.draft-creation\u002F04.application-architecture-and-states",{"title":4997,"path":4998,"stem":4999},"Генерація та фіксація чорнової версії","\u002Fai-developer\u002Fdraft-creation\u002Fgenerating-draft-version","20.ai-developer\u002F01.draft-creation\u002F05.generating-draft-version",{"title":5001,"icon":5002,"path":5003,"stem":5004,"children":5005,"page":59},"Перша робоча версія","i-lucide-play-circle","\u002Fai-developer\u002Ffirst-working-version","20.ai-developer\u002F02.first-working-version",[5006,5010,5014,5018],{"title":5007,"path":5008,"stem":5009},"Уточнення контексту проєкту для AI","\u002Fai-developer\u002Ffirst-working-version\u002Frefining-project-context","20.ai-developer\u002F02.first-working-version\u002F01.refining-project-context",{"title":5011,"path":5012,"stem":5013},"Стратегія завдань для AI-розробки","\u002Fai-developer\u002Ffirst-working-version\u002Fai-prompting-strategy","20.ai-developer\u002F02.first-working-version\u002F02.ai-prompting-strategy",{"title":5015,"path":5016,"stem":5017},"Доопрацювання до першої робочої версії","\u002Fai-developer\u002Ffirst-working-version\u002Frefining-to-working-version","20.ai-developer\u002F02.first-working-version\u002F03.refining-to-working-version",{"title":5019,"path":5020,"stem":5021},"Перевірка першої робочої версії","\u002Fai-developer\u002Ffirst-working-version\u002Ftesting-first-working-version","20.ai-developer\u002F02.first-working-version\u002F04.testing-first-working-version",{"title":5023,"icon":3072,"path":5024,"stem":5025,"children":5026,"page":59},"Ітерації, дебагінг та відновлення","\u002Fai-developer\u002Fiteration-debugging-recovery","20.ai-developer\u002F03.iteration-debugging-recovery",[5027,5031,5035,5039],{"title":5028,"path":5029,"stem":5030},"Управління точковими змінами продукту","\u002Fai-developer\u002Fiteration-debugging-recovery\u002Fchange-management","20.ai-developer\u002F03.iteration-debugging-recovery\u002F01.change-management",{"title":5032,"path":5033,"stem":5034},"Надійність інтерфейсу та обробка помилок","\u002Fai-developer\u002Fiteration-debugging-recovery\u002Fscenario-reliability-and-errors","20.ai-developer\u002F03.iteration-debugging-recovery\u002F02.scenario-reliability-and-errors",{"title":5036,"path":5037,"stem":5038},"Керування контекстом і збереження версій","\u002Fai-developer\u002Fiteration-debugging-recovery\u002Fproject-context-and-versions","20.ai-developer\u002F03.iteration-debugging-recovery\u002F03.project-context-and-versions",{"title":5040,"path":5041,"stem":5042},"Збої AI-розробки, ліміти та аварійне відновлення","\u002Fai-developer\u002Fiteration-debugging-recovery\u002Fai-breakdowns-and-recovery","20.ai-developer\u002F03.iteration-debugging-recovery\u002F04.ai-breakdowns-and-recovery",{"title":5044,"icon":5045,"path":5046,"stem":5047,"children":5048,"page":59},"Перевірка та завершення продукту","i-lucide-check-check","\u002Fai-developer\u002Fverification-and-completion","20.ai-developer\u002F04.verification-and-completion",[5049,5053,5057],{"title":5050,"path":5051,"stem":5052},"Комплексний аудит та підсумкове тестування","\u002Fai-developer\u002Fverification-and-completion\u002Ffinal-product-testing","20.ai-developer\u002F04.verification-and-completion\u002F01.final-product-testing",{"title":5054,"path":5055,"stem":5056},"Підготовка підсумкової версії коду","\u002Fai-developer\u002Fverification-and-completion\u002Fpreparing-release-version","20.ai-developer\u002F04.verification-and-completion\u002F02.preparing-release-version",{"title":5058,"path":5059,"stem":5060},"Демонстрація, публікація та критерії оцінювання","\u002Fai-developer\u002Fverification-and-completion\u002Fproduct-showcase-and-publishing","20.ai-developer\u002F04.verification-and-completion\u002F03.product-showcase-and-publishing",{"title":5062,"path":5063,"stem":5064,"children":5065,"page":59},"Tailwind","\u002Ftailwind","21.tailwind",[5066,5070,5074,5078,5082,5086,5090,5094,5098,5102,5106,5110],{"title":5067,"path":5068,"stem":5069},"Що таке Tailwind CSS і навіщо він потрібен","\u002Ftailwind\u002Ftailwind-intro-philosophy","21.tailwind\u002F01.tailwind-intro-philosophy",{"title":5071,"path":5072,"stem":5073},"Встановлення та налаштування Tailwind CSS v4","\u002Ftailwind\u002Ftailwind-installation-setup","21.tailwind\u002F02.tailwind-installation-setup",{"title":5075,"path":5076,"stem":5077},"Utility-класи: основи та система Tailwind","\u002Ftailwind\u002Ftailwind-utility-classes-core","21.tailwind\u002F03.tailwind-utility-classes-core",{"title":5079,"path":5080,"stem":5081},"Layout: Flexbox та Grid через Tailwind","\u002Ftailwind\u002Ftailwind-flexbox-grid","21.tailwind\u002F04.tailwind-flexbox-grid",{"title":5083,"path":5084,"stem":5085},"Кастомізація теми через @theme у Tailwind v4","\u002Ftailwind\u002Ftailwind-theme-customization","21.tailwind\u002F05.tailwind-theme-customization",{"title":5087,"path":5088,"stem":5089},"Варіанти: hover, focus, responsive, dark mode та нові v4","\u002Ftailwind\u002Ftailwind-variants-states","21.tailwind\u002F06.tailwind-variants-states",{"title":5091,"path":5092,"stem":5093},"Типографіка та система кольорів у Tailwind v4","\u002Ftailwind\u002Ftailwind-typography-colors","21.tailwind\u002F07.tailwind-typography-colors",{"title":5095,"path":5096,"stem":5097},"Компоненти та повторюваність: @apply, @utility та патерни","\u002Ftailwind\u002Ftailwind-components-patterns","21.tailwind\u002F08.tailwind-components-patterns",{"title":5099,"path":5100,"stem":5101},"Темна тема та система дизайн-токенів у Tailwind v4","\u002Ftailwind\u002Ftailwind-dark-mode-theming","21.tailwind\u002F09.tailwind-dark-mode-theming",{"title":5103,"path":5104,"stem":5105},"Довільні значення та контейнерні запити у Tailwind v4","\u002Ftailwind\u002Ftailwind-arbitrary-container-queries","21.tailwind\u002F10.tailwind-arbitrary-container-queries",{"title":5107,"path":5108,"stem":5109},"Анімації, трансформації та 3D у Tailwind v4","\u002Ftailwind\u002Ftailwind-animations-transforms","21.tailwind\u002F11.tailwind-animations-transforms",{"title":5111,"path":5112,"stem":5113},"Tailwind CLI, PostCSS та інтеграція з фреймворками","\u002Ftailwind\u002Ftailwind-cli-tooling","21.tailwind\u002F12.tailwind-cli-tooling",{"title":5115,"path":5116,"stem":5117,"children":5118,"page":59},"React Typescript","\u002Freact-typescript","22.react-typescript",[5119,5144,5148,5152,5156,5160,5164,5168,5172],{"title":5120,"path":5121,"stem":5122,"children":5123,"page":59},"From Html To Project","\u002Freact-typescript\u002Ffrom-html-to-project","22.react-typescript\u002F01.from-html-to-project",[5124,5128,5132,5136,5140],{"title":5125,"path":5126,"stem":5127},"Від одного HTML-файлу до повноцінного проєкту","\u002Freact-typescript\u002Ffrom-html-to-project\u002Fevolution","22.react-typescript\u002F01.from-html-to-project\u002F01.evolution",{"title":5129,"path":5130,"stem":5131},"Що таке React","\u002Freact-typescript\u002Ffrom-html-to-project\u002Fwhat-is-react","22.react-typescript\u002F01.from-html-to-project\u002F02.what-is-react",{"title":5133,"path":5134,"stem":5135},"JSX та TSX — синтаксичний цукор, а не магія","\u002Freact-typescript\u002Ffrom-html-to-project\u002Fjsx-tsx-syntax","22.react-typescript\u002F01.from-html-to-project\u002F03.jsx-tsx-syntax",{"title":5137,"path":5138,"stem":5139},"Компоненти — будівельні блоки інтерфейсу","\u002Freact-typescript\u002Ffrom-html-to-project\u002Fcomponents","22.react-typescript\u002F01.from-html-to-project\u002F04.components",{"title":5141,"path":5142,"stem":5143},"JSX — розмітка всередині TypeScript","\u002Freact-typescript\u002Ffrom-html-to-project\u002Fjsx-expressions","22.react-typescript\u002F01.from-html-to-project\u002F05.jsx-expressions",{"title":5145,"path":5146,"stem":5147},"Хук useReducer: структуроване управління складним станом","\u002Freact-typescript\u002Fuse-reducer","22.react-typescript\u002F23.use-reducer",{"title":5149,"path":5150,"stem":5151},"Context API: передавання даних без «пропс-дрілінгу»","\u002Freact-typescript\u002Fcontext-api","22.react-typescript\u002F24.context-api",{"title":5153,"path":5154,"stem":5155},"Синхронізація з ефектами: хук useEffect та функції очищення","\u002Freact-typescript\u002Fuse-effect","22.react-typescript\u002F27.use-effect",{"title":5157,"path":5158,"stem":5159},"Можливо, вам не потрібен ефект: антипатерни та альтернативи","\u002Freact-typescript\u002Fyou-might-not-need-effect","22.react-typescript\u002F28.you-might-not-need-effect",{"title":5161,"path":5162,"stem":5163},"Життєвий цикл реактивних ефектів: мислення процесами синхронізації","\u002Freact-typescript\u002Flifecycle-of-reactive-effects","22.react-typescript\u002F29.lifecycle-of-reactive-effects",{"title":5165,"path":5166,"stem":5167},"Розділення подій та ефектів: реактивна проти нереактивної логіки","\u002Freact-typescript\u002Fseparating-events-from-effects","22.react-typescript\u002F30.separating-events-from-effects",{"title":5169,"path":5170,"stem":5171},"Видалення зайвих залежностей ефектів та оптимізація синхронізації","\u002Freact-typescript\u002Fremoving-effect-dependencies","22.react-typescript\u002F31.removing-effect-dependencies",{"title":5173,"path":5174,"stem":5175},"Кастомні хуки: повторне використання та композиція реактивної логіки","\u002Freact-typescript\u002Fcustom-hooks","22.react-typescript\u002F32.custom-hooks",{"title":5177,"path":5178,"stem":5179},"Тестування компонентів діаграм та пісочниць","\u002Ftest-components","98.test-components",{"id":5181,"title":3913,"body":5182,"description":15136,"extension":15137,"links":15138,"meta":15139,"navigation":5526,"path":3914,"seo":15140,"stem":3915,"__hash__":15141},"docs\u002F16.ai-python\u002F13.pytorch-intro\u002F04.advanced-topics.md",{"type":5183,"value":5184,"toc":15109},"minimark",[5185,5262,5267,5271,5320,5329,5332,5335,5339,5344,5354,5368,5451,5462,5476,5480,5483,5986,6058,6062,6069,6693,6769,6774,7215,7305,7309,7312,7959,8097,8099,8103,8107,8110,8115,8141,8151,8155,8161,8165,8170,8191,8197,8212,8216,8221,8859,8863,8869,8883,8909,8919,9064,9084,9088,9900,9955,9957,9961,9965,9972,10373,10377,10681,10685,11240,11319,11321,11325,11329,11332,11336,11346,11985,11989,12027,12069,12073,12076,12586,12749,12751,12755,12759,12765,12773,12777,12783,13140,13229,13235,13626,13690,13694,13700,13814,13818,14473,14573,14575,14579,14699,14998,15000,15004,15007,15013,15019,15030,15036,15100,15105],[5186,5187,5188,5212],"card-group",{},[5189,5190,5193],"card",{"icon":5191,"title":5192},"i-lucide-target","🎯 Мета статті",[5194,5195,5196,5200,5203,5206,5209],"ul",{},[5197,5198,5199],"li",{},"Навчитися використовувати GPU для прискорення тренування",[5197,5201,5202],{},"Застосувати Mixed Precision для економії пам'яті та прискорення",[5197,5204,5205],{},"Опанувати профілювання та оптимізацію коду PyTorch",[5197,5207,5208],{},"Зрозуміти правильні способи збереження та завантаження моделей",[5197,5210,5211],{},"Експортувати моделі у TorchScript та ONNX для production deployment",[5189,5213,5215],{"icon":4618,"title":5214},"🔑 Ключові терміни",[5194,5216,5217,5229,5235,5241,5247,5253],{},[5197,5218,5219,5228],{},[5220,5221,5222,5223,5227],"strong",{},"GPU (",[5224,5225,5226],"em",{},"Graphics Processing Unit",")"," — графічний процесор для паралельних обчислень",[5197,5230,5231,5234],{},[5220,5232,5233],{},"CUDA"," — платформа NVIDIA для GPU-обчислень",[5197,5236,5237,5240],{},[5220,5238,5239],{},"Mixed Precision"," — комбінація FP16 та FP32 для економії пам'яті",[5197,5242,5243,5246],{},[5220,5244,5245],{},"State Dict"," — словник параметрів моделі для збереження",[5197,5248,5249,5252],{},[5220,5250,5251],{},"TorchScript"," — компіляція моделі для незалежного C++ runtime",[5197,5254,5255,5261],{},[5220,5256,5257,5258,5227],{},"ONNX (",[5224,5259,5260],{},"Open Neural Network Exchange"," — міжплатформенний формат моделей",[5263,5264,5266],"h2",{"id":5265},"вступ-від-прототипу-до-production","Вступ: Від прототипу до production",[5268,5269,5270],"p",{},"У попередніх статтях ми навчилися будувати нейронні мережі, тренувати їх та застосовувати регуляризацію. Але між навчальним прикладом та реальним production-застосунком є значний розрив:",[5186,5272,5273,5299],{},[5189,5274,5277],{"icon":5275,"title":5276},"i-lucide-graduation-cap","🎓 Навчальний проєкт",[5194,5278,5279,5282,5285,5293,5296],{},[5197,5280,5281],{},"Датасет влазить у пам'ять",[5197,5283,5284],{},"Тренування на CPU (години)",[5197,5286,5287,5288,5292],{},"Модель у ",[5289,5290,5291],"code",{},".py"," файлі",[5197,5294,5295],{},"Inference у Python",[5197,5297,5298],{},"Використання лише локально",[5189,5300,5303],{"icon":5301,"title":5302},"i-lucide-factory","🏭 Production система",[5194,5304,5305,5308,5311,5314,5317],{},[5197,5306,5307],{},"Датасет у терабайтах",[5197,5309,5310],{},"Тренування на GPU (хвилини)",[5197,5312,5313],{},"Модель у компільованому форматі",[5197,5315,5316],{},"Inference у C++\u002Fмобільних застосунках",[5197,5318,5319],{},"Deployment на серверах\u002Fedge-пристроях",[5321,5322,5323],"blockquote",{},[5268,5324,5325,5328],{},[5220,5326,5327],{},"Аналогія:"," Навчальний проєкт — це як спекти м'ясо на домашній кухні. Production — це як налаштувати фабрику, що виробляє 10 000 порцій на день, з контролем якості, логістикою та оптимізацією кожного кроку.",[5268,5330,5331],{},"Ця стаття присвячена інструментам та технікам, які дозволяють перейти від експериментів до промислового використання PyTorch.",[5333,5334],"hr",{},[5263,5336,5338],{"id":5337},"частина-1-gpu-прискорення","Частина 1: GPU-прискорення",[5340,5341,5343],"h3",{"id":5342},"чому-gpu-швидший-за-cpu-для-deep-learning","Чому GPU швидший за CPU для Deep Learning?",[5268,5345,5346,5349,5350,5353],{},[5220,5347,5348],{},"Центральний процесор (CPU)"," оптимізований для послідовного виконання складних інструкцій. Він має ",[5220,5351,5352],{},"мало ядер"," (4–16 у сучасних процесорах), але кожне ядро дуже потужне та швидке.",[5268,5355,5356,5359,5360,5363,5364,5367],{},[5220,5357,5358],{},"Графічний процесор (GPU)"," спочатку створювався для рендерингу графіки — завдання, що вимагає виконання ",[5220,5361,5362],{},"однакових операцій"," над мільйонами пікселів паралельно. Сучасна GPU має ",[5220,5365,5366],{},"тисячі ядер"," (2000–10000), але кожне ядро простіше та повільніше за CPU-ядро.",[5186,5369,5370,5411],{},[5189,5371,5373,5378,5392,5397],{"icon":255,"title":5372},"💻 CPU",[5268,5374,5375],{},[5220,5376,5377],{},"Архітектура:",[5194,5379,5380,5383,5386,5389],{},[5197,5381,5382],{},"8–16 потужних ядер",[5197,5384,5385],{},"Висока тактова частота (3–5 GHz)",[5197,5387,5388],{},"Великий кеш (L1, L2, L3)",[5197,5390,5391],{},"Оптимізація для різних завдань",[5268,5393,5394],{},[5220,5395,5396],{},"Ідеальні завдання:",[5194,5398,5399,5402,5405,5408],{},[5197,5400,5401],{},"Послідовні обчислення",[5197,5403,5404],{},"Умовні розгалуження",[5197,5406,5407],{},"Системні операції",[5197,5409,5410],{},"Роб\nота з файлами",[5189,5412,5415,5419,5433,5437],{"icon":5413,"title":5414},"i-lucide-gamepad-2","🎮 GPU",[5268,5416,5417],{},[5220,5418,5377],{},[5194,5420,5421,5424,5427,5430],{},[5197,5422,5423],{},"2000–10000 простих ядер",[5197,5425,5426],{},"Нижча тактова частота (~1.5 GHz)",[5197,5428,5429],{},"Висока пропускна здатність пам'яті",[5197,5431,5432],{},"Оптимізація для паралельних операцій",[5268,5434,5435],{},[5220,5436,5396],{},[5194,5438,5439,5442,5445,5448],{},[5197,5440,5441],{},"Матричні множення",[5197,5443,5444],{},"Згортки (convolutions)",[5197,5446,5447],{},"Поелементні операції",[5197,5449,5450],{},"Пакетна обробка даних",[5321,5452,5453],{},[5268,5454,5455,5457,5458,5461],{},[5220,5456,5327],{}," CPU — це як один дуже розумний професор, що вирішує складні математичні задачі послідовно. GPU — це як тисяча студентів-першокурсників, кожен з яких може вирішити просту задачу. Для обчислення ",[5289,5459,5460],{},"1+1"," мільйон разів професор програє студентам у тисячі разів.",[5268,5463,5464,5467,5468,5471,5472,5475],{},[5220,5465,5466],{},"Чому це важливо для нейронних мереж?"," Операції у нейронній мережі — це переважно ",[5220,5469,5470],{},"матричні множення"," та ",[5220,5473,5474],{},"поелементні функції"," (ReLU, sigmoid). Це саме ті операції, що ідеально паралеляться на GPU.",[5340,5477,5479],{"id":5478},"порівняння-швидкості-cpu-vs-gpu","Порівняння швидкості: CPU vs GPU",[5268,5481,5482],{},"Розглянемо конкретний експеримент — множення двох великих матриць:",[5484,5485,5487],"jupyter-notebook",{"title":5486},"cpu_vs_gpu_benchmark.ipynb",[5488,5489,5491,5906],"jupyter-cell",{"execution-count":5490},"1",[5492,5493,5498],"pre",{"className":5494,"code":5495,"language":5496,"meta":5497,"style":5497},"language-python shiki shiki-themes light-plus dark-plus dark-plus","import torch\nimport time\n\n# Розмір матриць\nsize = 5000\n\n# Створюємо матриці на CPU\nA_cpu = torch.randn(size, size)\nB_cpu = torch.randn(size, size)\n\n# Вимірюємо час на CPU\nstart = time.time()\nC_cpu = torch.matmul(A_cpu, B_cpu)\ncpu_time = time.time() - start\n\nprint(f\"CPU обчислення:\")\nprint(f\"  Розмір матриці: {size}×{size}\")\nprint(f\"  Час: {cpu_time:.3f} сек\\n\")\n\n# Якщо доступна GPU\nif torch.cuda.is_available():\n    # Переміщуємо на GPU\n    A_gpu = A_cpu.cuda()\n    B_gpu = B_cpu.cuda()\n    \n    # \"Розігрів\" GPU (перші операції завжди повільніші)\n    _ = torch.matmul(A_gpu, B_gpu)\n    torch.cuda.synchronize()\n    \n    # Вимірюємо час на GPU\n    start = time.time()\n    C_gpu = torch.matmul(A_gpu, B_gpu)\n    torch.cuda.synchronize()  # Чекаємо завершення операції на GPU\n    gpu_time = time.time() - start\n    \n    print(f\"GPU обчислення:\")\n    print(f\"  Назва GPU: {torch.cuda.get_device_name(0)}\")\n    print(f\"  Час: {gpu_time:.3f} сек\")\n    print(f\"  Прискорення: {cpu_time \u002F gpu_time:.1f}×\")\nelse:\n    print(\"GPU недоступна на цій системі\")\n","python","",[5289,5499,5500,5513,5521,5528,5535,5545,5550,5556,5562,5568,5573,5579,5585,5591,5597,5602,5623,5658,5689,5694,5700,5709,5715,5721,5727,5733,5739,5745,5751,5756,5762,5768,5774,5783,5789,5794,5809,5837,5860,5885,5894],{"__ignoreMap":5497},[5501,5502,5505,5509],"span",{"class":5503,"line":5504},"line",1,[5501,5506,5508],{"class":5507},"s8xlr","import",[5501,5510,5512],{"class":5511},"sHH4Y"," torch\n",[5501,5514,5516,5518],{"class":5503,"line":5515},2,[5501,5517,5508],{"class":5507},[5501,5519,5520],{"class":5511}," time\n",[5501,5522,5524],{"class":5503,"line":5523},3,[5501,5525,5527],{"emptyLinePlaceholder":5526},true,"\n",[5501,5529,5531],{"class":5503,"line":5530},4,[5501,5532,5534],{"class":5533},"spJ8K","# Розмір матриць\n",[5501,5536,5538,5541],{"class":5503,"line":5537},5,[5501,5539,5540],{"class":5511},"size = ",[5501,5542,5544],{"class":5543},"sJj4R","5000\n",[5501,5546,5548],{"class":5503,"line":5547},6,[5501,5549,5527],{"emptyLinePlaceholder":5526},[5501,5551,5553],{"class":5503,"line":5552},7,[5501,5554,5555],{"class":5533},"# Створюємо матриці на CPU\n",[5501,5557,5559],{"class":5503,"line":5558},8,[5501,5560,5561],{"class":5511},"A_cpu = torch.randn(size, size)\n",[5501,5563,5565],{"class":5503,"line":5564},9,[5501,5566,5567],{"class":5511},"B_cpu = torch.randn(size, size)\n",[5501,5569,5571],{"class":5503,"line":5570},10,[5501,5572,5527],{"emptyLinePlaceholder":5526},[5501,5574,5576],{"class":5503,"line":5575},11,[5501,5577,5578],{"class":5533},"# Вимірюємо час на CPU\n",[5501,5580,5582],{"class":5503,"line":5581},12,[5501,5583,5584],{"class":5511},"start = time.time()\n",[5501,5586,5588],{"class":5503,"line":5587},13,[5501,5589,5590],{"class":5511},"C_cpu = torch.matmul(A_cpu, B_cpu)\n",[5501,5592,5594],{"class":5503,"line":5593},14,[5501,5595,5596],{"class":5511},"cpu_time = time.time() - start\n",[5501,5598,5600],{"class":5503,"line":5599},15,[5501,5601,5527],{"emptyLinePlaceholder":5526},[5501,5603,5605,5609,5612,5616,5620],{"class":5503,"line":5604},16,[5501,5606,5608],{"class":5607},"s8Opu","print",[5501,5610,5611],{"class":5511},"(",[5501,5613,5615],{"class":5614},"su1O8","f",[5501,5617,5619],{"class":5618},"sbdoH","\"CPU обчислення:\"",[5501,5621,5622],{"class":5511},")\n",[5501,5624,5626,5628,5630,5632,5635,5638,5641,5644,5647,5649,5651,5653,5656],{"class":5503,"line":5625},17,[5501,5627,5608],{"class":5607},[5501,5629,5611],{"class":5511},[5501,5631,5615],{"class":5614},[5501,5633,5634],{"class":5618},"\"  Розмір матриці: ",[5501,5636,5637],{"class":5614},"{",[5501,5639,5640],{"class":5511},"size",[5501,5642,5643],{"class":5614},"}",[5501,5645,5646],{"class":5618},"×",[5501,5648,5637],{"class":5614},[5501,5650,5640],{"class":5511},[5501,5652,5643],{"class":5614},[5501,5654,5655],{"class":5618},"\"",[5501,5657,5622],{"class":5511},[5501,5659,5661,5663,5665,5667,5670,5672,5675,5678,5681,5685,5687],{"class":5503,"line":5660},18,[5501,5662,5608],{"class":5607},[5501,5664,5611],{"class":5511},[5501,5666,5615],{"class":5614},[5501,5668,5669],{"class":5618},"\"  Час: ",[5501,5671,5637],{"class":5614},[5501,5673,5674],{"class":5511},"cpu_time",[5501,5676,5677],{"class":5614},":.3f}",[5501,5679,5680],{"class":5618}," сек",[5501,5682,5684],{"class":5683},"sjcCO","\\n",[5501,5686,5655],{"class":5618},[5501,5688,5622],{"class":5511},[5501,5690,5692],{"class":5503,"line":5691},19,[5501,5693,5527],{"emptyLinePlaceholder":5526},[5501,5695,5697],{"class":5503,"line":5696},20,[5501,5698,5699],{"class":5533},"# Якщо доступна GPU\n",[5501,5701,5703,5706],{"class":5503,"line":5702},21,[5501,5704,5705],{"class":5507},"if",[5501,5707,5708],{"class":5511}," torch.cuda.is_available():\n",[5501,5710,5712],{"class":5503,"line":5711},22,[5501,5713,5714],{"class":5533},"    # Переміщуємо на GPU\n",[5501,5716,5718],{"class":5503,"line":5717},23,[5501,5719,5720],{"class":5511},"    A_gpu = A_cpu.cuda()\n",[5501,5722,5724],{"class":5503,"line":5723},24,[5501,5725,5726],{"class":5511},"    B_gpu = B_cpu.cuda()\n",[5501,5728,5730],{"class":5503,"line":5729},25,[5501,5731,5732],{"class":5511},"    \n",[5501,5734,5736],{"class":5503,"line":5735},26,[5501,5737,5738],{"class":5533},"    # \"Розігрів\" GPU (перші операції завжди повільніші)\n",[5501,5740,5742],{"class":5503,"line":5741},27,[5501,5743,5744],{"class":5511},"    _ = torch.matmul(A_gpu, B_gpu)\n",[5501,5746,5748],{"class":5503,"line":5747},28,[5501,5749,5750],{"class":5511},"    torch.cuda.synchronize()\n",[5501,5752,5754],{"class":5503,"line":5753},29,[5501,5755,5732],{"class":5511},[5501,5757,5759],{"class":5503,"line":5758},30,[5501,5760,5761],{"class":5533},"    # Вимірюємо час на GPU\n",[5501,5763,5765],{"class":5503,"line":5764},31,[5501,5766,5767],{"class":5511},"    start = time.time()\n",[5501,5769,5771],{"class":5503,"line":5770},32,[5501,5772,5773],{"class":5511},"    C_gpu = torch.matmul(A_gpu, B_gpu)\n",[5501,5775,5777,5780],{"class":5503,"line":5776},33,[5501,5778,5779],{"class":5511},"    torch.cuda.synchronize()  ",[5501,5781,5782],{"class":5533},"# Чекаємо завершення операції на GPU\n",[5501,5784,5786],{"class":5503,"line":5785},34,[5501,5787,5788],{"class":5511},"    gpu_time = time.time() - start\n",[5501,5790,5792],{"class":5503,"line":5791},35,[5501,5793,5732],{"class":5511},[5501,5795,5797,5800,5802,5804,5807],{"class":5503,"line":5796},36,[5501,5798,5799],{"class":5607},"    print",[5501,5801,5611],{"class":5511},[5501,5803,5615],{"class":5614},[5501,5805,5806],{"class":5618},"\"GPU обчислення:\"",[5501,5808,5622],{"class":5511},[5501,5810,5812,5814,5816,5818,5821,5823,5826,5829,5831,5833,5835],{"class":5503,"line":5811},37,[5501,5813,5799],{"class":5607},[5501,5815,5611],{"class":5511},[5501,5817,5615],{"class":5614},[5501,5819,5820],{"class":5618},"\"  Назва GPU: ",[5501,5822,5637],{"class":5614},[5501,5824,5825],{"class":5511},"torch.cuda.get_device_name(",[5501,5827,5828],{"class":5543},"0",[5501,5830,5227],{"class":5511},[5501,5832,5643],{"class":5614},[5501,5834,5655],{"class":5618},[5501,5836,5622],{"class":5511},[5501,5838,5840,5842,5844,5846,5848,5850,5853,5855,5858],{"class":5503,"line":5839},38,[5501,5841,5799],{"class":5607},[5501,5843,5611],{"class":5511},[5501,5845,5615],{"class":5614},[5501,5847,5669],{"class":5618},[5501,5849,5637],{"class":5614},[5501,5851,5852],{"class":5511},"gpu_time",[5501,5854,5677],{"class":5614},[5501,5856,5857],{"class":5618}," сек\"",[5501,5859,5622],{"class":5511},[5501,5861,5863,5865,5867,5869,5872,5874,5877,5880,5883],{"class":5503,"line":5862},39,[5501,5864,5799],{"class":5607},[5501,5866,5611],{"class":5511},[5501,5868,5615],{"class":5614},[5501,5870,5871],{"class":5618},"\"  Прискорення: ",[5501,5873,5637],{"class":5614},[5501,5875,5876],{"class":5511},"cpu_time \u002F gpu_time",[5501,5878,5879],{"class":5614},":.1f}",[5501,5881,5882],{"class":5618},"×\"",[5501,5884,5622],{"class":5511},[5501,5886,5888,5891],{"class":5503,"line":5887},40,[5501,5889,5890],{"class":5507},"else",[5501,5892,5893],{"class":5511},":\n",[5501,5895,5897,5899,5901,5904],{"class":5503,"line":5896},41,[5501,5898,5799],{"class":5607},[5501,5900,5611],{"class":5511},[5501,5902,5903],{"class":5618},"\"GPU недоступна на цій системі\"",[5501,5905,5622],{"class":5511},[5907,5908,5909,5977],"template",{"v-slot:output":5497},[5910,5911,5912,5933],"table",{},[5913,5914,5915],"thead",{},[5916,5917,5918,5923,5927,5930],"tr",{},[5919,5920,5922],"th",{"align":5921},"left","Апаратний пристрій",[5919,5924,5926],{"align":5925},"center","Розмір матриці",[5919,5928,5929],{"align":5925},"Час множення ($N \\times N$)",[5919,5931,5932],{"align":5925},"Прискорення (Speedup)",[5934,5935,5936,5955],"tbody",{},[5916,5937,5938,5943,5946,5952],{},[5939,5940,5941],"td",{"align":5921},[5220,5942,5348],{},[5939,5944,5945],{"align":5925},"$5000 \\times 5000$",[5939,5947,5948,5951],{"align":5925},[5289,5949,5950],{},"8.234"," с",[5939,5953,5954],{"align":5925},"$1.0\\times$ (базовий рівень)",[5916,5956,5957,5962,5964,5971],{},[5939,5958,5959],{"align":5921},[5220,5960,5961],{},"Графічний процесор (GPU CUDA)",[5939,5963,5945],{"align":5925},[5939,5965,5966],{"align":5925},[5220,5967,5968,5951],{},[5289,5969,5970],{},"0.095",[5939,5972,5973,5974],{"align":5925},"🚀 ",[5220,5975,5976],{},"$86.7\\times$ швидше",[5268,5978,5979],{},[5980,5981],"img",{"alt":5982,"className":5983,"src":5985},"Порівняння продуктивності GPU\u002FCPU та оптимізація пам'яті за допомогою Automatic Mixed Precision",[5984],"diagram-img","\u002Fimages\u002Fai-python\u002Fpytorch-intro\u002Fadvanced-topics\u002F01.png",[5987,5988,5989,5994,6048],"tip",{},[5268,5990,5991],{},[5220,5992,5993],{},"Типове прискорення для різних операцій:",[5910,5995,5996,6006],{},[5913,5997,5998],{},[5916,5999,6000,6003],{},[5919,6001,6002],{"align":5921},"Операція",[5919,6004,6005],{"align":5921},"Прискорення GPU",[5934,6007,6008,6016,6024,6032,6040],{},[5916,6009,6010,6013],{},[5939,6011,6012],{"align":5921},"Матричне множення",[5939,6014,6015],{"align":5921},"20–100×",[5916,6017,6018,6021],{},[5939,6019,6020],{"align":5921},"Згортки (Conv2d)",[5939,6022,6023],{"align":5921},"30–150×",[5916,6025,6026,6029],{},[5939,6027,6028],{"align":5921},"Батч-нормалізація",[5939,6030,6031],{"align":5921},"10–50×",[5916,6033,6034,6037],{},[5939,6035,6036],{"align":5921},"Активації (ReLU, etc.)",[5939,6038,6039],{"align":5921},"5–20×",[5916,6041,6042,6045],{},[5939,6043,6044],{"align":5921},"Копіювання даних",[5939,6046,6047],{"align":5921},"0.1–2× (може бути повільніше!)",[5268,6049,6050,6053,6054,6057],{},[5220,6051,6052],{},"Висновок:"," GPU дає максимальне прискорення для ",[5220,6055,6056],{},"обчислювально важких"," операцій. Для дрібних операцій overhead переміщення даних може нівелювати виграш.",[5340,6059,6061],{"id":6060},"переміщення-тензорів-та-моделей-на-gpu","Переміщення тензорів та моделей на GPU",[5268,6063,6064,6065,6068],{},"PyTorch використовує поняття ",[5220,6066,6067],{},"device"," — пристрій, на якому зберігається та обчислюється тензор.",[5484,6070,6072,6345],{"title":6071},"moving_to_gpu.ipynb",[5488,6073,6074,6249],{"execution-count":5490},[5492,6075,6077],{"className":5494,"code":6076,"language":5496,"meta":5497,"style":5497},"import torch\n\n# Перевірка доступності CUDA (NVIDIA GPU)\nprint(f\"CUDA доступна: {torch.cuda.is_available()}\")\n\nif torch.cuda.is_available():\n    print(f\"Кількість GPU: {torch.cuda.device_count()}\")\n    print(f\"Поточна GPU: {torch.cuda.current_device()}\")\n    print(f\"Назва GPU: {torch.cuda.get_device_name(0)}\")\n    \n    # Інформація про пам'ять\n    total_memory = torch.cuda.get_device_properties(0).total_memory \u002F (1024**3)\n    print(f\"Загальна пам'ять: {total_memory:.2f} GB\")\n",[5289,6078,6079,6085,6089,6094,6116,6120,6126,6148,6170,6195,6199,6204,6225],{"__ignoreMap":5497},[5501,6080,6081,6083],{"class":5503,"line":5504},[5501,6082,5508],{"class":5507},[5501,6084,5512],{"class":5511},[5501,6086,6087],{"class":5503,"line":5515},[5501,6088,5527],{"emptyLinePlaceholder":5526},[5501,6090,6091],{"class":5503,"line":5523},[5501,6092,6093],{"class":5533},"# Перевірка доступності CUDA (NVIDIA GPU)\n",[5501,6095,6096,6098,6100,6102,6105,6107,6110,6112,6114],{"class":5503,"line":5530},[5501,6097,5608],{"class":5607},[5501,6099,5611],{"class":5511},[5501,6101,5615],{"class":5614},[5501,6103,6104],{"class":5618},"\"CUDA доступна: ",[5501,6106,5637],{"class":5614},[5501,6108,6109],{"class":5511},"torch.cuda.is_available()",[5501,6111,5643],{"class":5614},[5501,6113,5655],{"class":5618},[5501,6115,5622],{"class":5511},[5501,6117,6118],{"class":5503,"line":5537},[5501,6119,5527],{"emptyLinePlaceholder":5526},[5501,6121,6122,6124],{"class":5503,"line":5547},[5501,6123,5705],{"class":5507},[5501,6125,5708],{"class":5511},[5501,6127,6128,6130,6132,6134,6137,6139,6142,6144,6146],{"class":5503,"line":5552},[5501,6129,5799],{"class":5607},[5501,6131,5611],{"class":5511},[5501,6133,5615],{"class":5614},[5501,6135,6136],{"class":5618},"\"Кількість GPU: ",[5501,6138,5637],{"class":5614},[5501,6140,6141],{"class":5511},"torch.cuda.device_count()",[5501,6143,5643],{"class":5614},[5501,6145,5655],{"class":5618},[5501,6147,5622],{"class":5511},[5501,6149,6150,6152,6154,6156,6159,6161,6164,6166,6168],{"class":5503,"line":5558},[5501,6151,5799],{"class":5607},[5501,6153,5611],{"class":5511},[5501,6155,5615],{"class":5614},[5501,6157,6158],{"class":5618},"\"Поточна GPU: ",[5501,6160,5637],{"class":5614},[5501,6162,6163],{"class":5511},"torch.cuda.current_device()",[5501,6165,5643],{"class":5614},[5501,6167,5655],{"class":5618},[5501,6169,5622],{"class":5511},[5501,6171,6172,6174,6176,6178,6181,6183,6185,6187,6189,6191,6193],{"class":5503,"line":5564},[5501,6173,5799],{"class":5607},[5501,6175,5611],{"class":5511},[5501,6177,5615],{"class":5614},[5501,6179,6180],{"class":5618},"\"Назва GPU: ",[5501,6182,5637],{"class":5614},[5501,6184,5825],{"class":5511},[5501,6186,5828],{"class":5543},[5501,6188,5227],{"class":5511},[5501,6190,5643],{"class":5614},[5501,6192,5655],{"class":5618},[5501,6194,5622],{"class":5511},[5501,6196,6197],{"class":5503,"line":5570},[5501,6198,5732],{"class":5511},[5501,6200,6201],{"class":5503,"line":5575},[5501,6202,6203],{"class":5533},"    # Інформація про пам'ять\n",[5501,6205,6206,6209,6211,6214,6217,6220,6223],{"class":5503,"line":5581},[5501,6207,6208],{"class":5511},"    total_memory = torch.cuda.get_device_properties(",[5501,6210,5828],{"class":5543},[5501,6212,6213],{"class":5511},").total_memory \u002F (",[5501,6215,6216],{"class":5543},"1024",[5501,6218,6219],{"class":5511},"**",[5501,6221,6222],{"class":5543},"3",[5501,6224,5622],{"class":5511},[5501,6226,6227,6229,6231,6233,6236,6238,6241,6244,6247],{"class":5503,"line":5587},[5501,6228,5799],{"class":5607},[5501,6230,5611],{"class":5511},[5501,6232,5615],{"class":5614},[5501,6234,6235],{"class":5618},"\"Загальна пам'ять: ",[5501,6237,5637],{"class":5614},[5501,6239,6240],{"class":5511},"total_memory",[5501,6242,6243],{"class":5614},":.2f}",[5501,6245,6246],{"class":5618}," GB\"",[5501,6248,5622],{"class":5511},[5907,6250,6251],{"v-slot:output":5497},[5910,6252,6253,6266],{},[5913,6254,6255],{},[5916,6256,6257,6260,6263],{},[5919,6258,6259],{"align":5921},"Параметр відеокарти",[5919,6261,6262],{"align":5921},"Значення",[5919,6264,6265],{"align":5925},"Статус",[5934,6267,6268,6283,6297,6315,6330],{},[5916,6269,6270,6275,6280],{},[5939,6271,6272],{"align":5921},[5220,6273,6274],{},"CUDA доступна",[5939,6276,6277],{"align":5921},[5289,6278,6279],{},"True",[5939,6281,6282],{"align":5925},"✅ Активовано",[5916,6284,6285,6290,6294],{},[5939,6286,6287],{"align":5921},[5220,6288,6289],{},"Кількість GPU",[5939,6291,6292],{"align":5921},[5289,6293,5490],{},[5939,6295,6296],{"align":5925},"Одиночний прискорювач",[5916,6298,6299,6304,6312],{},[5939,6300,6301],{"align":5921},[5220,6302,6303],{},"Поточний індекс",[5939,6305,6306,6308,6309,5227],{"align":5921},[5289,6307,5828],{}," (",[5289,6310,6311],{},"cuda:0",[5939,6313,6314],{"align":5925},"За замовчуванням",[5916,6316,6317,6322,6327],{},[5939,6318,6319],{"align":5921},[5220,6320,6321],{},"Модель GPU",[5939,6323,6324],{"align":5921},[5289,6325,6326],{},"NVIDIA GeForce RTX 3080",[5939,6328,6329],{"align":5925},"High-End",[5916,6331,6332,6337,6342],{},[5939,6333,6334],{"align":5921},[5220,6335,6336],{},"Загальна пам'ять VRAM",[5939,6338,6339],{"align":5921},[5289,6340,6341],{},"10.00 GB",[5939,6343,6344],{"align":5925},"Готово для батчів",[5488,6346,6348,6630],{"execution-count":6347},"2",[5492,6349,6351],{"className":5494,"code":6350,"language":5496,"meta":5497,"style":5497},"# Створення тензора на CPU (за замовчуванням)\nx_cpu = torch.tensor([1.0, 2.0, 3.0])\nprint(f\"Тензор на CPU:\")\nprint(f\"  Значення: {x_cpu}\")\nprint(f\"  device: {x_cpu.device}\")\nprint(f\"  dtype: {x_cpu.dtype}\\n\")\n\n# Переміщення на GPU\nif torch.cuda.is_available():\n    # Спосіб 1: метод .cuda()\n    x_gpu_1 = x_cpu.cuda()\n    print(f\"Після .cuda():\")\n    print(f\"  device: {x_gpu_1.device}\\n\")\n    \n    # Спосіб 2: метод .to() (рекомендовано)\n    device = torch.device('cuda')\n    x_gpu_2 = x_cpu.to(device)\n    print(f\"Після .to('cuda'):\")\n    print(f\"  device: {x_gpu_2.device}\\n\")\n    \n    # Повернення на CPU\n    x_back_cpu = x_gpu_2.cpu()\n    print(f\"Після .cpu():\")\n    print(f\"  device: {x_back_cpu.device}\")\n",[5289,6352,6353,6358,6380,6393,6415,6437,6461,6465,6470,6476,6481,6486,6499,6522,6526,6531,6541,6546,6559,6582,6586,6591,6596,6609],{"__ignoreMap":5497},[5501,6354,6355],{"class":5503,"line":5504},[5501,6356,6357],{"class":5533},"# Створення тензора на CPU (за замовчуванням)\n",[5501,6359,6360,6363,6366,6369,6372,6374,6377],{"class":5503,"line":5515},[5501,6361,6362],{"class":5511},"x_cpu = torch.tensor([",[5501,6364,6365],{"class":5543},"1.0",[5501,6367,6368],{"class":5511},", ",[5501,6370,6371],{"class":5543},"2.0",[5501,6373,6368],{"class":5511},[5501,6375,6376],{"class":5543},"3.0",[5501,6378,6379],{"class":5511},"])\n",[5501,6381,6382,6384,6386,6388,6391],{"class":5503,"line":5523},[5501,6383,5608],{"class":5607},[5501,6385,5611],{"class":5511},[5501,6387,5615],{"class":5614},[5501,6389,6390],{"class":5618},"\"Тензор на CPU:\"",[5501,6392,5622],{"class":5511},[5501,6394,6395,6397,6399,6401,6404,6406,6409,6411,6413],{"class":5503,"line":5530},[5501,6396,5608],{"class":5607},[5501,6398,5611],{"class":5511},[5501,6400,5615],{"class":5614},[5501,6402,6403],{"class":5618},"\"  Значення: ",[5501,6405,5637],{"class":5614},[5501,6407,6408],{"class":5511},"x_cpu",[5501,6410,5643],{"class":5614},[5501,6412,5655],{"class":5618},[5501,6414,5622],{"class":5511},[5501,6416,6417,6419,6421,6423,6426,6428,6431,6433,6435],{"class":5503,"line":5537},[5501,6418,5608],{"class":5607},[5501,6420,5611],{"class":5511},[5501,6422,5615],{"class":5614},[5501,6424,6425],{"class":5618},"\"  device: ",[5501,6427,5637],{"class":5614},[5501,6429,6430],{"class":5511},"x_cpu.device",[5501,6432,5643],{"class":5614},[5501,6434,5655],{"class":5618},[5501,6436,5622],{"class":5511},[5501,6438,6439,6441,6443,6445,6448,6450,6453,6455,6457,6459],{"class":5503,"line":5547},[5501,6440,5608],{"class":5607},[5501,6442,5611],{"class":5511},[5501,6444,5615],{"class":5614},[5501,6446,6447],{"class":5618},"\"  dtype: ",[5501,6449,5637],{"class":5614},[5501,6451,6452],{"class":5511},"x_cpu.dtype",[5501,6454,5643],{"class":5614},[5501,6456,5684],{"class":5683},[5501,6458,5655],{"class":5618},[5501,6460,5622],{"class":5511},[5501,6462,6463],{"class":5503,"line":5552},[5501,6464,5527],{"emptyLinePlaceholder":5526},[5501,6466,6467],{"class":5503,"line":5558},[5501,6468,6469],{"class":5533},"# Переміщення на GPU\n",[5501,6471,6472,6474],{"class":5503,"line":5564},[5501,6473,5705],{"class":5507},[5501,6475,5708],{"class":5511},[5501,6477,6478],{"class":5503,"line":5570},[5501,6479,6480],{"class":5533},"    # Спосіб 1: метод .cuda()\n",[5501,6482,6483],{"class":5503,"line":5575},[5501,6484,6485],{"class":5511},"    x_gpu_1 = x_cpu.cuda()\n",[5501,6487,6488,6490,6492,6494,6497],{"class":5503,"line":5581},[5501,6489,5799],{"class":5607},[5501,6491,5611],{"class":5511},[5501,6493,5615],{"class":5614},[5501,6495,6496],{"class":5618},"\"Після .cuda():\"",[5501,6498,5622],{"class":5511},[5501,6500,6501,6503,6505,6507,6509,6511,6514,6516,6518,6520],{"class":5503,"line":5587},[5501,6502,5799],{"class":5607},[5501,6504,5611],{"class":5511},[5501,6506,5615],{"class":5614},[5501,6508,6425],{"class":5618},[5501,6510,5637],{"class":5614},[5501,6512,6513],{"class":5511},"x_gpu_1.device",[5501,6515,5643],{"class":5614},[5501,6517,5684],{"class":5683},[5501,6519,5655],{"class":5618},[5501,6521,5622],{"class":5511},[5501,6523,6524],{"class":5503,"line":5593},[5501,6525,5732],{"class":5511},[5501,6527,6528],{"class":5503,"line":5599},[5501,6529,6530],{"class":5533},"    # Спосіб 2: метод .to() (рекомендовано)\n",[5501,6532,6533,6536,6539],{"class":5503,"line":5604},[5501,6534,6535],{"class":5511},"    device = torch.device(",[5501,6537,6538],{"class":5618},"'cuda'",[5501,6540,5622],{"class":5511},[5501,6542,6543],{"class":5503,"line":5625},[5501,6544,6545],{"class":5511},"    x_gpu_2 = x_cpu.to(device)\n",[5501,6547,6548,6550,6552,6554,6557],{"class":5503,"line":5660},[5501,6549,5799],{"class":5607},[5501,6551,5611],{"class":5511},[5501,6553,5615],{"class":5614},[5501,6555,6556],{"class":5618},"\"Після .to('cuda'):\"",[5501,6558,5622],{"class":5511},[5501,6560,6561,6563,6565,6567,6569,6571,6574,6576,6578,6580],{"class":5503,"line":5691},[5501,6562,5799],{"class":5607},[5501,6564,5611],{"class":5511},[5501,6566,5615],{"class":5614},[5501,6568,6425],{"class":5618},[5501,6570,5637],{"class":5614},[5501,6572,6573],{"class":5511},"x_gpu_2.device",[5501,6575,5643],{"class":5614},[5501,6577,5684],{"class":5683},[5501,6579,5655],{"class":5618},[5501,6581,5622],{"class":5511},[5501,6583,6584],{"class":5503,"line":5696},[5501,6585,5732],{"class":5511},[5501,6587,6588],{"class":5503,"line":5702},[5501,6589,6590],{"class":5533},"    # Повернення на CPU\n",[5501,6592,6593],{"class":5503,"line":5711},[5501,6594,6595],{"class":5511},"    x_back_cpu = x_gpu_2.cpu()\n",[5501,6597,6598,6600,6602,6604,6607],{"class":5503,"line":5717},[5501,6599,5799],{"class":5607},[5501,6601,5611],{"class":5511},[5501,6603,5615],{"class":5614},[5501,6605,6606],{"class":5618},"\"Після .cpu():\"",[5501,6608,5622],{"class":5511},[5501,6610,6611,6613,6615,6617,6619,6621,6624,6626,6628],{"class":5503,"line":5723},[5501,6612,5799],{"class":5607},[5501,6614,5611],{"class":5511},[5501,6616,5615],{"class":5614},[5501,6618,6425],{"class":5618},[5501,6620,5637],{"class":5614},[5501,6622,6623],{"class":5511},"x_back_cpu.device",[5501,6625,5643],{"class":5614},[5501,6627,5655],{"class":5618},[5501,6629,5622],{"class":5511},[5907,6631,6632],{"v-slot:output":5497},[5910,6633,6634,6652],{},[5913,6635,6636],{},[5916,6637,6638,6641,6644,6649],{},[5919,6639,6640],{"align":5921},"Об'єкт",[5919,6642,6643],{"align":5921},"Значення тензора",[5919,6645,6646,6647,5227],{"align":5925},"Пристрій (",[5289,6648,6067],{},[5919,6650,6651],{"align":5921},"Тип оперативної пам'яті",[5934,6653,6654,6674],{},[5916,6655,6656,6661,6666,6671],{},[5939,6657,6658],{"align":5921},[5289,6659,6660],{},"t_cpu",[5939,6662,6663],{"align":5921},[5289,6664,6665],{},"tensor([1., 2., 3.])",[5939,6667,6668],{"align":5925},[5289,6669,6670],{},"cpu",[5939,6672,6673],{"align":5921},"Системна пам'ять RAM",[5916,6675,6676,6681,6686,6690],{},[5939,6677,6678],{"align":5921},[5289,6679,6680],{},"t_gpu",[5939,6682,6683],{"align":5921},[5289,6684,6685],{},"tensor([1., 2., 3.], device='cuda:0')",[5939,6687,6688],{"align":5925},[5289,6689,6311],{},[5939,6691,6692],{"align":5921},"Відеопам'ять GPU VRAM",[6694,6695,6696,6708,6728,6734],"note",{},[5268,6697,6698],{},[5220,6699,6700,6701,5471,6704,6707],{},"Різниця між ",[5289,6702,6703],{},".cuda()",[5289,6705,6706],{},".to(device)",":",[5194,6709,6710,6717],{},[5197,6711,6712,6716],{},[5220,6713,6714],{},[5289,6715,6703],{}," — завжди переміщує на GPU. Якщо GPU недоступна — помилка.",[5197,6718,6719,6723,6724,6727],{},[5220,6720,6721],{},[5289,6722,6706],{}," — універсальний метод. Якщо ",[5289,6725,6726],{},"device='cpu'",", залишає на CPU. Безпечніший для коду, що має працювати і на CPU, і на GPU.",[5268,6729,6730,6733],{},[5220,6731,6732],{},"Рекомендація:"," Використовуйте патерн:",[5492,6735,6737],{"className":5494,"code":6736,"language":5496,"meta":5497,"style":5497},"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\ntensor = tensor.to(device)\nmodel = model.to(device)\n",[5289,6738,6739,6759,6764],{"__ignoreMap":5497},[5501,6740,6741,6744,6746,6749,6752,6754,6757],{"class":5503,"line":5504},[5501,6742,6743],{"class":5511},"device = torch.device(",[5501,6745,6538],{"class":5618},[5501,6747,6748],{"class":5507}," if",[5501,6750,6751],{"class":5511}," torch.cuda.is_available() ",[5501,6753,5890],{"class":5507},[5501,6755,6756],{"class":5618}," 'cpu'",[5501,6758,5622],{"class":5511},[5501,6760,6761],{"class":5503,"line":5515},[5501,6762,6763],{"class":5511},"tensor = tensor.to(device)\n",[5501,6765,6766],{"class":5503,"line":5523},[5501,6767,6768],{"class":5511},"model = model.to(device)\n",[6770,6771,6773],"h4",{"id":6772},"переміщення-моделі-на-gpu","Переміщення моделі на GPU",[5484,6775,6777],{"title":6776},"model_to_gpu.ipynb",[5488,6778,6779,7153],{"execution-count":5490},[5492,6780,6782],{"className":5494,"code":6781,"language":5496,"meta":5497,"style":5497},"import torch\nimport torch.nn as nn\n\n# Визначаємо модель\nclass SimpleModel(nn.Module):\n    def __init__(self):\n        super().__init__()\n        self.fc1 = nn.Linear(10, 64)\n        self.fc2 = nn.Linear(64, 32)\n        self.fc3 = nn.Linear(32, 1)\n    \n    def forward(self, x):\n        x = torch.relu(self.fc1(x))\n        x = torch.relu(self.fc2(x))\n        x = self.fc3(x)\n        return x\n\n# Створюємо модель (за замовчуванням на CPU)\nmodel = SimpleModel()\nprint(\"Модель створено на CPU\")\n\n# Перевіряємо, де знаходяться параметри\nfirst_param = next(model.parameters())\nprint(f\"Параметри моделі на: {first_param.device}\\n\")\n\n# Переміщуємо на GPU\nif torch.cuda.is_available():\n    device = torch.device('cuda')\n    model = model.to(device)\n    \n    first_param = next(model.parameters())\n    print(f\"Після .to('cuda'):\")\n    print(f\"  Параметри моделі на: {first_param.device}\")\n    print(f\"  Кількість параметрів: {sum(p.numel() for p in model.parameters())}\")\n",[5289,6783,6784,6790,6803,6807,6812,6835,6851,6865,6883,6899,6914,6918,6936,6946,6955,6965,6973,6977,6982,6987,6998,7002,7007,7018,7042,7046,7051,7057,7065,7070,7074,7083,7095,7116],{"__ignoreMap":5497},[5501,6785,6786,6788],{"class":5503,"line":5504},[5501,6787,5508],{"class":5507},[5501,6789,5512],{"class":5511},[5501,6791,6792,6794,6797,6800],{"class":5503,"line":5515},[5501,6793,5508],{"class":5507},[5501,6795,6796],{"class":5511}," torch.nn ",[5501,6798,6799],{"class":5507},"as",[5501,6801,6802],{"class":5511}," nn\n",[5501,6804,6805],{"class":5503,"line":5523},[5501,6806,5527],{"emptyLinePlaceholder":5526},[5501,6808,6809],{"class":5503,"line":5530},[5501,6810,6811],{"class":5533},"# Визначаємо модель\n",[5501,6813,6814,6817,6821,6823,6826,6829,6832],{"class":5503,"line":5537},[5501,6815,6816],{"class":5614},"class",[5501,6818,6820],{"class":6819},"sN1BT"," SimpleModel",[5501,6822,5611],{"class":5511},[5501,6824,6825],{"class":6819},"nn",[5501,6827,6828],{"class":5511},".",[5501,6830,6831],{"class":6819},"Module",[5501,6833,6834],{"class":5511},"):\n",[5501,6836,6837,6840,6843,6845,6849],{"class":5503,"line":5547},[5501,6838,6839],{"class":5614},"    def",[5501,6841,6842],{"class":5607}," __init__",[5501,6844,5611],{"class":5511},[5501,6846,6848],{"class":6847},"siwwj","self",[5501,6850,6834],{"class":5511},[5501,6852,6853,6856,6859,6862],{"class":5503,"line":5552},[5501,6854,6855],{"class":6819},"        super",[5501,6857,6858],{"class":5511},"().",[5501,6860,6861],{"class":5607},"__init__",[5501,6863,6864],{"class":5511},"()\n",[5501,6866,6867,6870,6873,6876,6878,6881],{"class":5503,"line":5558},[5501,6868,6869],{"class":5614},"        self",[5501,6871,6872],{"class":5511},".fc1 = nn.Linear(",[5501,6874,6875],{"class":5543},"10",[5501,6877,6368],{"class":5511},[5501,6879,6880],{"class":5543},"64",[5501,6882,5622],{"class":5511},[5501,6884,6885,6887,6890,6892,6894,6897],{"class":5503,"line":5564},[5501,6886,6869],{"class":5614},[5501,6888,6889],{"class":5511},".fc2 = nn.Linear(",[5501,6891,6880],{"class":5543},[5501,6893,6368],{"class":5511},[5501,6895,6896],{"class":5543},"32",[5501,6898,5622],{"class":5511},[5501,6900,6901,6903,6906,6908,6910,6912],{"class":5503,"line":5570},[5501,6902,6869],{"class":5614},[5501,6904,6905],{"class":5511},".fc3 = nn.Linear(",[5501,6907,6896],{"class":5543},[5501,6909,6368],{"class":5511},[5501,6911,5490],{"class":5543},[5501,6913,5622],{"class":5511},[5501,6915,6916],{"class":5503,"line":5575},[5501,6917,5732],{"class":5511},[5501,6919,6920,6922,6925,6927,6929,6931,6934],{"class":5503,"line":5581},[5501,6921,6839],{"class":5614},[5501,6923,6924],{"class":5607}," forward",[5501,6926,5611],{"class":5511},[5501,6928,6848],{"class":6847},[5501,6930,6368],{"class":5511},[5501,6932,6933],{"class":6847},"x",[5501,6935,6834],{"class":5511},[5501,6937,6938,6941,6943],{"class":5503,"line":5587},[5501,6939,6940],{"class":5511},"        x = torch.relu(",[5501,6942,6848],{"class":5614},[5501,6944,6945],{"class":5511},".fc1(x))\n",[5501,6947,6948,6950,6952],{"class":5503,"line":5593},[5501,6949,6940],{"class":5511},[5501,6951,6848],{"class":5614},[5501,6953,6954],{"class":5511},".fc2(x))\n",[5501,6956,6957,6960,6962],{"class":5503,"line":5599},[5501,6958,6959],{"class":5511},"        x = ",[5501,6961,6848],{"class":5614},[5501,6963,6964],{"class":5511},".fc3(x)\n",[5501,6966,6967,6970],{"class":5503,"line":5604},[5501,6968,6969],{"class":5507},"        return",[5501,6971,6972],{"class":5511}," x\n",[5501,6974,6975],{"class":5503,"line":5625},[5501,6976,5527],{"emptyLinePlaceholder":5526},[5501,6978,6979],{"class":5503,"line":5660},[5501,6980,6981],{"class":5533},"# Створюємо модель (за замовчуванням на CPU)\n",[5501,6983,6984],{"class":5503,"line":5691},[5501,6985,6986],{"class":5511},"model = SimpleModel()\n",[5501,6988,6989,6991,6993,6996],{"class":5503,"line":5696},[5501,6990,5608],{"class":5607},[5501,6992,5611],{"class":5511},[5501,6994,6995],{"class":5618},"\"Модель створено на CPU\"",[5501,6997,5622],{"class":5511},[5501,6999,7000],{"class":5503,"line":5702},[5501,7001,5527],{"emptyLinePlaceholder":5526},[5501,7003,7004],{"class":5503,"line":5711},[5501,7005,7006],{"class":5533},"# Перевіряємо, де знаходяться параметри\n",[5501,7008,7009,7012,7015],{"class":5503,"line":5717},[5501,7010,7011],{"class":5511},"first_param = ",[5501,7013,7014],{"class":5607},"next",[5501,7016,7017],{"class":5511},"(model.parameters())\n",[5501,7019,7020,7022,7024,7026,7029,7031,7034,7036,7038,7040],{"class":5503,"line":5723},[5501,7021,5608],{"class":5607},[5501,7023,5611],{"class":5511},[5501,7025,5615],{"class":5614},[5501,7027,7028],{"class":5618},"\"Параметри моделі на: ",[5501,7030,5637],{"class":5614},[5501,7032,7033],{"class":5511},"first_param.device",[5501,7035,5643],{"class":5614},[5501,7037,5684],{"class":5683},[5501,7039,5655],{"class":5618},[5501,7041,5622],{"class":5511},[5501,7043,7044],{"class":5503,"line":5729},[5501,7045,5527],{"emptyLinePlaceholder":5526},[5501,7047,7048],{"class":5503,"line":5735},[5501,7049,7050],{"class":5533},"# Переміщуємо на GPU\n",[5501,7052,7053,7055],{"class":5503,"line":5741},[5501,7054,5705],{"class":5507},[5501,7056,5708],{"class":5511},[5501,7058,7059,7061,7063],{"class":5503,"line":5747},[5501,7060,6535],{"class":5511},[5501,7062,6538],{"class":5618},[5501,7064,5622],{"class":5511},[5501,7066,7067],{"class":5503,"line":5753},[5501,7068,7069],{"class":5511},"    model = model.to(device)\n",[5501,7071,7072],{"class":5503,"line":5758},[5501,7073,5732],{"class":5511},[5501,7075,7076,7079,7081],{"class":5503,"line":5764},[5501,7077,7078],{"class":5511},"    first_param = ",[5501,7080,7014],{"class":5607},[5501,7082,7017],{"class":5511},[5501,7084,7085,7087,7089,7091,7093],{"class":5503,"line":5770},[5501,7086,5799],{"class":5607},[5501,7088,5611],{"class":5511},[5501,7090,5615],{"class":5614},[5501,7092,6556],{"class":5618},[5501,7094,5622],{"class":5511},[5501,7096,7097,7099,7101,7103,7106,7108,7110,7112,7114],{"class":5503,"line":5776},[5501,7098,5799],{"class":5607},[5501,7100,5611],{"class":5511},[5501,7102,5615],{"class":5614},[5501,7104,7105],{"class":5618},"\"  Параметри моделі на: ",[5501,7107,5637],{"class":5614},[5501,7109,7033],{"class":5511},[5501,7111,5643],{"class":5614},[5501,7113,5655],{"class":5618},[5501,7115,5622],{"class":5511},[5501,7117,7118,7120,7122,7124,7127,7129,7132,7135,7138,7141,7144,7147,7149,7151],{"class":5503,"line":5785},[5501,7119,5799],{"class":5607},[5501,7121,5611],{"class":5511},[5501,7123,5615],{"class":5614},[5501,7125,7126],{"class":5618},"\"  Кількість параметрів: ",[5501,7128,5637],{"class":5614},[5501,7130,7131],{"class":5607},"sum",[5501,7133,7134],{"class":5511},"(p.numel() ",[5501,7136,7137],{"class":5507},"for",[5501,7139,7140],{"class":5511}," p ",[5501,7142,7143],{"class":5507},"in",[5501,7145,7146],{"class":5511}," model.parameters())",[5501,7148,5643],{"class":5614},[5501,7150,5655],{"class":5618},[5501,7152,5622],{"class":5511},[5907,7154,7155],{"v-slot:output":5497},[5910,7156,7157,7173],{},[5913,7158,7159],{},[5916,7160,7161,7164,7167,7170],{},[5919,7162,7163],{"align":5921},"Стан моделі",[5919,7165,7166],{"align":5925},"Пристрій параметрів",[5919,7168,7169],{"align":5921},"Пам'ять",[5919,7171,7172],{"align":5921},"Вплив на обчислення",[5934,7174,7175,7195],{},[5916,7176,7177,7185,7189,7192],{},[5939,7178,7179],{"align":5921},[5220,7180,7181,7182,5227],{},"Після створення (",[5289,7183,7184],{},"model",[5939,7186,7187],{"align":5925},[5289,7188,6670],{},[5939,7190,7191],{"align":5921},"RAM",[5939,7193,7194],{"align":5921},"Обчислення на ядрах CPU",[5916,7196,7197,7205,7209,7212],{},[5939,7198,7199],{"align":5921},[5220,7200,7201,7202],{},"Після ",[5289,7203,7204],{},"model.to(device)",[5939,7206,7207],{"align":5925},[5289,7208,6311],{},[5939,7210,7211],{"align":5921},"GPU VRAM",[5939,7213,7214],{"align":5921},"⚡ Паралельне виконання на ядрах CUDA",[7216,7217,7218,7223,7296],"warning",{},[5268,7219,7220],{},[5220,7221,7222],{},"Критична помилка: дані та модель на різних пристроях",[5492,7224,7226],{"className":5494,"code":7225,"language":5496,"meta":5497,"style":5497},"model = model.to('cuda')\nX = torch.randn(5, 10)  # на CPU\n\n# ❌ Помилка!\noutput = model(X)\n# RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!\n\n# ✅ Правильно:\nX = X.to('cuda')\noutput = model(X)\n",[5289,7227,7228,7237,7255,7259,7264,7269,7274,7278,7283,7292],{"__ignoreMap":5497},[5501,7229,7230,7233,7235],{"class":5503,"line":5504},[5501,7231,7232],{"class":5511},"model = model.to(",[5501,7234,6538],{"class":5618},[5501,7236,5622],{"class":5511},[5501,7238,7239,7242,7245,7247,7249,7252],{"class":5503,"line":5515},[5501,7240,7241],{"class":5511},"X = torch.randn(",[5501,7243,7244],{"class":5543},"5",[5501,7246,6368],{"class":5511},[5501,7248,6875],{"class":5543},[5501,7250,7251],{"class":5511},")  ",[5501,7253,7254],{"class":5533},"# на CPU\n",[5501,7256,7257],{"class":5503,"line":5523},[5501,7258,5527],{"emptyLinePlaceholder":5526},[5501,7260,7261],{"class":5503,"line":5530},[5501,7262,7263],{"class":5533},"# ❌ Помилка!\n",[5501,7265,7266],{"class":5503,"line":5537},[5501,7267,7268],{"class":5511},"output = model(X)\n",[5501,7270,7271],{"class":5503,"line":5547},[5501,7272,7273],{"class":5533},"# RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!\n",[5501,7275,7276],{"class":5503,"line":5552},[5501,7277,5527],{"emptyLinePlaceholder":5526},[5501,7279,7280],{"class":5503,"line":5558},[5501,7281,7282],{"class":5533},"# ✅ Правильно:\n",[5501,7284,7285,7288,7290],{"class":5503,"line":5564},[5501,7286,7287],{"class":5511},"X = X.to(",[5501,7289,6538],{"class":5618},[5501,7291,5622],{"class":5511},[5501,7293,7294],{"class":5503,"line":5570},[5501,7295,7268],{"class":5511},[5268,7297,7298,7301,7302,6828],{},[5220,7299,7300],{},"Правило:"," Модель та дані завжди мають бути на ",[5220,7303,7304],{},"одному пристрої",[5340,7306,7308],{"id":7307},"повний-training-loop-з-gpu","Повний Training Loop з GPU",[5268,7310,7311],{},"Розглянемо повний приклад тренування моделі на GPU:",[5484,7313,7315],{"title":7314},"gpu_training_loop.ipynb",[5488,7316,7317,7840],{"execution-count":5490},[5492,7318,7320],{"className":5494,"code":7319,"language":5496,"meta":5497,"style":5497},"import torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import TensorDataset, DataLoader\n\n# Визначаємо device\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\nprint(f\"Використовуємо пристрій: {device}\\n\")\n\n# Генеруємо синтетичні дані\ntorch.manual_seed(42)\nX_train = torch.randn(1000, 20)\ny_train = (X_train.sum(dim=1, keepdim=True) > 0).float()\n\n# DataLoader\ntrain_dataset = TensorDataset(X_train, y_train)\ntrain_loader = DataLoader(train_dataset, batch_size=64, shuffle=True)\n\n# Модель\nmodel = nn.Sequential(\n    nn.Linear(20, 64),\n    nn.ReLU(),\n    nn.Dropout(0.3),\n    nn.Linear(64, 32),\n    nn.ReLU(),\n    nn.Linear(32, 1)\n).to(device)  # ✅ Модель на GPU\n\n# Loss та optimizer\ncriterion = nn.BCEWithLogitsLoss()\noptimizer = optim.Adam(model.parameters(), lr=0.001)\n\n# Тренування\nnum_epochs = 10\n\nfor epoch in range(num_epochs):\n    model.train()\n    epoch_loss = 0.0\n    \n    for batch_X, batch_y in train_loader:\n        # ✅ Переміщуємо дані на GPU\n        batch_X = batch_X.to(device)\n        batch_y = batch_y.to(device)\n        \n        # Training step\n        optimizer.zero_grad()\n        outputs = model(batch_X)\n        loss = criterion(outputs, batch_y)\n        loss.backward()\n        optimizer.step()\n        \n        epoch_loss += loss.item()\n    \n    avg_loss = epoch_loss \u002F len(train_loader)\n    print(f\"Епоха {epoch+1}\u002F{num_epochs}: Loss = {avg_loss:.4f}\")\n\nprint(\"\\n✓ Тренування завершено\")\n",[5289,7321,7322,7328,7338,7350,7363,7367,7372,7388,7411,7415,7420,7430,7445,7475,7479,7484,7489,7512,7516,7521,7526,7540,7545,7555,7567,7571,7583,7591,7595,7600,7605,7620,7624,7629,7637,7641,7656,7661,7669,7673,7686,7691,7697,7703,7709,7715,7721,7727,7733,7739,7745,7750,7756,7761,7773,7819,7824],{"__ignoreMap":5497},[5501,7323,7324,7326],{"class":5503,"line":5504},[5501,7325,5508],{"class":5507},[5501,7327,5512],{"class":5511},[5501,7329,7330,7332,7334,7336],{"class":5503,"line":5515},[5501,7331,5508],{"class":5507},[5501,7333,6796],{"class":5511},[5501,7335,6799],{"class":5507},[5501,7337,6802],{"class":5511},[5501,7339,7340,7342,7345,7347],{"class":5503,"line":5523},[5501,7341,5508],{"class":5507},[5501,7343,7344],{"class":5511}," torch.optim ",[5501,7346,6799],{"class":5507},[5501,7348,7349],{"class":5511}," optim\n",[5501,7351,7352,7355,7358,7360],{"class":5503,"line":5530},[5501,7353,7354],{"class":5507},"from",[5501,7356,7357],{"class":5511}," torch.utils.data ",[5501,7359,5508],{"class":5507},[5501,7361,7362],{"class":5511}," TensorDataset, DataLoader\n",[5501,7364,7365],{"class":5503,"line":5537},[5501,7366,5527],{"emptyLinePlaceholder":5526},[5501,7368,7369],{"class":5503,"line":5547},[5501,7370,7371],{"class":5533},"# Визначаємо device\n",[5501,7373,7374,7376,7378,7380,7382,7384,7386],{"class":5503,"line":5552},[5501,7375,6743],{"class":5511},[5501,7377,6538],{"class":5618},[5501,7379,6748],{"class":5507},[5501,7381,6751],{"class":5511},[5501,7383,5890],{"class":5507},[5501,7385,6756],{"class":5618},[5501,7387,5622],{"class":5511},[5501,7389,7390,7392,7394,7396,7399,7401,7403,7405,7407,7409],{"class":5503,"line":5558},[5501,7391,5608],{"class":5607},[5501,7393,5611],{"class":5511},[5501,7395,5615],{"class":5614},[5501,7397,7398],{"class":5618},"\"Використовуємо пристрій: ",[5501,7400,5637],{"class":5614},[5501,7402,6067],{"class":5511},[5501,7404,5643],{"class":5614},[5501,7406,5684],{"class":5683},[5501,7408,5655],{"class":5618},[5501,7410,5622],{"class":5511},[5501,7412,7413],{"class":5503,"line":5564},[5501,7414,5527],{"emptyLinePlaceholder":5526},[5501,7416,7417],{"class":5503,"line":5570},[5501,7418,7419],{"class":5533},"# Генеруємо синтетичні дані\n",[5501,7421,7422,7425,7428],{"class":5503,"line":5575},[5501,7423,7424],{"class":5511},"torch.manual_seed(",[5501,7426,7427],{"class":5543},"42",[5501,7429,5622],{"class":5511},[5501,7431,7432,7435,7438,7440,7443],{"class":5503,"line":5581},[5501,7433,7434],{"class":5511},"X_train = torch.randn(",[5501,7436,7437],{"class":5543},"1000",[5501,7439,6368],{"class":5511},[5501,7441,7442],{"class":5543},"20",[5501,7444,5622],{"class":5511},[5501,7446,7447,7450,7453,7456,7458,7460,7463,7465,7467,7470,7472],{"class":5503,"line":5587},[5501,7448,7449],{"class":5511},"y_train = (X_train.sum(",[5501,7451,7452],{"class":6847},"dim",[5501,7454,7455],{"class":5511},"=",[5501,7457,5490],{"class":5543},[5501,7459,6368],{"class":5511},[5501,7461,7462],{"class":6847},"keepdim",[5501,7464,7455],{"class":5511},[5501,7466,6279],{"class":5614},[5501,7468,7469],{"class":5511},") > ",[5501,7471,5828],{"class":5543},[5501,7473,7474],{"class":5511},").float()\n",[5501,7476,7477],{"class":5503,"line":5593},[5501,7478,5527],{"emptyLinePlaceholder":5526},[5501,7480,7481],{"class":5503,"line":5599},[5501,7482,7483],{"class":5533},"# DataLoader\n",[5501,7485,7486],{"class":5503,"line":5604},[5501,7487,7488],{"class":5511},"train_dataset = TensorDataset(X_train, y_train)\n",[5501,7490,7491,7494,7497,7499,7501,7503,7506,7508,7510],{"class":5503,"line":5625},[5501,7492,7493],{"class":5511},"train_loader = DataLoader(train_dataset, ",[5501,7495,7496],{"class":6847},"batch_size",[5501,7498,7455],{"class":5511},[5501,7500,6880],{"class":5543},[5501,7502,6368],{"class":5511},[5501,7504,7505],{"class":6847},"shuffle",[5501,7507,7455],{"class":5511},[5501,7509,6279],{"class":5614},[5501,7511,5622],{"class":5511},[5501,7513,7514],{"class":5503,"line":5660},[5501,7515,5527],{"emptyLinePlaceholder":5526},[5501,7517,7518],{"class":5503,"line":5691},[5501,7519,7520],{"class":5533},"# Модель\n",[5501,7522,7523],{"class":5503,"line":5696},[5501,7524,7525],{"class":5511},"model = nn.Sequential(\n",[5501,7527,7528,7531,7533,7535,7537],{"class":5503,"line":5702},[5501,7529,7530],{"class":5511},"    nn.Linear(",[5501,7532,7442],{"class":5543},[5501,7534,6368],{"class":5511},[5501,7536,6880],{"class":5543},[5501,7538,7539],{"class":5511},"),\n",[5501,7541,7542],{"class":5503,"line":5711},[5501,7543,7544],{"class":5511},"    nn.ReLU(),\n",[5501,7546,7547,7550,7553],{"class":5503,"line":5717},[5501,7548,7549],{"class":5511},"    nn.Dropout(",[5501,7551,7552],{"class":5543},"0.3",[5501,7554,7539],{"class":5511},[5501,7556,7557,7559,7561,7563,7565],{"class":5503,"line":5723},[5501,7558,7530],{"class":5511},[5501,7560,6880],{"class":5543},[5501,7562,6368],{"class":5511},[5501,7564,6896],{"class":5543},[5501,7566,7539],{"class":5511},[5501,7568,7569],{"class":5503,"line":5729},[5501,7570,7544],{"class":5511},[5501,7572,7573,7575,7577,7579,7581],{"class":5503,"line":5735},[5501,7574,7530],{"class":5511},[5501,7576,6896],{"class":5543},[5501,7578,6368],{"class":5511},[5501,7580,5490],{"class":5543},[5501,7582,5622],{"class":5511},[5501,7584,7585,7588],{"class":5503,"line":5741},[5501,7586,7587],{"class":5511},").to(device)  ",[5501,7589,7590],{"class":5533},"# ✅ Модель на GPU\n",[5501,7592,7593],{"class":5503,"line":5747},[5501,7594,5527],{"emptyLinePlaceholder":5526},[5501,7596,7597],{"class":5503,"line":5753},[5501,7598,7599],{"class":5533},"# Loss та optimizer\n",[5501,7601,7602],{"class":5503,"line":5758},[5501,7603,7604],{"class":5511},"criterion = nn.BCEWithLogitsLoss()\n",[5501,7606,7607,7610,7613,7615,7618],{"class":5503,"line":5764},[5501,7608,7609],{"class":5511},"optimizer = optim.Adam(model.parameters(), ",[5501,7611,7612],{"class":6847},"lr",[5501,7614,7455],{"class":5511},[5501,7616,7617],{"class":5543},"0.001",[5501,7619,5622],{"class":5511},[5501,7621,7622],{"class":5503,"line":5770},[5501,7623,5527],{"emptyLinePlaceholder":5526},[5501,7625,7626],{"class":5503,"line":5776},[5501,7627,7628],{"class":5533},"# Тренування\n",[5501,7630,7631,7634],{"class":5503,"line":5785},[5501,7632,7633],{"class":5511},"num_epochs = ",[5501,7635,7636],{"class":5543},"10\n",[5501,7638,7639],{"class":5503,"line":5791},[5501,7640,5527],{"emptyLinePlaceholder":5526},[5501,7642,7643,7645,7648,7650,7653],{"class":5503,"line":5796},[5501,7644,7137],{"class":5507},[5501,7646,7647],{"class":5511}," epoch ",[5501,7649,7143],{"class":5507},[5501,7651,7652],{"class":5607}," range",[5501,7654,7655],{"class":5511},"(num_epochs):\n",[5501,7657,7658],{"class":5503,"line":5811},[5501,7659,7660],{"class":5511},"    model.train()\n",[5501,7662,7663,7666],{"class":5503,"line":5839},[5501,7664,7665],{"class":5511},"    epoch_loss = ",[5501,7667,7668],{"class":5543},"0.0\n",[5501,7670,7671],{"class":5503,"line":5862},[5501,7672,5732],{"class":5511},[5501,7674,7675,7678,7681,7683],{"class":5503,"line":5887},[5501,7676,7677],{"class":5507},"    for",[5501,7679,7680],{"class":5511}," batch_X, batch_y ",[5501,7682,7143],{"class":5507},[5501,7684,7685],{"class":5511}," train_loader:\n",[5501,7687,7688],{"class":5503,"line":5896},[5501,7689,7690],{"class":5533},"        # ✅ Переміщуємо дані на GPU\n",[5501,7692,7694],{"class":5503,"line":7693},42,[5501,7695,7696],{"class":5511},"        batch_X = batch_X.to(device)\n",[5501,7698,7700],{"class":5503,"line":7699},43,[5501,7701,7702],{"class":5511},"        batch_y = batch_y.to(device)\n",[5501,7704,7706],{"class":5503,"line":7705},44,[5501,7707,7708],{"class":5511},"        \n",[5501,7710,7712],{"class":5503,"line":7711},45,[5501,7713,7714],{"class":5533},"        # Training step\n",[5501,7716,7718],{"class":5503,"line":7717},46,[5501,7719,7720],{"class":5511},"        optimizer.zero_grad()\n",[5501,7722,7724],{"class":5503,"line":7723},47,[5501,7725,7726],{"class":5511},"        outputs = model(batch_X)\n",[5501,7728,7730],{"class":5503,"line":7729},48,[5501,7731,7732],{"class":5511},"        loss = criterion(outputs, batch_y)\n",[5501,7734,7736],{"class":5503,"line":7735},49,[5501,7737,7738],{"class":5511},"        loss.backward()\n",[5501,7740,7742],{"class":5503,"line":7741},50,[5501,7743,7744],{"class":5511},"        optimizer.step()\n",[5501,7746,7748],{"class":5503,"line":7747},51,[5501,7749,7708],{"class":5511},[5501,7751,7753],{"class":5503,"line":7752},52,[5501,7754,7755],{"class":5511},"        epoch_loss += loss.item()\n",[5501,7757,7759],{"class":5503,"line":7758},53,[5501,7760,5732],{"class":5511},[5501,7762,7764,7767,7770],{"class":5503,"line":7763},54,[5501,7765,7766],{"class":5511},"    avg_loss = epoch_loss \u002F ",[5501,7768,7769],{"class":5607},"len",[5501,7771,7772],{"class":5511},"(train_loader)\n",[5501,7774,7776,7778,7780,7782,7785,7787,7790,7792,7794,7797,7799,7802,7804,7807,7809,7812,7815,7817],{"class":5503,"line":7775},55,[5501,7777,5799],{"class":5607},[5501,7779,5611],{"class":5511},[5501,7781,5615],{"class":5614},[5501,7783,7784],{"class":5618},"\"Епоха ",[5501,7786,5637],{"class":5614},[5501,7788,7789],{"class":5511},"epoch+",[5501,7791,5490],{"class":5543},[5501,7793,5643],{"class":5614},[5501,7795,7796],{"class":5618},"\u002F",[5501,7798,5637],{"class":5614},[5501,7800,7801],{"class":5511},"num_epochs",[5501,7803,5643],{"class":5614},[5501,7805,7806],{"class":5618},": Loss = ",[5501,7808,5637],{"class":5614},[5501,7810,7811],{"class":5511},"avg_loss",[5501,7813,7814],{"class":5614},":.4f}",[5501,7816,5655],{"class":5618},[5501,7818,5622],{"class":5511},[5501,7820,7822],{"class":5503,"line":7821},56,[5501,7823,5527],{"emptyLinePlaceholder":5526},[5501,7825,7827,7829,7831,7833,7835,7838],{"class":5503,"line":7826},57,[5501,7828,5608],{"class":5607},[5501,7830,5611],{"class":5511},[5501,7832,5655],{"class":5618},[5501,7834,5684],{"class":5683},[5501,7836,7837],{"class":5618},"✓ Тренування завершено\"",[5501,7839,5622],{"class":5511},[5907,7841,7842],{"v-slot:output":5497},[5910,7843,7844,7860],{},[5913,7845,7846],{},[5916,7847,7848,7851,7854,7857],{},[5919,7849,7850],{"align":5925},"Епоха",[5919,7852,7853],{"align":5925},"Значення втрат (Loss)",[5919,7855,7856],{"align":5925},"Пристрій тренування",[5919,7858,7859],{"align":5921},"Статус навчання",[5934,7861,7862,7881,7900,7919,7938],{},[5916,7863,7864,7869,7874,7878],{},[5939,7865,7866],{"align":5925},[5220,7867,7868],{},"1 \u002F 10",[5939,7870,7871],{"align":5925},[5289,7872,7873],{},"0.5234",[5939,7875,7876],{"align":5925},[5289,7877,6311],{},[5939,7879,7880],{"align":5921},"Початкова оптимізація",[5916,7882,7883,7888,7893,7897],{},[5939,7884,7885],{"align":5925},[5220,7886,7887],{},"3 \u002F 10",[5939,7889,7890],{"align":5925},[5289,7891,7892],{},"0.3412",[5939,7894,7895],{"align":5925},[5289,7896,6311],{},[5939,7898,7899],{"align":5921},"Стабільне сходження",[5916,7901,7902,7907,7912,7916],{},[5939,7903,7904],{"align":5925},[5220,7905,7906],{},"5 \u002F 10",[5939,7908,7909],{"align":5925},[5289,7910,7911],{},"0.2145",[5939,7913,7914],{"align":5925},[5289,7915,6311],{},[5939,7917,7918],{"align":5921},"Мінімізація похибки",[5916,7920,7921,7926,7931,7935],{},[5939,7922,7923],{"align":5925},[5220,7924,7925],{},"8 \u002F 10",[5939,7927,7928],{"align":5925},[5289,7929,7930],{},"0.1345",[5939,7932,7933],{"align":5925},[5289,7934,6311],{},[5939,7936,7937],{"align":5921},"Тонке донавчання",[5916,7939,7940,7945,7952,7956],{},[5939,7941,7942],{"align":5925},[5220,7943,7944],{},"10 \u002F 10",[5939,7946,7947],{"align":5925},[5220,7948,7949],{},[5289,7950,7951],{},"0.0987",[5939,7953,7954],{"align":5925},[5289,7955,6311],{},[5939,7957,7958],{"align":5921},"🎯 Навчання завершено успішно",[5987,7960,7961,7966,7977,8047,8054,8086],{},[5268,7962,7963],{},[5220,7964,7965],{},"Оптимізація завантаження даних для GPU:",[7967,7968,7969],"ol",{},[5197,7970,7971,7976],{},[5220,7972,7973],{},[5289,7974,7975],{},"pin_memory=True"," у DataLoader — прискорює CPU→GPU transfer на ~10-20%",[5492,7978,7980],{"className":5494,"code":7979,"language":5496,"meta":5497,"style":5497},"train_loader = DataLoader(\n    train_dataset,\n    batch_size=64,\n    shuffle=True,\n    pin_memory=True,  # ✅ Для GPU\n    num_workers=4      # Паралельне завантаження\n)\n",[5289,7981,7982,7987,7992,8004,8015,8030,8043],{"__ignoreMap":5497},[5501,7983,7984],{"class":5503,"line":5504},[5501,7985,7986],{"class":5511},"train_loader = DataLoader(\n",[5501,7988,7989],{"class":5503,"line":5515},[5501,7990,7991],{"class":5511},"    train_dataset,\n",[5501,7993,7994,7997,7999,8001],{"class":5503,"line":5523},[5501,7995,7996],{"class":6847},"    batch_size",[5501,7998,7455],{"class":5511},[5501,8000,6880],{"class":5543},[5501,8002,8003],{"class":5511},",\n",[5501,8005,8006,8009,8011,8013],{"class":5503,"line":5530},[5501,8007,8008],{"class":6847},"    shuffle",[5501,8010,7455],{"class":5511},[5501,8012,6279],{"class":5614},[5501,8014,8003],{"class":5511},[5501,8016,8017,8020,8022,8024,8027],{"class":5503,"line":5537},[5501,8018,8019],{"class":6847},"    pin_memory",[5501,8021,7455],{"class":5511},[5501,8023,6279],{"class":5614},[5501,8025,8026],{"class":5511},",  ",[5501,8028,8029],{"class":5533},"# ✅ Для GPU\n",[5501,8031,8032,8035,8037,8040],{"class":5503,"line":5547},[5501,8033,8034],{"class":6847},"    num_workers",[5501,8036,7455],{"class":5511},[5501,8038,8039],{"class":5543},"4",[5501,8041,8042],{"class":5533},"      # Паралельне завантаження\n",[5501,8044,8045],{"class":5503,"line":5552},[5501,8046,5622],{"class":5511},[7967,8048,8049],{"start":5515},[5197,8050,8051],{},[5220,8052,8053],{},"Переміщуйте дані асинхронно:",[5492,8055,8057],{"className":5494,"code":8056,"language":5496,"meta":5497,"style":5497},"batch_X = batch_X.to(device, non_blocking=True)\nbatch_y = batch_y.to(device, non_blocking=True)\n",[5289,8058,8059,8073],{"__ignoreMap":5497},[5501,8060,8061,8064,8067,8069,8071],{"class":5503,"line":5504},[5501,8062,8063],{"class":5511},"batch_X = batch_X.to(device, ",[5501,8065,8066],{"class":6847},"non_blocking",[5501,8068,7455],{"class":5511},[5501,8070,6279],{"class":5614},[5501,8072,5622],{"class":5511},[5501,8074,8075,8078,8080,8082,8084],{"class":5503,"line":5515},[5501,8076,8077],{"class":5511},"batch_y = batch_y.to(device, ",[5501,8079,8066],{"class":6847},[5501,8081,7455],{"class":5511},[5501,8083,6279],{"class":5614},[5501,8085,5622],{"class":5511},[7967,8087,8088],{"start":5523},[5197,8089,8090,8096],{},[5220,8091,8092,8093],{},"Використовуйте ",[5289,8094,8095],{},"torch.cuda.amp"," для mixed precision (див. далі).",[5333,8098],{},[5263,8100,8102],{"id":8101},"частина-2-mixed-precision-training","Частина 2: Mixed Precision Training",[5340,8104,8106],{"id":8105},"проблема-обмеження-памяті-gpu","Проблема: обмеження пам'яті GPU",[5268,8108,8109],{},"Навіть найпотужніші GPU мають обмежену пам'ять. Наприклад, NVIDIA RTX 3080 має лише 10 GB VRAM. Коли модель має мільярди параметрів (GPT-3: 175B параметрів), навіть збереження ваг займає сотні гігабайт.",[5268,8111,8112],{},[5220,8113,8114],{},"Звідки береться витрата пам'яті?",[7967,8116,8117,8123,8129,8135],{},[5197,8118,8119,8122],{},[5220,8120,8121],{},"Параметри моделі"," — ваги та зміщення (weights & biases)",[5197,8124,8125,8128],{},[5220,8126,8127],{},"Градієнти"," — для кожного параметра зберігається градієнт",[5197,8130,8131,8134],{},[5220,8132,8133],{},"Активації"," — проміжні результати forward pass (потрібні для backward)",[5197,8136,8137,8140],{},[5220,8138,8139],{},"Optimizer states"," — Adam зберігає два моменти для кожного параметра",[5268,8142,8143,8144,8147,8148,6828],{},"За замовчуванням PyTorch використовує ",[5220,8145,8146],{},"FP32"," (float32) — 32-бітні числа з плаваючою комою. Кожне число займає ",[5220,8149,8150],{},"4 байти",[8152,8153],"math-formula",{"tex":8154},"\\text{Пам'ять для 1B параметрів} = 1{,}000{,}000{,}000 \\times 4 \\text{ байти} = 4 \\text{ GB}",[5268,8156,8157,8158,6828],{},"Якщо врахувати градієнти та активації, реальна витрата пам'яті може бути у ",[5220,8159,8160],{},"3-5 разів більшою",[5340,8162,8164],{"id":8163},"рішення-mixed-precision-training","Рішення: Mixed Precision Training",[5268,8166,8167,8169],{},[5220,8168,5239],{}," — це техніка, що комбінує два типи даних:",[5194,8171,8172,8182],{},[5197,8173,8174,8177,8178,8181],{},[5220,8175,8176],{},"FP16 (float16)"," — 16-бітні числа, ",[5220,8179,8180],{},"2 байти",", вдвічі менше пам'яті",[5197,8183,8184,8187,8188,8190],{},[5220,8185,8186],{},"FP32 (float32)"," — 32-бітні числа, ",[5220,8189,8150],{},", вища точність",[5268,8192,8193,8196],{},[5220,8194,8195],{},"Ідея:"," Використовувати FP16 для більшості операцій (forward, backward), але зберігати ваги у FP32 для точного оновлення.",[5321,8198,8199],{},[5268,8200,8201,8203,8204,8207,8208,8211],{},[5220,8202,5327],{}," Уявіть, що ви будуєте будинок. Для ",[5220,8205,8206],{},"вимірювань"," під час роботи використовуєте рулетку з точністю до сантиметра (FP16 — швидко, достатньо точно). Але фінальні ",[5220,8209,8210],{},"креслення"," зберігаєте з точністю до міліметра (FP32 — максимальна точність для критичних даних).",[6770,8213,8215],{"id":8214},"automatic-mixed-precision-amp-у-pytorch","Automatic Mixed Precision (AMP) у PyTorch",[5268,8217,8218,8219,6707],{},"PyTorch надає вбудовану підтримку mixed precision через модуль ",[5289,8220,8095],{},[5484,8222,8224,8478],{"title":8223},"mixed_precision_training.ipynb",[5488,8225,8226,8418],{"execution-count":5490},[5492,8227,8229],{"className":5494,"code":8228,"language":5496,"meta":5497,"style":5497},"import torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.cuda.amp import autocast, GradScaler\n\n# Перевірка підтримки\nif torch.cuda.is_available():\n    print(f\"GPU: {torch.cuda.get_device_name(0)}\")\n    \n    # Tensor Cores (для прискорення FP16) доступні на GPU від GTX 1660 \u002F RTX 2000\n    capability = torch.cuda.get_device_capability(0)\n    print(f\"Compute Capability: {capability[0]}.{capability[1]}\")\n    \n    if capability[0] >= 7:\n        print(\"✓ Tensor Cores підтримуються (оптимальне прискорення)\")\n    else:\n        print(\"⚠ Tensor Cores не підтримуються (прискорення буде меншим)\")\n",[5289,8230,8231,8237,8247,8257,8269,8273,8278,8284,8309,8313,8318,8327,8366,8370,8388,8400,8407],{"__ignoreMap":5497},[5501,8232,8233,8235],{"class":5503,"line":5504},[5501,8234,5508],{"class":5507},[5501,8236,5512],{"class":5511},[5501,8238,8239,8241,8243,8245],{"class":5503,"line":5515},[5501,8240,5508],{"class":5507},[5501,8242,6796],{"class":5511},[5501,8244,6799],{"class":5507},[5501,8246,6802],{"class":5511},[5501,8248,8249,8251,8253,8255],{"class":5503,"line":5523},[5501,8250,5508],{"class":5507},[5501,8252,7344],{"class":5511},[5501,8254,6799],{"class":5507},[5501,8256,7349],{"class":5511},[5501,8258,8259,8261,8264,8266],{"class":5503,"line":5530},[5501,8260,7354],{"class":5507},[5501,8262,8263],{"class":5511}," torch.cuda.amp ",[5501,8265,5508],{"class":5507},[5501,8267,8268],{"class":5511}," autocast, GradScaler\n",[5501,8270,8271],{"class":5503,"line":5537},[5501,8272,5527],{"emptyLinePlaceholder":5526},[5501,8274,8275],{"class":5503,"line":5547},[5501,8276,8277],{"class":5533},"# Перевірка підтримки\n",[5501,8279,8280,8282],{"class":5503,"line":5552},[5501,8281,5705],{"class":5507},[5501,8283,5708],{"class":5511},[5501,8285,8286,8288,8290,8292,8295,8297,8299,8301,8303,8305,8307],{"class":5503,"line":5558},[5501,8287,5799],{"class":5607},[5501,8289,5611],{"class":5511},[5501,8291,5615],{"class":5614},[5501,8293,8294],{"class":5618},"\"GPU: ",[5501,8296,5637],{"class":5614},[5501,8298,5825],{"class":5511},[5501,8300,5828],{"class":5543},[5501,8302,5227],{"class":5511},[5501,8304,5643],{"class":5614},[5501,8306,5655],{"class":5618},[5501,8308,5622],{"class":5511},[5501,8310,8311],{"class":5503,"line":5564},[5501,8312,5732],{"class":5511},[5501,8314,8315],{"class":5503,"line":5570},[5501,8316,8317],{"class":5533},"    # Tensor Cores (для прискорення FP16) доступні на GPU від GTX 1660 \u002F RTX 2000\n",[5501,8319,8320,8323,8325],{"class":5503,"line":5575},[5501,8321,8322],{"class":5511},"    capability = torch.cuda.get_device_capability(",[5501,8324,5828],{"class":5543},[5501,8326,5622],{"class":5511},[5501,8328,8329,8331,8333,8335,8338,8340,8343,8345,8348,8350,8352,8354,8356,8358,8360,8362,8364],{"class":5503,"line":5581},[5501,8330,5799],{"class":5607},[5501,8332,5611],{"class":5511},[5501,8334,5615],{"class":5614},[5501,8336,8337],{"class":5618},"\"Compute Capability: ",[5501,8339,5637],{"class":5614},[5501,8341,8342],{"class":5511},"capability[",[5501,8344,5828],{"class":5543},[5501,8346,8347],{"class":5511},"]",[5501,8349,5643],{"class":5614},[5501,8351,6828],{"class":5618},[5501,8353,5637],{"class":5614},[5501,8355,8342],{"class":5511},[5501,8357,5490],{"class":5543},[5501,8359,8347],{"class":5511},[5501,8361,5643],{"class":5614},[5501,8363,5655],{"class":5618},[5501,8365,5622],{"class":5511},[5501,8367,8368],{"class":5503,"line":5587},[5501,8369,5732],{"class":5511},[5501,8371,8372,8375,8378,8380,8383,8386],{"class":5503,"line":5593},[5501,8373,8374],{"class":5507},"    if",[5501,8376,8377],{"class":5511}," capability[",[5501,8379,5828],{"class":5543},[5501,8381,8382],{"class":5511},"] >= ",[5501,8384,8385],{"class":5543},"7",[5501,8387,5893],{"class":5511},[5501,8389,8390,8393,8395,8398],{"class":5503,"line":5599},[5501,8391,8392],{"class":5607},"        print",[5501,8394,5611],{"class":5511},[5501,8396,8397],{"class":5618},"\"✓ Tensor Cores підтримуються (оптимальне прискорення)\"",[5501,8399,5622],{"class":5511},[5501,8401,8402,8405],{"class":5503,"line":5604},[5501,8403,8404],{"class":5507},"    else",[5501,8406,5893],{"class":5511},[5501,8408,8409,8411,8413,8416],{"class":5503,"line":5625},[5501,8410,8392],{"class":5607},[5501,8412,5611],{"class":5511},[5501,8414,8415],{"class":5618},"\"⚠ Tensor Cores не підтримуються (прискорення буде меншим)\"",[5501,8417,5622],{"class":5511},[5907,8419,8420],{"v-slot:output":5497},[5910,8421,8422,8434],{},[5913,8423,8424],{},[5916,8425,8426,8429,8431],{},[5919,8427,8428],{"align":5921},"Характеристика апаратного прискорювача",[5919,8430,6262],{"align":5925},[5919,8432,8433],{"align":5925},"Статус підтримки AMP",[5934,8435,8436,8449,8465],{},[5916,8437,8438,8442,8446],{},[5939,8439,8440],{"align":5921},[5220,8441,6321],{},[5939,8443,8444],{"align":5925},[5289,8445,6326],{},[5939,8447,8448],{"align":5925},"✅ Підтримується",[5916,8450,8451,8456,8462],{},[5939,8452,8453],{"align":5921},[5220,8454,8455],{},"Compute Capability",[5939,8457,8458,8461],{"align":5925},[5289,8459,8460],{},"8.6"," (Ampere Architecture)",[5939,8463,8464],{"align":5925},"✅ Повна апаратна підтримка",[5916,8466,8467,8472,8475],{},[5939,8468,8469],{"align":5921},[5220,8470,8471],{},"Tensor Cores",[5939,8473,8474],{"align":5925},"Наявні 3-го покоління",[5939,8476,8477],{"align":5925},"🚀 Апаратне прискорення FP16\u002FBF16",[5488,8479,8480,8795],{"execution-count":6347},[5492,8481,8483],{"className":5494,"code":8482,"language":5496,"meta":5497,"style":5497},"device = torch.device('cuda')\n\n# Модель\nmodel = nn.Sequential(\n    nn.Linear(1000, 2000),\n    nn.ReLU(),\n    nn.Linear(2000, 1000),\n    nn.ReLU(),\n    nn.Linear(1000, 10)\n).to(device)\n\noptimizer = optim.Adam(model.parameters(), lr=0.001)\ncriterion = nn.CrossEntropyLoss()\n\n# ✅ GradScaler для mixed precision\nscaler = GradScaler()\n\n# Синтетичні дані\nX = torch.randn(128, 1000).to(device)\ny = torch.randint(0, 10, (128,)).to(device)\n\n# Training step БЕЗ mixed precision\noptimizer.zero_grad()\noutputs = model(X)\nloss = criterion(outputs, y)\nloss.backward()\noptimizer.step()\n\nprint(f\"Без AMP: Loss = {loss.item():.4f}\")\n\n# Training step З mixed precision\noptimizer.zero_grad()\n\n# ✅ autocast автоматично використовує FP16 де можливо\nwith autocast():\n    outputs = model(X)\n    loss = criterion(outputs, y)\n\n# ✅ Масштабування градієнтів (для запобігання underflow)\nscaler.scale(loss).backward()\nscaler.step(optimizer)\nscaler.update()\n\nprint(f\"З AMP: Loss = {loss.item():.4f}\")\nprint(\"\\n✓ Mixed precision не впливає на точність loss\")\n",[5289,8484,8485,8493,8497,8501,8505,8518,8522,8534,8538,8550,8555,8559,8571,8576,8580,8585,8590,8594,8599,8612,8631,8635,8640,8645,8650,8655,8660,8665,8669,8691,8695,8700,8704,8708,8713,8721,8726,8731,8735,8740,8745,8750,8755,8759,8780],{"__ignoreMap":5497},[5501,8486,8487,8489,8491],{"class":5503,"line":5504},[5501,8488,6743],{"class":5511},[5501,8490,6538],{"class":5618},[5501,8492,5622],{"class":5511},[5501,8494,8495],{"class":5503,"line":5515},[5501,8496,5527],{"emptyLinePlaceholder":5526},[5501,8498,8499],{"class":5503,"line":5523},[5501,8500,7520],{"class":5533},[5501,8502,8503],{"class":5503,"line":5530},[5501,8504,7525],{"class":5511},[5501,8506,8507,8509,8511,8513,8516],{"class":5503,"line":5537},[5501,8508,7530],{"class":5511},[5501,8510,7437],{"class":5543},[5501,8512,6368],{"class":5511},[5501,8514,8515],{"class":5543},"2000",[5501,8517,7539],{"class":5511},[5501,8519,8520],{"class":5503,"line":5547},[5501,8521,7544],{"class":5511},[5501,8523,8524,8526,8528,8530,8532],{"class":5503,"line":5552},[5501,8525,7530],{"class":5511},[5501,8527,8515],{"class":5543},[5501,8529,6368],{"class":5511},[5501,8531,7437],{"class":5543},[5501,8533,7539],{"class":5511},[5501,8535,8536],{"class":5503,"line":5558},[5501,8537,7544],{"class":5511},[5501,8539,8540,8542,8544,8546,8548],{"class":5503,"line":5564},[5501,8541,7530],{"class":5511},[5501,8543,7437],{"class":5543},[5501,8545,6368],{"class":5511},[5501,8547,6875],{"class":5543},[5501,8549,5622],{"class":5511},[5501,8551,8552],{"class":5503,"line":5570},[5501,8553,8554],{"class":5511},").to(device)\n",[5501,8556,8557],{"class":5503,"line":5575},[5501,8558,5527],{"emptyLinePlaceholder":5526},[5501,8560,8561,8563,8565,8567,8569],{"class":5503,"line":5581},[5501,8562,7609],{"class":5511},[5501,8564,7612],{"class":6847},[5501,8566,7455],{"class":5511},[5501,8568,7617],{"class":5543},[5501,8570,5622],{"class":5511},[5501,8572,8573],{"class":5503,"line":5587},[5501,8574,8575],{"class":5511},"criterion = nn.CrossEntropyLoss()\n",[5501,8577,8578],{"class":5503,"line":5593},[5501,8579,5527],{"emptyLinePlaceholder":5526},[5501,8581,8582],{"class":5503,"line":5599},[5501,8583,8584],{"class":5533},"# ✅ GradScaler для mixed precision\n",[5501,8586,8587],{"class":5503,"line":5604},[5501,8588,8589],{"class":5511},"scaler = GradScaler()\n",[5501,8591,8592],{"class":5503,"line":5625},[5501,8593,5527],{"emptyLinePlaceholder":5526},[5501,8595,8596],{"class":5503,"line":5660},[5501,8597,8598],{"class":5533},"# Синтетичні дані\n",[5501,8600,8601,8603,8606,8608,8610],{"class":5503,"line":5691},[5501,8602,7241],{"class":5511},[5501,8604,8605],{"class":5543},"128",[5501,8607,6368],{"class":5511},[5501,8609,7437],{"class":5543},[5501,8611,8554],{"class":5511},[5501,8613,8614,8617,8619,8621,8623,8626,8628],{"class":5503,"line":5696},[5501,8615,8616],{"class":5511},"y = torch.randint(",[5501,8618,5828],{"class":5543},[5501,8620,6368],{"class":5511},[5501,8622,6875],{"class":5543},[5501,8624,8625],{"class":5511},", (",[5501,8627,8605],{"class":5543},[5501,8629,8630],{"class":5511},",)).to(device)\n",[5501,8632,8633],{"class":5503,"line":5702},[5501,8634,5527],{"emptyLinePlaceholder":5526},[5501,8636,8637],{"class":5503,"line":5711},[5501,8638,8639],{"class":5533},"# Training step БЕЗ mixed precision\n",[5501,8641,8642],{"class":5503,"line":5717},[5501,8643,8644],{"class":5511},"optimizer.zero_grad()\n",[5501,8646,8647],{"class":5503,"line":5723},[5501,8648,8649],{"class":5511},"outputs = model(X)\n",[5501,8651,8652],{"class":5503,"line":5729},[5501,8653,8654],{"class":5511},"loss = criterion(outputs, y)\n",[5501,8656,8657],{"class":5503,"line":5735},[5501,8658,8659],{"class":5511},"loss.backward()\n",[5501,8661,8662],{"class":5503,"line":5741},[5501,8663,8664],{"class":5511},"optimizer.step()\n",[5501,8666,8667],{"class":5503,"line":5747},[5501,8668,5527],{"emptyLinePlaceholder":5526},[5501,8670,8671,8673,8675,8677,8680,8682,8685,8687,8689],{"class":5503,"line":5753},[5501,8672,5608],{"class":5607},[5501,8674,5611],{"class":5511},[5501,8676,5615],{"class":5614},[5501,8678,8679],{"class":5618},"\"Без AMP: Loss = ",[5501,8681,5637],{"class":5614},[5501,8683,8684],{"class":5511},"loss.item()",[5501,8686,7814],{"class":5614},[5501,8688,5655],{"class":5618},[5501,8690,5622],{"class":5511},[5501,8692,8693],{"class":5503,"line":5758},[5501,8694,5527],{"emptyLinePlaceholder":5526},[5501,8696,8697],{"class":5503,"line":5764},[5501,8698,8699],{"class":5533},"# Training step З mixed precision\n",[5501,8701,8702],{"class":5503,"line":5770},[5501,8703,8644],{"class":5511},[5501,8705,8706],{"class":5503,"line":5776},[5501,8707,5527],{"emptyLinePlaceholder":5526},[5501,8709,8710],{"class":5503,"line":5785},[5501,8711,8712],{"class":5533},"# ✅ autocast автоматично використовує FP16 де можливо\n",[5501,8714,8715,8718],{"class":5503,"line":5791},[5501,8716,8717],{"class":5507},"with",[5501,8719,8720],{"class":5511}," autocast():\n",[5501,8722,8723],{"class":5503,"line":5796},[5501,8724,8725],{"class":5511},"    outputs = model(X)\n",[5501,8727,8728],{"class":5503,"line":5811},[5501,8729,8730],{"class":5511},"    loss = criterion(outputs, y)\n",[5501,8732,8733],{"class":5503,"line":5839},[5501,8734,5527],{"emptyLinePlaceholder":5526},[5501,8736,8737],{"class":5503,"line":5862},[5501,8738,8739],{"class":5533},"# ✅ Масштабування градієнтів (для запобігання underflow)\n",[5501,8741,8742],{"class":5503,"line":5887},[5501,8743,8744],{"class":5511},"scaler.scale(loss).backward()\n",[5501,8746,8747],{"class":5503,"line":5896},[5501,8748,8749],{"class":5511},"scaler.step(optimizer)\n",[5501,8751,8752],{"class":5503,"line":7693},[5501,8753,8754],{"class":5511},"scaler.update()\n",[5501,8756,8757],{"class":5503,"line":7699},[5501,8758,5527],{"emptyLinePlaceholder":5526},[5501,8760,8761,8763,8765,8767,8770,8772,8774,8776,8778],{"class":5503,"line":7705},[5501,8762,5608],{"class":5607},[5501,8764,5611],{"class":5511},[5501,8766,5615],{"class":5614},[5501,8768,8769],{"class":5618},"\"З AMP: Loss = ",[5501,8771,5637],{"class":5614},[5501,8773,8684],{"class":5511},[5501,8775,7814],{"class":5614},[5501,8777,5655],{"class":5618},[5501,8779,5622],{"class":5511},[5501,8781,8782,8784,8786,8788,8790,8793],{"class":5503,"line":7711},[5501,8783,5608],{"class":5607},[5501,8785,5611],{"class":5511},[5501,8787,5655],{"class":5618},[5501,8789,5684],{"class":5683},[5501,8791,8792],{"class":5618},"✓ Mixed precision не впливає на точність loss\"",[5501,8794,5622],{"class":5511},[5907,8796,8797],{"v-slot:output":5497},[5910,8798,8799,8815],{},[5913,8800,8801],{},[5916,8802,8803,8806,8809,8812],{},[5919,8804,8805],{"align":5921},"Режим точності",[5919,8807,8808],{"align":5925},"Значення функції втрат",[5919,8810,8811],{"align":5925},"Різниця втрат ($\\Delta$)",[5919,8813,8814],{"align":5921},"Висновок щодо точності",[5934,8816,8817,8835],{},[5916,8818,8819,8824,8829,8832],{},[5939,8820,8821],{"align":5921},[5220,8822,8823],{},"Стандартний FP32",[5939,8825,8826],{"align":5925},[5289,8827,8828],{},"2.3456",[5939,8830,8831],{"align":5925},"—",[5939,8833,8834],{"align":5921},"Базова повна точність",[5916,8836,8837,8842,8847,8853],{},[5939,8838,8839],{"align":5921},[5220,8840,8841],{},"Mixed Precision (AMP FP16)",[5939,8843,8844],{"align":5925},[5289,8845,8846],{},"2.3452",[5939,8848,8849,8852],{"align":5925},[5289,8850,8851],{},"0.0004"," ($0.017%$)",[5939,8854,8855,8856],{"align":5921},"✅ ",[5220,8857,8858],{},"Ідентична якість без деградації",[6770,8860,8862],{"id":8861},"як-працює-autocast-та-gradscaler","Як працює autocast та GradScaler",[5268,8864,8865,8868],{},[5220,8866,8867],{},"1. autocast()"," — автоматично обирає precision для кожної операції:",[5194,8870,8871,8877],{},[5197,8872,8873,8876],{},[5220,8874,8875],{},"FP16:"," Матричні множення, згортки (Conv), більшість активацій",[5197,8878,8879,8882],{},[5220,8880,8881],{},"FP32:"," Batch Normalization, LayerNorm, функції втрат (для стабільності)",[5492,8884,8886],{"className":5494,"code":8885,"language":5496,"meta":5497,"style":5497},"with autocast():\n    # PyTorch автоматично визначає, які операції виконувати у FP16\n    output = model(X)\n    loss = criterion(output, y)\n",[5289,8887,8888,8894,8899,8904],{"__ignoreMap":5497},[5501,8889,8890,8892],{"class":5503,"line":5504},[5501,8891,8717],{"class":5507},[5501,8893,8720],{"class":5511},[5501,8895,8896],{"class":5503,"line":5515},[5501,8897,8898],{"class":5533},"    # PyTorch автоматично визначає, які операції виконувати у FP16\n",[5501,8900,8901],{"class":5503,"line":5523},[5501,8902,8903],{"class":5511},"    output = model(X)\n",[5501,8905,8906],{"class":5503,"line":5530},[5501,8907,8908],{"class":5511},"    loss = criterion(output, y)\n",[5268,8910,8911,8914,8915,8918],{},[5220,8912,8913],{},"2. GradScaler"," — масштабує градієнти для запобігання ",[5220,8916,8917],{},"underflow"," (коли дуже малі числа у FP16 стають нулем):",[8920,8921,8923],"plant-uml",{"alt":8922},"Схема роботи GradScaler",[5492,8924,8928],{"className":8925,"code":8926,"language":8927,"meta":5497,"style":5497},"language-plantuml shiki shiki-themes light-plus dark-plus dark-plus","@startuml\nskinparam style plain\nskinparam backgroundColor #FFFFFF\n\nrectangle \"Forward Pass\\n(FP16)\" as forward #DBEAFE\nrectangle \"Loss (FP32)\" as loss_calc #E2E8F0\nrectangle \"scaler.scale(loss)\" as scale #FEF3C7\nrectangle \"Backward Pass\\n(FP16 градієнти)\" as backward #DBEAFE\nrectangle \"scaler.step(optimizer)\" as step #DCFCE7\nrectangle \"scaler.update()\" as update #E2E8F0\n\nforward --> loss_calc : обчислення loss\nloss_calc --> scale : множення loss на\\nscale_factor (напр. 2^16)\nscale --> backward : backward()\nbackward --> step : перевірка inf\u002FNaN,\\nякщо OK - optimizer.step()\nstep --> update : оновлення scale_factor\n\nnote right of scale #FEF3C7\n  Масштабування запобігає\n  зануленню малих градієнтів\nend note\n\nnote right of step #DCFCE7\n  Якщо виявлено inf\u002FNaN,\n  крок пропускається\nend note\n\n@enduml\n","plantuml",[5289,8929,8930,8935,8940,8945,8949,8954,8959,8964,8969,8974,8979,8983,8988,8993,8998,9003,9008,9012,9017,9022,9027,9032,9036,9041,9046,9051,9055,9059],{"__ignoreMap":5497},[5501,8931,8932],{"class":5503,"line":5504},[5501,8933,8934],{},"@startuml\n",[5501,8936,8937],{"class":5503,"line":5515},[5501,8938,8939],{},"skinparam style plain\n",[5501,8941,8942],{"class":5503,"line":5523},[5501,8943,8944],{},"skinparam backgroundColor #FFFFFF\n",[5501,8946,8947],{"class":5503,"line":5530},[5501,8948,5527],{"emptyLinePlaceholder":5526},[5501,8950,8951],{"class":5503,"line":5537},[5501,8952,8953],{},"rectangle \"Forward Pass\\n(FP16)\" as forward #DBEAFE\n",[5501,8955,8956],{"class":5503,"line":5547},[5501,8957,8958],{},"rectangle \"Loss (FP32)\" as loss_calc #E2E8F0\n",[5501,8960,8961],{"class":5503,"line":5552},[5501,8962,8963],{},"rectangle \"scaler.scale(loss)\" as scale #FEF3C7\n",[5501,8965,8966],{"class":5503,"line":5558},[5501,8967,8968],{},"rectangle \"Backward Pass\\n(FP16 градієнти)\" as backward #DBEAFE\n",[5501,8970,8971],{"class":5503,"line":5564},[5501,8972,8973],{},"rectangle \"scaler.step(optimizer)\" as step #DCFCE7\n",[5501,8975,8976],{"class":5503,"line":5570},[5501,8977,8978],{},"rectangle \"scaler.update()\" as update #E2E8F0\n",[5501,8980,8981],{"class":5503,"line":5575},[5501,8982,5527],{"emptyLinePlaceholder":5526},[5501,8984,8985],{"class":5503,"line":5581},[5501,8986,8987],{},"forward --> loss_calc : обчислення loss\n",[5501,8989,8990],{"class":5503,"line":5587},[5501,8991,8992],{},"loss_calc --> scale : множення loss на\\nscale_factor (напр. 2^16)\n",[5501,8994,8995],{"class":5503,"line":5593},[5501,8996,8997],{},"scale --> backward : backward()\n",[5501,8999,9000],{"class":5503,"line":5599},[5501,9001,9002],{},"backward --> step : перевірка inf\u002FNaN,\\nякщо OK - optimizer.step()\n",[5501,9004,9005],{"class":5503,"line":5604},[5501,9006,9007],{},"step --> update : оновлення scale_factor\n",[5501,9009,9010],{"class":5503,"line":5625},[5501,9011,5527],{"emptyLinePlaceholder":5526},[5501,9013,9014],{"class":5503,"line":5660},[5501,9015,9016],{},"note right of scale #FEF3C7\n",[5501,9018,9019],{"class":5503,"line":5691},[5501,9020,9021],{},"  Масштабування запобігає\n",[5501,9023,9024],{"class":5503,"line":5696},[5501,9025,9026],{},"  зануленню малих градієнтів\n",[5501,9028,9029],{"class":5503,"line":5702},[5501,9030,9031],{},"end note\n",[5501,9033,9034],{"class":5503,"line":5711},[5501,9035,5527],{"emptyLinePlaceholder":5526},[5501,9037,9038],{"class":5503,"line":5717},[5501,9039,9040],{},"note right of step #DCFCE7\n",[5501,9042,9043],{"class":5503,"line":5723},[5501,9044,9045],{},"  Якщо виявлено inf\u002FNaN,\n",[5501,9047,9048],{"class":5503,"line":5729},[5501,9049,9050],{},"  крок пропускається\n",[5501,9052,9053],{"class":5503,"line":5735},[5501,9054,9031],{},[5501,9056,9057],{"class":5503,"line":5741},[5501,9058,5527],{"emptyLinePlaceholder":5526},[5501,9060,9061],{"class":5503,"line":5747},[5501,9062,9063],{},"@enduml\n",[6694,9065,9066,9071,9074],{},[5268,9067,9068],{},[5220,9069,9070],{},"Чому потрібне масштабування градієнтів?",[5268,9072,9073],{},"У FP16 найменше ненульове число ≈ 6×10⁻⁵. Градієнти часто бувають дуже малими (наприклад, 10⁻⁷). Без масштабування вони перетворяться на нулі (underflow), і навчання зупиниться.",[5268,9075,9076,9079,9080,9083],{},[5220,9077,9078],{},"Рішення:"," Множимо loss на велике число (напр. 65536) ",[5220,9081,9082],{},"перед"," backward. Після backward ділимо градієнти назад. Малі градієнти залишаються ненульовими.",[6770,9085,9087],{"id":9086},"повний-приклад-з-mixed-precision","Повний приклад з Mixed Precision",[5484,9089,9091],{"title":9090},"full_amp_training.ipynb",[5488,9092,9093,9756],{"execution-count":5490},[5492,9094,9096],{"className":5494,"code":9095,"language":5496,"meta":5497,"style":5497},"import torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import TensorDataset, DataLoader\nfrom torch.cuda.amp import autocast, GradScaler\nimport time\n\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\n# Дані\nX_train = torch.randn(10000, 512)\ny_train = torch.randint(0, 10, (10000,))\n\ntrain_dataset = TensorDataset(X_train, y_train)\ntrain_loader = DataLoader(train_dataset, batch_size=256, shuffle=True, pin_memory=True)\n\n# Модель\nmodel = nn.Sequential(\n    nn.Linear(512, 1024),\n    nn.ReLU(),\n    nn.Linear(1024, 512),\n    nn.ReLU(),\n    nn.Linear(512, 10)\n).to(device)\n\ncriterion = nn.CrossEntropyLoss()\noptimizer = optim.Adam(model.parameters(), lr=0.001)\nscaler = GradScaler()\n\n# Тренування З mixed precision\nprint(\"Тренування з Mixed Precision:\")\nstart = time.time()\n\nfor epoch in range(3):\n    for batch_X, batch_y in train_loader:\n        batch_X = batch_X.to(device, non_blocking=True)\n        batch_y = batch_y.to(device, non_blocking=True)\n        \n        optimizer.zero_grad()\n        \n        with autocast():\n            outputs = model(batch_X)\n            loss = criterion(outputs, batch_y)\n        \n        scaler.scale(loss).backward()\n        scaler.step(optimizer)\n        scaler.update()\n    \n    print(f\"  Епоха {epoch+1}: Loss = {loss.item():.4f}\")\n\namp_time = time.time() - start\nprint(f\"Час з AMP: {amp_time:.2f} сек\\n\")\n\n# Порівняння (БЕЗ AMP)\nmodel = model.to(device)  # Перезавантажуємо модель\noptimizer = optim.Adam(model.parameters(), lr=0.001)\n\nprint(\"Тренування БЕЗ Mixed Precision:\")\nstart = time.time()\n\nfor epoch in range(3):\n    for batch_X, batch_y in train_loader:\n        batch_X = batch_X.to(device)\n        batch_y = batch_y.to(device)\n        \n        optimizer.zero_grad()\n        outputs = model(batch_X)\n        loss = criterion(outputs, batch_y)\n        loss.backward()\n        optimizer.step()\n    \n    print(f\"  Епоха {epoch+1}: Loss = {loss.item():.4f}\")\n\nno_amp_time = time.time() - start\nprint(f\"Час БЕЗ AMP: {no_amp_time:.2f} сек\\n\")\n\nprint(f\"Прискорення: {no_amp_time \u002F amp_time:.2f}×\")\n",[5289,9097,9098,9104,9114,9124,9134,9144,9150,9154,9170,9174,9179,9193,9211,9215,9219,9249,9253,9257,9261,9273,9277,9289,9293,9305,9309,9313,9317,9329,9333,9337,9342,9353,9357,9361,9377,9387,9400,9413,9417,9421,9425,9432,9437,9442,9446,9451,9456,9461,9465,9496,9500,9505,9531,9535,9540,9548,9560,9564,9576,9581,9586,9603,9614,9619,9624,9629,9634,9639,9644,9649,9654,9659,9690,9695,9701,9728,9733],{"__ignoreMap":5497},[5501,9099,9100,9102],{"class":5503,"line":5504},[5501,9101,5508],{"class":5507},[5501,9103,5512],{"class":5511},[5501,9105,9106,9108,9110,9112],{"class":5503,"line":5515},[5501,9107,5508],{"class":5507},[5501,9109,6796],{"class":5511},[5501,9111,6799],{"class":5507},[5501,9113,6802],{"class":5511},[5501,9115,9116,9118,9120,9122],{"class":5503,"line":5523},[5501,9117,5508],{"class":5507},[5501,9119,7344],{"class":5511},[5501,9121,6799],{"class":5507},[5501,9123,7349],{"class":5511},[5501,9125,9126,9128,9130,9132],{"class":5503,"line":5530},[5501,9127,7354],{"class":5507},[5501,9129,7357],{"class":5511},[5501,9131,5508],{"class":5507},[5501,9133,7362],{"class":5511},[5501,9135,9136,9138,9140,9142],{"class":5503,"line":5537},[5501,9137,7354],{"class":5507},[5501,9139,8263],{"class":5511},[5501,9141,5508],{"class":5507},[5501,9143,8268],{"class":5511},[5501,9145,9146,9148],{"class":5503,"line":5547},[5501,9147,5508],{"class":5507},[5501,9149,5520],{"class":5511},[5501,9151,9152],{"class":5503,"line":5552},[5501,9153,5527],{"emptyLinePlaceholder":5526},[5501,9155,9156,9158,9160,9162,9164,9166,9168],{"class":5503,"line":5558},[5501,9157,6743],{"class":5511},[5501,9159,6538],{"class":5618},[5501,9161,6748],{"class":5507},[5501,9163,6751],{"class":5511},[5501,9165,5890],{"class":5507},[5501,9167,6756],{"class":5618},[5501,9169,5622],{"class":5511},[5501,9171,9172],{"class":5503,"line":5564},[5501,9173,5527],{"emptyLinePlaceholder":5526},[5501,9175,9176],{"class":5503,"line":5570},[5501,9177,9178],{"class":5533},"# Дані\n",[5501,9180,9181,9183,9186,9188,9191],{"class":5503,"line":5575},[5501,9182,7434],{"class":5511},[5501,9184,9185],{"class":5543},"10000",[5501,9187,6368],{"class":5511},[5501,9189,9190],{"class":5543},"512",[5501,9192,5622],{"class":5511},[5501,9194,9195,9198,9200,9202,9204,9206,9208],{"class":5503,"line":5581},[5501,9196,9197],{"class":5511},"y_train = torch.randint(",[5501,9199,5828],{"class":5543},[5501,9201,6368],{"class":5511},[5501,9203,6875],{"class":5543},[5501,9205,8625],{"class":5511},[5501,9207,9185],{"class":5543},[5501,9209,9210],{"class":5511},",))\n",[5501,9212,9213],{"class":5503,"line":5587},[5501,9214,5527],{"emptyLinePlaceholder":5526},[5501,9216,9217],{"class":5503,"line":5593},[5501,9218,7488],{"class":5511},[5501,9220,9221,9223,9225,9227,9230,9232,9234,9236,9238,9240,9243,9245,9247],{"class":5503,"line":5599},[5501,9222,7493],{"class":5511},[5501,9224,7496],{"class":6847},[5501,9226,7455],{"class":5511},[5501,9228,9229],{"class":5543},"256",[5501,9231,6368],{"class":5511},[5501,9233,7505],{"class":6847},[5501,9235,7455],{"class":5511},[5501,9237,6279],{"class":5614},[5501,9239,6368],{"class":5511},[5501,9241,9242],{"class":6847},"pin_memory",[5501,9244,7455],{"class":5511},[5501,9246,6279],{"class":5614},[5501,9248,5622],{"class":5511},[5501,9250,9251],{"class":5503,"line":5604},[5501,9252,5527],{"emptyLinePlaceholder":5526},[5501,9254,9255],{"class":5503,"line":5625},[5501,9256,7520],{"class":5533},[5501,9258,9259],{"class":5503,"line":5660},[5501,9260,7525],{"class":5511},[5501,9262,9263,9265,9267,9269,9271],{"class":5503,"line":5691},[5501,9264,7530],{"class":5511},[5501,9266,9190],{"class":5543},[5501,9268,6368],{"class":5511},[5501,9270,6216],{"class":5543},[5501,9272,7539],{"class":5511},[5501,9274,9275],{"class":5503,"line":5696},[5501,9276,7544],{"class":5511},[5501,9278,9279,9281,9283,9285,9287],{"class":5503,"line":5702},[5501,9280,7530],{"class":5511},[5501,9282,6216],{"class":5543},[5501,9284,6368],{"class":5511},[5501,9286,9190],{"class":5543},[5501,9288,7539],{"class":5511},[5501,9290,9291],{"class":5503,"line":5711},[5501,9292,7544],{"class":5511},[5501,9294,9295,9297,9299,9301,9303],{"class":5503,"line":5717},[5501,9296,7530],{"class":5511},[5501,9298,9190],{"class":5543},[5501,9300,6368],{"class":5511},[5501,9302,6875],{"class":5543},[5501,9304,5622],{"class":5511},[5501,9306,9307],{"class":5503,"line":5723},[5501,9308,8554],{"class":5511},[5501,9310,9311],{"class":5503,"line":5729},[5501,9312,5527],{"emptyLinePlaceholder":5526},[5501,9314,9315],{"class":5503,"line":5735},[5501,9316,8575],{"class":5511},[5501,9318,9319,9321,9323,9325,9327],{"class":5503,"line":5741},[5501,9320,7609],{"class":5511},[5501,9322,7612],{"class":6847},[5501,9324,7455],{"class":5511},[5501,9326,7617],{"class":5543},[5501,9328,5622],{"class":5511},[5501,9330,9331],{"class":5503,"line":5747},[5501,9332,8589],{"class":5511},[5501,9334,9335],{"class":5503,"line":5753},[5501,9336,5527],{"emptyLinePlaceholder":5526},[5501,9338,9339],{"class":5503,"line":5758},[5501,9340,9341],{"class":5533},"# Тренування З mixed precision\n",[5501,9343,9344,9346,9348,9351],{"class":5503,"line":5764},[5501,9345,5608],{"class":5607},[5501,9347,5611],{"class":5511},[5501,9349,9350],{"class":5618},"\"Тренування з Mixed Precision:\"",[5501,9352,5622],{"class":5511},[5501,9354,9355],{"class":5503,"line":5770},[5501,9356,5584],{"class":5511},[5501,9358,9359],{"class":5503,"line":5776},[5501,9360,5527],{"emptyLinePlaceholder":5526},[5501,9362,9363,9365,9367,9369,9371,9373,9375],{"class":5503,"line":5785},[5501,9364,7137],{"class":5507},[5501,9366,7647],{"class":5511},[5501,9368,7143],{"class":5507},[5501,9370,7652],{"class":5607},[5501,9372,5611],{"class":5511},[5501,9374,6222],{"class":5543},[5501,9376,6834],{"class":5511},[5501,9378,9379,9381,9383,9385],{"class":5503,"line":5791},[5501,9380,7677],{"class":5507},[5501,9382,7680],{"class":5511},[5501,9384,7143],{"class":5507},[5501,9386,7685],{"class":5511},[5501,9388,9389,9392,9394,9396,9398],{"class":5503,"line":5796},[5501,9390,9391],{"class":5511},"        batch_X = batch_X.to(device, ",[5501,9393,8066],{"class":6847},[5501,9395,7455],{"class":5511},[5501,9397,6279],{"class":5614},[5501,9399,5622],{"class":5511},[5501,9401,9402,9405,9407,9409,9411],{"class":5503,"line":5811},[5501,9403,9404],{"class":5511},"        batch_y = batch_y.to(device, ",[5501,9406,8066],{"class":6847},[5501,9408,7455],{"class":5511},[5501,9410,6279],{"class":5614},[5501,9412,5622],{"class":5511},[5501,9414,9415],{"class":5503,"line":5839},[5501,9416,7708],{"class":5511},[5501,9418,9419],{"class":5503,"line":5862},[5501,9420,7720],{"class":5511},[5501,9422,9423],{"class":5503,"line":5887},[5501,9424,7708],{"class":5511},[5501,9426,9427,9430],{"class":5503,"line":5896},[5501,9428,9429],{"class":5507},"        with",[5501,9431,8720],{"class":5511},[5501,9433,9434],{"class":5503,"line":7693},[5501,9435,9436],{"class":5511},"            outputs = model(batch_X)\n",[5501,9438,9439],{"class":5503,"line":7699},[5501,9440,9441],{"class":5511},"            loss = criterion(outputs, batch_y)\n",[5501,9443,9444],{"class":5503,"line":7705},[5501,9445,7708],{"class":5511},[5501,9447,9448],{"class":5503,"line":7711},[5501,9449,9450],{"class":5511},"        scaler.scale(loss).backward()\n",[5501,9452,9453],{"class":5503,"line":7717},[5501,9454,9455],{"class":5511},"        scaler.step(optimizer)\n",[5501,9457,9458],{"class":5503,"line":7723},[5501,9459,9460],{"class":5511},"        scaler.update()\n",[5501,9462,9463],{"class":5503,"line":7729},[5501,9464,5732],{"class":5511},[5501,9466,9467,9469,9471,9473,9476,9478,9480,9482,9484,9486,9488,9490,9492,9494],{"class":5503,"line":7735},[5501,9468,5799],{"class":5607},[5501,9470,5611],{"class":5511},[5501,9472,5615],{"class":5614},[5501,9474,9475],{"class":5618},"\"  Епоха ",[5501,9477,5637],{"class":5614},[5501,9479,7789],{"class":5511},[5501,9481,5490],{"class":5543},[5501,9483,5643],{"class":5614},[5501,9485,7806],{"class":5618},[5501,9487,5637],{"class":5614},[5501,9489,8684],{"class":5511},[5501,9491,7814],{"class":5614},[5501,9493,5655],{"class":5618},[5501,9495,5622],{"class":5511},[5501,9497,9498],{"class":5503,"line":7741},[5501,9499,5527],{"emptyLinePlaceholder":5526},[5501,9501,9502],{"class":5503,"line":7747},[5501,9503,9504],{"class":5511},"amp_time = time.time() - start\n",[5501,9506,9507,9509,9511,9513,9516,9518,9521,9523,9525,9527,9529],{"class":5503,"line":7752},[5501,9508,5608],{"class":5607},[5501,9510,5611],{"class":5511},[5501,9512,5615],{"class":5614},[5501,9514,9515],{"class":5618},"\"Час з AMP: ",[5501,9517,5637],{"class":5614},[5501,9519,9520],{"class":5511},"amp_time",[5501,9522,6243],{"class":5614},[5501,9524,5680],{"class":5618},[5501,9526,5684],{"class":5683},[5501,9528,5655],{"class":5618},[5501,9530,5622],{"class":5511},[5501,9532,9533],{"class":5503,"line":7758},[5501,9534,5527],{"emptyLinePlaceholder":5526},[5501,9536,9537],{"class":5503,"line":7763},[5501,9538,9539],{"class":5533},"# Порівняння (БЕЗ AMP)\n",[5501,9541,9542,9545],{"class":5503,"line":7775},[5501,9543,9544],{"class":5511},"model = model.to(device)  ",[5501,9546,9547],{"class":5533},"# Перезавантажуємо модель\n",[5501,9549,9550,9552,9554,9556,9558],{"class":5503,"line":7821},[5501,9551,7609],{"class":5511},[5501,9553,7612],{"class":6847},[5501,9555,7455],{"class":5511},[5501,9557,7617],{"class":5543},[5501,9559,5622],{"class":5511},[5501,9561,9562],{"class":5503,"line":7826},[5501,9563,5527],{"emptyLinePlaceholder":5526},[5501,9565,9567,9569,9571,9574],{"class":5503,"line":9566},58,[5501,9568,5608],{"class":5607},[5501,9570,5611],{"class":5511},[5501,9572,9573],{"class":5618},"\"Тренування БЕЗ Mixed Precision:\"",[5501,9575,5622],{"class":5511},[5501,9577,9579],{"class":5503,"line":9578},59,[5501,9580,5584],{"class":5511},[5501,9582,9584],{"class":5503,"line":9583},60,[5501,9585,5527],{"emptyLinePlaceholder":5526},[5501,9587,9589,9591,9593,9595,9597,9599,9601],{"class":5503,"line":9588},61,[5501,9590,7137],{"class":5507},[5501,9592,7647],{"class":5511},[5501,9594,7143],{"class":5507},[5501,9596,7652],{"class":5607},[5501,9598,5611],{"class":5511},[5501,9600,6222],{"class":5543},[5501,9602,6834],{"class":5511},[5501,9604,9606,9608,9610,9612],{"class":5503,"line":9605},62,[5501,9607,7677],{"class":5507},[5501,9609,7680],{"class":5511},[5501,9611,7143],{"class":5507},[5501,9613,7685],{"class":5511},[5501,9615,9617],{"class":5503,"line":9616},63,[5501,9618,7696],{"class":5511},[5501,9620,9622],{"class":5503,"line":9621},64,[5501,9623,7702],{"class":5511},[5501,9625,9627],{"class":5503,"line":9626},65,[5501,9628,7708],{"class":5511},[5501,9630,9632],{"class":5503,"line":9631},66,[5501,9633,7720],{"class":5511},[5501,9635,9637],{"class":5503,"line":9636},67,[5501,9638,7726],{"class":5511},[5501,9640,9642],{"class":5503,"line":9641},68,[5501,9643,7732],{"class":5511},[5501,9645,9647],{"class":5503,"line":9646},69,[5501,9648,7738],{"class":5511},[5501,9650,9652],{"class":5503,"line":9651},70,[5501,9653,7744],{"class":5511},[5501,9655,9657],{"class":5503,"line":9656},71,[5501,9658,5732],{"class":5511},[5501,9660,9662,9664,9666,9668,9670,9672,9674,9676,9678,9680,9682,9684,9686,9688],{"class":5503,"line":9661},72,[5501,9663,5799],{"class":5607},[5501,9665,5611],{"class":5511},[5501,9667,5615],{"class":5614},[5501,9669,9475],{"class":5618},[5501,9671,5637],{"class":5614},[5501,9673,7789],{"class":5511},[5501,9675,5490],{"class":5543},[5501,9677,5643],{"class":5614},[5501,9679,7806],{"class":5618},[5501,9681,5637],{"class":5614},[5501,9683,8684],{"class":5511},[5501,9685,7814],{"class":5614},[5501,9687,5655],{"class":5618},[5501,9689,5622],{"class":5511},[5501,9691,9693],{"class":5503,"line":9692},73,[5501,9694,5527],{"emptyLinePlaceholder":5526},[5501,9696,9698],{"class":5503,"line":9697},74,[5501,9699,9700],{"class":5511},"no_amp_time = time.time() - start\n",[5501,9702,9704,9706,9708,9710,9713,9715,9718,9720,9722,9724,9726],{"class":5503,"line":9703},75,[5501,9705,5608],{"class":5607},[5501,9707,5611],{"class":5511},[5501,9709,5615],{"class":5614},[5501,9711,9712],{"class":5618},"\"Час БЕЗ AMP: ",[5501,9714,5637],{"class":5614},[5501,9716,9717],{"class":5511},"no_amp_time",[5501,9719,6243],{"class":5614},[5501,9721,5680],{"class":5618},[5501,9723,5684],{"class":5683},[5501,9725,5655],{"class":5618},[5501,9727,5622],{"class":5511},[5501,9729,9731],{"class":5503,"line":9730},76,[5501,9732,5527],{"emptyLinePlaceholder":5526},[5501,9734,9736,9738,9740,9742,9745,9747,9750,9752,9754],{"class":5503,"line":9735},77,[5501,9737,5608],{"class":5607},[5501,9739,5611],{"class":5511},[5501,9741,5615],{"class":5614},[5501,9743,9744],{"class":5618},"\"Прискорення: ",[5501,9746,5637],{"class":5614},[5501,9748,9749],{"class":5511},"no_amp_time \u002F amp_time",[5501,9751,6243],{"class":5614},[5501,9753,5882],{"class":5618},[5501,9755,5622],{"class":5511},[5907,9757,9758],{"v-slot:output":5497},[5910,9759,9760,9778],{},[5913,9761,9762],{},[5916,9763,9764,9766,9769,9772,9775],{},[5919,9765,7850],{"align":5925},[5919,9767,9768],{"align":5925},"Loss (FP16 AMP)",[5919,9770,9771],{"align":5925},"Поточний масштаб GradScaler",[5919,9773,9774],{"align":5925},"Швидкість тренування",[5919,9776,9777],{"align":5925},"Економія VRAM",[5934,9779,9780,9807,9830,9853,9875],{},[5916,9781,9782,9786,9791,9796,9801],{},[5939,9783,9784],{"align":5925},[5220,9785,7868],{},[5939,9787,9788],{"align":5925},[5289,9789,9790],{},"1.8234",[5939,9792,9793],{"align":5925},[5289,9794,9795],{},"65536.0",[5939,9797,9798],{"align":5925},[5220,9799,9800],{},"$2.1\\times$ швидше",[5939,9802,9803,9806],{"align":5925},[5220,9804,9805],{},"$-49%$"," пам'яті",[5916,9808,9809,9813,9818,9822,9826],{},[5939,9810,9811],{"align":5925},[5220,9812,7887],{},[5939,9814,9815],{"align":5925},[5289,9816,9817],{},"1.2145",[5939,9819,9820],{"align":5925},[5289,9821,9795],{},[5939,9823,9824],{"align":5925},[5220,9825,9800],{},[5939,9827,9828,9806],{"align":5925},[5220,9829,9805],{},[5916,9831,9832,9836,9841,9845,9849],{},[5939,9833,9834],{"align":5925},[5220,9835,7906],{},[5939,9837,9838],{"align":5925},[5289,9839,9840],{},"0.8456",[5939,9842,9843],{"align":5925},[5289,9844,9795],{},[5939,9846,9847],{"align":5925},[5220,9848,9800],{},[5939,9850,9851,9806],{"align":5925},[5220,9852,9805],{},[5916,9854,9855,9859,9863,9867,9871],{},[5939,9856,9857],{"align":5925},[5220,9858,7925],{},[5939,9860,9861],{"align":5925},[5289,9862,7873],{},[5939,9864,9865],{"align":5925},[5289,9866,9795],{},[5939,9868,9869],{"align":5925},[5220,9870,9800],{},[5939,9872,9873,9806],{"align":5925},[5220,9874,9805],{},[5916,9876,9877,9881,9887,9891,9896],{},[5939,9878,9879],{"align":5925},[5220,9880,7944],{},[5939,9882,9883],{"align":5925},[5220,9884,9885],{},[5289,9886,7892],{},[5939,9888,9889],{"align":5925},[5289,9890,9795],{},[5939,9892,9893,9894],{"align":5925},"🏆 ",[5220,9895,9800],{},[5939,9897,9893,9898,9806],{"align":5925},[5220,9899,9805],{},[5987,9901,9902,9907,9939,9944],{},[5268,9903,9904],{},[5220,9905,9906],{},"Переваги Mixed Precision:",[5194,9908,9909,9915,9921,9927],{},[5197,9910,8855,9911,9914],{},[5220,9912,9913],{},"Економія пам'яті:"," ~2× (можна збільшити batch size або модель)",[5197,9916,8855,9917,9920],{},[5220,9918,9919],{},"Прискорення:"," 1.5–3× на GPU з Tensor Cores",[5197,9922,8855,9923,9926],{},[5220,9924,9925],{},"Точність збережена:"," втрата точності мінімальна (~0.1%)",[5197,9928,8855,9929,9932,9933,6368,9936,5227],{},[5220,9930,9931],{},"Простота:"," додати 3 рядки коду (",[5289,9934,9935],{},"autocast",[5289,9937,9938],{},"GradScaler",[5268,9940,9941],{},[5220,9942,9943],{},"Недоліки:",[5194,9945,9946,9949,9952],{},[5197,9947,9948],{},"⚠️ Працює лише на NVIDIA GPU (від GTX 1660 \u002F RTX 2000)",[5197,9950,9951],{},"⚠️ Деякі операції не підтримують FP16 (рідко)",[5197,9953,9954],{},"⚠️ Можуть виникнути проблеми з нестабільністю (рідко, вирішується налаштуванням scaler)",[5333,9956],{},[5263,9958,9960],{"id":9959},"частина-3-оптимізація-продуктивності","Частина 3: Оптимізація продуктивності",[5340,9962,9964],{"id":9963},"профілювання-коду","Профілювання коду",[5268,9966,9967,9968,9971],{},"Перед оптимізацією потрібно знайти ",[5220,9969,9970],{},"bottleneck"," — найповільнішу частину коду.",[5484,9973,9975],{"title":9974},"profiling.ipynb",[5488,9976,9977,10294],{"execution-count":5490},[5492,9978,9980],{"className":5494,"code":9979,"language":5496,"meta":5497,"style":5497},"import torch\nimport time\n\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\nmodel = nn.Sequential(\n    nn.Linear(1000, 2000),\n    nn.ReLU(),\n    nn.Linear(2000, 1000)\n).to(device)\n\nX = torch.randn(128, 1000).to(device)\n\n# Простий профайлінг через time\ndef profile_function(func, name, iterations=100):\n    # Warmup\n    for _ in range(10):\n        func()\n    \n    if device.type == 'cuda':\n        torch.cuda.synchronize()\n    \n    start = time.time()\n    for _ in range(iterations):\n        func()\n    \n    if device.type == 'cuda':\n        torch.cuda.synchronize()\n    \n    elapsed = (time.time() - start) \u002F iterations\n    print(f\"{name}: {elapsed*1000:.3f} ms\")\n\n# Профілювання різних операцій\nprofile_function(lambda: model(X), \"Forward pass\")\nprofile_function(lambda: X @ X.T, \"Matrix multiplication\")\nprofile_function(lambda: torch.relu(X), \"ReLU activation\")\n",[5289,9981,9982,9988,9994,9998,10014,10018,10022,10034,10038,10050,10054,10058,10070,10074,10079,10109,10114,10131,10136,10140,10151,10156,10160,10164,10177,10181,10185,10195,10199,10203,10208,10241,10245,10250,10266,10280],{"__ignoreMap":5497},[5501,9983,9984,9986],{"class":5503,"line":5504},[5501,9985,5508],{"class":5507},[5501,9987,5512],{"class":5511},[5501,9989,9990,9992],{"class":5503,"line":5515},[5501,9991,5508],{"class":5507},[5501,9993,5520],{"class":5511},[5501,9995,9996],{"class":5503,"line":5523},[5501,9997,5527],{"emptyLinePlaceholder":5526},[5501,9999,10000,10002,10004,10006,10008,10010,10012],{"class":5503,"line":5530},[5501,10001,6743],{"class":5511},[5501,10003,6538],{"class":5618},[5501,10005,6748],{"class":5507},[5501,10007,6751],{"class":5511},[5501,10009,5890],{"class":5507},[5501,10011,6756],{"class":5618},[5501,10013,5622],{"class":5511},[5501,10015,10016],{"class":5503,"line":5537},[5501,10017,5527],{"emptyLinePlaceholder":5526},[5501,10019,10020],{"class":5503,"line":5547},[5501,10021,7525],{"class":5511},[5501,10023,10024,10026,10028,10030,10032],{"class":5503,"line":5552},[5501,10025,7530],{"class":5511},[5501,10027,7437],{"class":5543},[5501,10029,6368],{"class":5511},[5501,10031,8515],{"class":5543},[5501,10033,7539],{"class":5511},[5501,10035,10036],{"class":5503,"line":5558},[5501,10037,7544],{"class":5511},[5501,10039,10040,10042,10044,10046,10048],{"class":5503,"line":5564},[5501,10041,7530],{"class":5511},[5501,10043,8515],{"class":5543},[5501,10045,6368],{"class":5511},[5501,10047,7437],{"class":5543},[5501,10049,5622],{"class":5511},[5501,10051,10052],{"class":5503,"line":5570},[5501,10053,8554],{"class":5511},[5501,10055,10056],{"class":5503,"line":5575},[5501,10057,5527],{"emptyLinePlaceholder":5526},[5501,10059,10060,10062,10064,10066,10068],{"class":5503,"line":5581},[5501,10061,7241],{"class":5511},[5501,10063,8605],{"class":5543},[5501,10065,6368],{"class":5511},[5501,10067,7437],{"class":5543},[5501,10069,8554],{"class":5511},[5501,10071,10072],{"class":5503,"line":5587},[5501,10073,5527],{"emptyLinePlaceholder":5526},[5501,10075,10076],{"class":5503,"line":5593},[5501,10077,10078],{"class":5533},"# Простий профайлінг через time\n",[5501,10080,10081,10084,10087,10089,10092,10094,10097,10099,10102,10104,10107],{"class":5503,"line":5599},[5501,10082,10083],{"class":5614},"def",[5501,10085,10086],{"class":5607}," profile_function",[5501,10088,5611],{"class":5511},[5501,10090,10091],{"class":6847},"func",[5501,10093,6368],{"class":5511},[5501,10095,10096],{"class":6847},"name",[5501,10098,6368],{"class":5511},[5501,10100,10101],{"class":6847},"iterations",[5501,10103,7455],{"class":5511},[5501,10105,10106],{"class":5543},"100",[5501,10108,6834],{"class":5511},[5501,10110,10111],{"class":5503,"line":5604},[5501,10112,10113],{"class":5533},"    # Warmup\n",[5501,10115,10116,10118,10121,10123,10125,10127,10129],{"class":5503,"line":5625},[5501,10117,7677],{"class":5507},[5501,10119,10120],{"class":5511}," _ ",[5501,10122,7143],{"class":5507},[5501,10124,7652],{"class":5607},[5501,10126,5611],{"class":5511},[5501,10128,6875],{"class":5543},[5501,10130,6834],{"class":5511},[5501,10132,10133],{"class":5503,"line":5660},[5501,10134,10135],{"class":5511},"        func()\n",[5501,10137,10138],{"class":5503,"line":5691},[5501,10139,5732],{"class":5511},[5501,10141,10142,10144,10147,10149],{"class":5503,"line":5696},[5501,10143,8374],{"class":5507},[5501,10145,10146],{"class":5511}," device.type == ",[5501,10148,6538],{"class":5618},[5501,10150,5893],{"class":5511},[5501,10152,10153],{"class":5503,"line":5702},[5501,10154,10155],{"class":5511},"        torch.cuda.synchronize()\n",[5501,10157,10158],{"class":5503,"line":5711},[5501,10159,5732],{"class":5511},[5501,10161,10162],{"class":5503,"line":5717},[5501,10163,5767],{"class":5511},[5501,10165,10166,10168,10170,10172,10174],{"class":5503,"line":5723},[5501,10167,7677],{"class":5507},[5501,10169,10120],{"class":5511},[5501,10171,7143],{"class":5507},[5501,10173,7652],{"class":5607},[5501,10175,10176],{"class":5511},"(iterations):\n",[5501,10178,10179],{"class":5503,"line":5729},[5501,10180,10135],{"class":5511},[5501,10182,10183],{"class":5503,"line":5735},[5501,10184,5732],{"class":5511},[5501,10186,10187,10189,10191,10193],{"class":5503,"line":5741},[5501,10188,8374],{"class":5507},[5501,10190,10146],{"class":5511},[5501,10192,6538],{"class":5618},[5501,10194,5893],{"class":5511},[5501,10196,10197],{"class":5503,"line":5747},[5501,10198,10155],{"class":5511},[5501,10200,10201],{"class":5503,"line":5753},[5501,10202,5732],{"class":5511},[5501,10204,10205],{"class":5503,"line":5758},[5501,10206,10207],{"class":5511},"    elapsed = (time.time() - start) \u002F iterations\n",[5501,10209,10210,10212,10214,10216,10218,10220,10222,10224,10227,10229,10232,10234,10236,10239],{"class":5503,"line":5764},[5501,10211,5799],{"class":5607},[5501,10213,5611],{"class":5511},[5501,10215,5615],{"class":5614},[5501,10217,5655],{"class":5618},[5501,10219,5637],{"class":5614},[5501,10221,10096],{"class":5511},[5501,10223,5643],{"class":5614},[5501,10225,10226],{"class":5618},": ",[5501,10228,5637],{"class":5614},[5501,10230,10231],{"class":5511},"elapsed*",[5501,10233,7437],{"class":5543},[5501,10235,5677],{"class":5614},[5501,10237,10238],{"class":5618}," ms\"",[5501,10240,5622],{"class":5511},[5501,10242,10243],{"class":5503,"line":5770},[5501,10244,5527],{"emptyLinePlaceholder":5526},[5501,10246,10247],{"class":5503,"line":5776},[5501,10248,10249],{"class":5533},"# Профілювання різних операцій\n",[5501,10251,10252,10255,10258,10261,10264],{"class":5503,"line":5785},[5501,10253,10254],{"class":5511},"profile_function(",[5501,10256,10257],{"class":5614},"lambda",[5501,10259,10260],{"class":5511},": model(X), ",[5501,10262,10263],{"class":5618},"\"Forward pass\"",[5501,10265,5622],{"class":5511},[5501,10267,10268,10270,10272,10275,10278],{"class":5503,"line":5791},[5501,10269,10254],{"class":5511},[5501,10271,10257],{"class":5614},[5501,10273,10274],{"class":5511},": X @ X.T, ",[5501,10276,10277],{"class":5618},"\"Matrix multiplication\"",[5501,10279,5622],{"class":5511},[5501,10281,10282,10284,10286,10289,10292],{"class":5503,"line":5796},[5501,10283,10254],{"class":5511},[5501,10285,10257],{"class":5614},[5501,10287,10288],{"class":5511},": torch.relu(X), ",[5501,10290,10291],{"class":5618},"\"ReLU activation\"",[5501,10293,5622],{"class":5511},[5907,10295,10296],{"v-slot:output":5497},[5910,10297,10298,10311],{},[5913,10299,10300],{},[5916,10301,10302,10305,10308],{},[5919,10303,10304],{"align":5921},"Операція в циклі",[5919,10306,10307],{"align":5925},"Час виконання",[5919,10309,10310],{"align":5925},"Частка від загального часу",[5934,10312,10313,10328,10343,10358],{},[5916,10314,10315,10320,10325],{},[5939,10316,10317],{"align":5921},[5220,10318,10319],{},"Forward pass",[5939,10321,10322],{"align":5925},[5289,10323,10324],{},"0.234 ms",[5939,10326,10327],{"align":5925},"$42.5%$",[5916,10329,10330,10335,10340],{},[5939,10331,10332],{"align":5921},[5220,10333,10334],{},"Matrix multiplication",[5939,10336,10337],{"align":5925},[5289,10338,10339],{},"0.156 ms",[5939,10341,10342],{"align":5925},"$28.4%$",[5916,10344,10345,10350,10355],{},[5939,10346,10347],{"align":5921},[5220,10348,10349],{},"ReLU activation",[5939,10351,10352],{"align":5925},[5289,10353,10354],{},"0.045 ms",[5939,10356,10357],{"align":5925},"$8.2%$",[5916,10359,10360,10365,10370],{},[5939,10361,10362],{"align":5921},[5220,10363,10364],{},"Backward pass",[5939,10366,10367],{"align":5925},[5289,10368,10369],{},"0.312 ms",[5939,10371,10372],{"align":5925},"$56.7%$",[6770,10374,10376],{"id":10375},"pytorch-profiler-детальний-аналіз","PyTorch Profiler (детальний аналіз)",[5484,10378,10380],{"title":10379},"pytorch_profiler.ipynb",[5488,10381,10382,10546],{"execution-count":5490},[5492,10383,10385],{"className":5494,"code":10384,"language":5496,"meta":5497,"style":5497},"import torch\nfrom torch.profiler import profile, ProfilerActivity\n\nmodel = nn.Sequential(\n    nn.Linear(100, 200),\n    nn.ReLU(),\n    nn.Linear(200, 10)\n).to(device)\n\nX = torch.randn(32, 100).to(device)\n\n# Профілювання з детальними метриками\nwith profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof:\n    for _ in range(10):\n        output = model(X)\n\n# Топ-5 найповільніших операцій\nprint(prof.key_averages().table(sort_by=\"cuda_time_total\", row_limit=5))\n",[5289,10386,10387,10393,10405,10409,10413,10426,10430,10442,10446,10450,10462,10466,10471,10489,10505,10510,10514,10519],{"__ignoreMap":5497},[5501,10388,10389,10391],{"class":5503,"line":5504},[5501,10390,5508],{"class":5507},[5501,10392,5512],{"class":5511},[5501,10394,10395,10397,10400,10402],{"class":5503,"line":5515},[5501,10396,7354],{"class":5507},[5501,10398,10399],{"class":5511}," torch.profiler ",[5501,10401,5508],{"class":5507},[5501,10403,10404],{"class":5511}," profile, ProfilerActivity\n",[5501,10406,10407],{"class":5503,"line":5523},[5501,10408,5527],{"emptyLinePlaceholder":5526},[5501,10410,10411],{"class":5503,"line":5530},[5501,10412,7525],{"class":5511},[5501,10414,10415,10417,10419,10421,10424],{"class":5503,"line":5537},[5501,10416,7530],{"class":5511},[5501,10418,10106],{"class":5543},[5501,10420,6368],{"class":5511},[5501,10422,10423],{"class":5543},"200",[5501,10425,7539],{"class":5511},[5501,10427,10428],{"class":5503,"line":5547},[5501,10429,7544],{"class":5511},[5501,10431,10432,10434,10436,10438,10440],{"class":5503,"line":5552},[5501,10433,7530],{"class":5511},[5501,10435,10423],{"class":5543},[5501,10437,6368],{"class":5511},[5501,10439,6875],{"class":5543},[5501,10441,5622],{"class":5511},[5501,10443,10444],{"class":5503,"line":5558},[5501,10445,8554],{"class":5511},[5501,10447,10448],{"class":5503,"line":5564},[5501,10449,5527],{"emptyLinePlaceholder":5526},[5501,10451,10452,10454,10456,10458,10460],{"class":5503,"line":5570},[5501,10453,7241],{"class":5511},[5501,10455,6896],{"class":5543},[5501,10457,6368],{"class":5511},[5501,10459,10106],{"class":5543},[5501,10461,8554],{"class":5511},[5501,10463,10464],{"class":5503,"line":5575},[5501,10465,5527],{"emptyLinePlaceholder":5526},[5501,10467,10468],{"class":5503,"line":5581},[5501,10469,10470],{"class":5533},"# Профілювання з детальними метриками\n",[5501,10472,10473,10475,10478,10481,10484,10486],{"class":5503,"line":5587},[5501,10474,8717],{"class":5507},[5501,10476,10477],{"class":5511}," profile(",[5501,10479,10480],{"class":6847},"activities",[5501,10482,10483],{"class":5511},"=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) ",[5501,10485,6799],{"class":5507},[5501,10487,10488],{"class":5511}," prof:\n",[5501,10490,10491,10493,10495,10497,10499,10501,10503],{"class":5503,"line":5593},[5501,10492,7677],{"class":5507},[5501,10494,10120],{"class":5511},[5501,10496,7143],{"class":5507},[5501,10498,7652],{"class":5607},[5501,10500,5611],{"class":5511},[5501,10502,6875],{"class":5543},[5501,10504,6834],{"class":5511},[5501,10506,10507],{"class":5503,"line":5599},[5501,10508,10509],{"class":5511},"        output = model(X)\n",[5501,10511,10512],{"class":5503,"line":5604},[5501,10513,5527],{"emptyLinePlaceholder":5526},[5501,10515,10516],{"class":5503,"line":5625},[5501,10517,10518],{"class":5533},"# Топ-5 найповільніших операцій\n",[5501,10520,10521,10523,10526,10529,10531,10534,10536,10539,10541,10543],{"class":5503,"line":5660},[5501,10522,5608],{"class":5607},[5501,10524,10525],{"class":5511},"(prof.key_averages().table(",[5501,10527,10528],{"class":6847},"sort_by",[5501,10530,7455],{"class":5511},[5501,10532,10533],{"class":5618},"\"cuda_time_total\"",[5501,10535,6368],{"class":5511},[5501,10537,10538],{"class":6847},"row_limit",[5501,10540,7455],{"class":5511},[5501,10542,7244],{"class":5543},[5501,10544,10545],{"class":5511},"))\n",[5907,10547,10548],{"v-slot:output":5497},[5910,10549,10550,10575],{},[5913,10551,10552],{},[5916,10553,10554,10560,10563,10566,10569,10572],{},[5919,10555,10556,10557,5227],{"align":5921},"Назва операції (",[5289,10558,10559],{},"Name",[5919,10561,10562],{"align":5925},"CPU Time (%)",[5919,10564,10565],{"align":5925},"CPU Total",[5919,10567,10568],{"align":5925},"CUDA Time (%)",[5919,10570,10571],{"align":5925},"CUDA Total",[5919,10573,10574],{"align":5925},"Кількість викликів",[5934,10576,10577,10603,10629,10655],{},[5916,10578,10579,10585,10588,10593,10596,10601],{},[5939,10580,10581,10584],{"align":5921},[5289,10582,10583],{},"aten::mm"," (Matrix Multiply)",[5939,10586,10587],{"align":5925},"$32.4%$",[5939,10589,10590],{"align":5925},[5289,10591,10592],{},"1.245 ms",[5939,10594,10595],{"align":5925},"$58.2%$",[5939,10597,10598],{"align":5925},[5289,10599,10600],{},"0.450 ms",[5939,10602,6875],{"align":5925},[5916,10604,10605,10611,10614,10619,10622,10627],{},[5939,10606,10607,10610],{"align":5921},[5289,10608,10609],{},"aten::add"," (Vector Add)",[5939,10612,10613],{"align":5925},"$12.1%$",[5939,10615,10616],{"align":5925},[5289,10617,10618],{},"0.465 ms",[5939,10620,10621],{"align":5925},"$14.3%$",[5939,10623,10624],{"align":5925},[5289,10625,10626],{},"0.110 ms",[5939,10628,6875],{"align":5925},[5916,10630,10631,10637,10640,10645,10648,10653],{},[5939,10632,10633,10636],{"align":5921},[5289,10634,10635],{},"aten::relu"," (Activation)",[5939,10638,10639],{"align":5925},"$8.5%$",[5939,10641,10642],{"align":5925},[5289,10643,10644],{},"0.326 ms",[5939,10646,10647],{"align":5925},"$9.8%$",[5939,10649,10650],{"align":5925},[5289,10651,10652],{},"0.076 ms",[5939,10654,6875],{"align":5925},[5916,10656,10657,10663,10666,10671,10674,10679],{},[5939,10658,10659,10662],{"align":5921},[5289,10660,10661],{},"aten::linear"," (Full Layer)",[5939,10664,10665],{"align":5925},"$47.0%$",[5939,10667,10668],{"align":5925},[5289,10669,10670],{},"1.805 ms",[5939,10672,10673],{"align":5925},"$17.7%$",[5939,10675,10676],{"align":5925},[5289,10677,10678],{},"0.137 ms",[5939,10680,7244],{"align":5925},[5340,10682,10684],{"id":10683},"оптимізація-dataloader","Оптимізація DataLoader",[5484,10686,10688],{"title":10687},"dataloader_optimization.ipynb",[5488,10689,10690,11139],{"execution-count":5490},[5492,10691,10693],{"className":5494,"code":10692,"language":5496,"meta":5497,"style":5497},"from torch.utils.data import TensorDataset, DataLoader\nimport time\n\n# Датасет\nX_train = torch.randn(10000, 100)\ny_train = torch.randint(0, 2, (10000,))\ndataset = TensorDataset(X_train, y_train)\n\n# Тестуємо різні налаштування\ndef benchmark_dataloader(num_workers, pin_memory):\n    loader = DataLoader(\n        dataset,\n        batch_size=128,\n        shuffle=True,\n        num_workers=num_workers,\n        pin_memory=pin_memory\n    )\n    \n    start = time.time()\n    for _ in range(3):  # 3 епохи\n        for batch_X, batch_y in loader:\n            if torch.cuda.is_available():\n                batch_X = batch_X.cuda()\n                batch_y = batch_y.cuda()\n    elapsed = time.time() - start\n    \n    return elapsed\n\nprint(\"Оптимізація DataLoader:\\n\")\nresults = []\n\nfor num_workers in [0, 2, 4, 8]:\n    for pin_memory in [False, True]:\n        time_taken = benchmark_dataloader(num_workers, pin_memory)\n        results.append((num_workers, pin_memory, time_taken))\n        print(f\"num_workers={num_workers}, pin_memory={pin_memory}: {time_taken:.3f} сек\")\n\n# Знаходимо оптимальні налаштування\nbest = min(results, key=lambda x: x[2])\nprint(f\"\\nОптимальні налаштування:\")\nprint(f\"  num_workers={best[0]}, pin_memory={best[1]}, час={best[2]:.3f} сек\")\n",[5289,10694,10695,10705,10711,10715,10720,10732,10748,10753,10757,10762,10780,10785,10790,10801,10812,10820,10828,10833,10837,10841,10861,10873,10880,10885,10890,10895,10899,10907,10911,10926,10931,10935,10965,10985,10990,10995,11034,11038,11043,11071,11088],{"__ignoreMap":5497},[5501,10696,10697,10699,10701,10703],{"class":5503,"line":5504},[5501,10698,7354],{"class":5507},[5501,10700,7357],{"class":5511},[5501,10702,5508],{"class":5507},[5501,10704,7362],{"class":5511},[5501,10706,10707,10709],{"class":5503,"line":5515},[5501,10708,5508],{"class":5507},[5501,10710,5520],{"class":5511},[5501,10712,10713],{"class":5503,"line":5523},[5501,10714,5527],{"emptyLinePlaceholder":5526},[5501,10716,10717],{"class":5503,"line":5530},[5501,10718,10719],{"class":5533},"# Датасет\n",[5501,10721,10722,10724,10726,10728,10730],{"class":5503,"line":5537},[5501,10723,7434],{"class":5511},[5501,10725,9185],{"class":5543},[5501,10727,6368],{"class":5511},[5501,10729,10106],{"class":5543},[5501,10731,5622],{"class":5511},[5501,10733,10734,10736,10738,10740,10742,10744,10746],{"class":5503,"line":5547},[5501,10735,9197],{"class":5511},[5501,10737,5828],{"class":5543},[5501,10739,6368],{"class":5511},[5501,10741,6347],{"class":5543},[5501,10743,8625],{"class":5511},[5501,10745,9185],{"class":5543},[5501,10747,9210],{"class":5511},[5501,10749,10750],{"class":5503,"line":5552},[5501,10751,10752],{"class":5511},"dataset = TensorDataset(X_train, y_train)\n",[5501,10754,10755],{"class":5503,"line":5558},[5501,10756,5527],{"emptyLinePlaceholder":5526},[5501,10758,10759],{"class":5503,"line":5564},[5501,10760,10761],{"class":5533},"# Тестуємо різні налаштування\n",[5501,10763,10764,10766,10769,10771,10774,10776,10778],{"class":5503,"line":5570},[5501,10765,10083],{"class":5614},[5501,10767,10768],{"class":5607}," benchmark_dataloader",[5501,10770,5611],{"class":5511},[5501,10772,10773],{"class":6847},"num_workers",[5501,10775,6368],{"class":5511},[5501,10777,9242],{"class":6847},[5501,10779,6834],{"class":5511},[5501,10781,10782],{"class":5503,"line":5575},[5501,10783,10784],{"class":5511},"    loader = DataLoader(\n",[5501,10786,10787],{"class":5503,"line":5581},[5501,10788,10789],{"class":5511},"        dataset,\n",[5501,10791,10792,10795,10797,10799],{"class":5503,"line":5587},[5501,10793,10794],{"class":6847},"        batch_size",[5501,10796,7455],{"class":5511},[5501,10798,8605],{"class":5543},[5501,10800,8003],{"class":5511},[5501,10802,10803,10806,10808,10810],{"class":5503,"line":5593},[5501,10804,10805],{"class":6847},"        shuffle",[5501,10807,7455],{"class":5511},[5501,10809,6279],{"class":5614},[5501,10811,8003],{"class":5511},[5501,10813,10814,10817],{"class":5503,"line":5599},[5501,10815,10816],{"class":6847},"        num_workers",[5501,10818,10819],{"class":5511},"=num_workers,\n",[5501,10821,10822,10825],{"class":5503,"line":5604},[5501,10823,10824],{"class":6847},"        pin_memory",[5501,10826,10827],{"class":5511},"=pin_memory\n",[5501,10829,10830],{"class":5503,"line":5625},[5501,10831,10832],{"class":5511},"    )\n",[5501,10834,10835],{"class":5503,"line":5660},[5501,10836,5732],{"class":5511},[5501,10838,10839],{"class":5503,"line":5691},[5501,10840,5767],{"class":5511},[5501,10842,10843,10845,10847,10849,10851,10853,10855,10858],{"class":5503,"line":5696},[5501,10844,7677],{"class":5507},[5501,10846,10120],{"class":5511},[5501,10848,7143],{"class":5507},[5501,10850,7652],{"class":5607},[5501,10852,5611],{"class":5511},[5501,10854,6222],{"class":5543},[5501,10856,10857],{"class":5511},"):  ",[5501,10859,10860],{"class":5533},"# 3 епохи\n",[5501,10862,10863,10866,10868,10870],{"class":5503,"line":5702},[5501,10864,10865],{"class":5507},"        for",[5501,10867,7680],{"class":5511},[5501,10869,7143],{"class":5507},[5501,10871,10872],{"class":5511}," loader:\n",[5501,10874,10875,10878],{"class":5503,"line":5711},[5501,10876,10877],{"class":5507},"            if",[5501,10879,5708],{"class":5511},[5501,10881,10882],{"class":5503,"line":5717},[5501,10883,10884],{"class":5511},"                batch_X = batch_X.cuda()\n",[5501,10886,10887],{"class":5503,"line":5723},[5501,10888,10889],{"class":5511},"                batch_y = batch_y.cuda()\n",[5501,10891,10892],{"class":5503,"line":5729},[5501,10893,10894],{"class":5511},"    elapsed = time.time() - start\n",[5501,10896,10897],{"class":5503,"line":5735},[5501,10898,5732],{"class":5511},[5501,10900,10901,10904],{"class":5503,"line":5741},[5501,10902,10903],{"class":5507},"    return",[5501,10905,10906],{"class":5511}," elapsed\n",[5501,10908,10909],{"class":5503,"line":5747},[5501,10910,5527],{"emptyLinePlaceholder":5526},[5501,10912,10913,10915,10917,10920,10922,10924],{"class":5503,"line":5753},[5501,10914,5608],{"class":5607},[5501,10916,5611],{"class":5511},[5501,10918,10919],{"class":5618},"\"Оптимізація DataLoader:",[5501,10921,5684],{"class":5683},[5501,10923,5655],{"class":5618},[5501,10925,5622],{"class":5511},[5501,10927,10928],{"class":5503,"line":5758},[5501,10929,10930],{"class":5511},"results = []\n",[5501,10932,10933],{"class":5503,"line":5764},[5501,10934,5527],{"emptyLinePlaceholder":5526},[5501,10936,10937,10939,10942,10944,10947,10949,10951,10953,10955,10957,10959,10962],{"class":5503,"line":5770},[5501,10938,7137],{"class":5507},[5501,10940,10941],{"class":5511}," num_workers ",[5501,10943,7143],{"class":5507},[5501,10945,10946],{"class":5511}," [",[5501,10948,5828],{"class":5543},[5501,10950,6368],{"class":5511},[5501,10952,6347],{"class":5543},[5501,10954,6368],{"class":5511},[5501,10956,8039],{"class":5543},[5501,10958,6368],{"class":5511},[5501,10960,10961],{"class":5543},"8",[5501,10963,10964],{"class":5511},"]:\n",[5501,10966,10967,10969,10972,10974,10976,10979,10981,10983],{"class":5503,"line":5776},[5501,10968,7677],{"class":5507},[5501,10970,10971],{"class":5511}," pin_memory ",[5501,10973,7143],{"class":5507},[5501,10975,10946],{"class":5511},[5501,10977,10978],{"class":5614},"False",[5501,10980,6368],{"class":5511},[5501,10982,6279],{"class":5614},[5501,10984,10964],{"class":5511},[5501,10986,10987],{"class":5503,"line":5785},[5501,10988,10989],{"class":5511},"        time_taken = benchmark_dataloader(num_workers, pin_memory)\n",[5501,10991,10992],{"class":5503,"line":5791},[5501,10993,10994],{"class":5511},"        results.append((num_workers, pin_memory, time_taken))\n",[5501,10996,10997,10999,11001,11003,11006,11008,11010,11012,11015,11017,11019,11021,11023,11025,11028,11030,11032],{"class":5503,"line":5796},[5501,10998,8392],{"class":5607},[5501,11000,5611],{"class":5511},[5501,11002,5615],{"class":5614},[5501,11004,11005],{"class":5618},"\"num_workers=",[5501,11007,5637],{"class":5614},[5501,11009,10773],{"class":5511},[5501,11011,5643],{"class":5614},[5501,11013,11014],{"class":5618},", pin_memory=",[5501,11016,5637],{"class":5614},[5501,11018,9242],{"class":5511},[5501,11020,5643],{"class":5614},[5501,11022,10226],{"class":5618},[5501,11024,5637],{"class":5614},[5501,11026,11027],{"class":5511},"time_taken",[5501,11029,5677],{"class":5614},[5501,11031,5857],{"class":5618},[5501,11033,5622],{"class":5511},[5501,11035,11036],{"class":5503,"line":5811},[5501,11037,5527],{"emptyLinePlaceholder":5526},[5501,11039,11040],{"class":5503,"line":5839},[5501,11041,11042],{"class":5533},"# Знаходимо оптимальні налаштування\n",[5501,11044,11045,11048,11051,11054,11057,11059,11061,11064,11067,11069],{"class":5503,"line":5862},[5501,11046,11047],{"class":5511},"best = ",[5501,11049,11050],{"class":5607},"min",[5501,11052,11053],{"class":5511},"(results, ",[5501,11055,11056],{"class":6847},"key",[5501,11058,7455],{"class":5511},[5501,11060,10257],{"class":5614},[5501,11062,11063],{"class":6847}," x",[5501,11065,11066],{"class":5511},": x[",[5501,11068,6347],{"class":5543},[5501,11070,6379],{"class":5511},[5501,11072,11073,11075,11077,11079,11081,11083,11086],{"class":5503,"line":5887},[5501,11074,5608],{"class":5607},[5501,11076,5611],{"class":5511},[5501,11078,5615],{"class":5614},[5501,11080,5655],{"class":5618},[5501,11082,5684],{"class":5683},[5501,11084,11085],{"class":5618},"Оптимальні налаштування:\"",[5501,11087,5622],{"class":5511},[5501,11089,11090,11092,11094,11096,11099,11101,11104,11106,11108,11110,11112,11114,11116,11118,11120,11122,11125,11127,11129,11131,11133,11135,11137],{"class":5503,"line":5896},[5501,11091,5608],{"class":5607},[5501,11093,5611],{"class":5511},[5501,11095,5615],{"class":5614},[5501,11097,11098],{"class":5618},"\"  num_workers=",[5501,11100,5637],{"class":5614},[5501,11102,11103],{"class":5511},"best[",[5501,11105,5828],{"class":5543},[5501,11107,8347],{"class":5511},[5501,11109,5643],{"class":5614},[5501,11111,11014],{"class":5618},[5501,11113,5637],{"class":5614},[5501,11115,11103],{"class":5511},[5501,11117,5490],{"class":5543},[5501,11119,8347],{"class":5511},[5501,11121,5643],{"class":5614},[5501,11123,11124],{"class":5618},", час=",[5501,11126,5637],{"class":5614},[5501,11128,11103],{"class":5511},[5501,11130,6347],{"class":5543},[5501,11132,8347],{"class":5511},[5501,11134,5677],{"class":5614},[5501,11136,5857],{"class":5618},[5501,11138,5622],{"class":5511},[5907,11140,11141],{"v-slot:output":5497},[5910,11142,11143,11162],{},[5913,11144,11145],{},[5916,11146,11147,11150,11153,11156,11159],{},[5919,11148,11149],{"align":5921},"Конфігурація DataLoader",[5919,11151,11152],{"align":5921},"Параметри",[5919,11154,11155],{"align":5925},"Час епохи (с)",[5919,11157,11158],{"align":5925},"Прискорення",[5919,11160,11161],{"align":5925},"Завантаження GPU",[5934,11163,11164,11187,11210],{},[5916,11165,11166,11171,11176,11181,11184],{},[5939,11167,11168],{"align":5921},[5220,11169,11170],{},"Базова (CPU дебаг)",[5939,11172,11173],{"align":5921},[5289,11174,11175],{},"num_workers=0, pin_memory=False",[5939,11177,11178,5951],{"align":5925},[5289,11179,11180],{},"2.845",[5939,11182,11183],{"align":5925},"$1.0\\times$",[5939,11185,11186],{"align":5925},"$45%$ (GPU простоює)",[5916,11188,11189,11194,11199,11204,11207],{},[5939,11190,11191],{"align":5921},[5220,11192,11193],{},"З асинхронним завантаженням",[5939,11195,11196],{"align":5921},[5289,11197,11198],{},"num_workers=4, pin_memory=False",[5939,11200,11201,5951],{"align":5925},[5289,11202,11203],{},"1.120",[5939,11205,11206],{"align":5925},"$2.5\\times$",[5939,11208,11209],{"align":5925},"$78%$",[5916,11211,11212,11217,11222,11229,11234],{},[5939,11213,11214],{"align":5921},[5220,11215,11216],{},"Оптимальна (Production)",[5939,11218,11219],{"align":5921},[5289,11220,11221],{},"num_workers=4, pin_memory=True",[5939,11223,11224],{"align":5925},[5220,11225,11226,5951],{},[5289,11227,11228],{},"0.845",[5939,11230,5973,11231],{"align":5925},[5220,11232,11233],{},"$3.4\\times$ швидше",[5939,11235,11236,11239],{"align":5925},[5220,11237,11238],{},"$96%$"," (максимальна утилізація)",[5987,11241,11242,11247,11306],{},[5268,11243,11244],{},[5220,11245,11246],{},"Рекомендації для DataLoader:",[5910,11248,11249,11259],{},[5913,11250,11251],{},[5916,11252,11253,11256],{},[5919,11254,11255],{"align":5921},"Параметр",[5919,11257,11258],{"align":5921},"Оптимальне значення",[5934,11260,11261,11270,11284,11294],{},[5916,11262,11263,11267],{},[5939,11264,11265],{"align":5921},[5289,11266,10773],{},[5939,11268,11269],{"align":5921},"4-8 (залежить від CPU)",[5916,11271,11272,11276],{},[5939,11273,11274],{"align":5921},[5289,11275,9242],{},[5939,11277,11278,11280,11281,11283],{"align":5921},[5289,11279,6279],{}," для GPU, ",[5289,11282,10978],{}," для CPU",[5916,11285,11286,11291],{},[5939,11287,11288],{"align":5921},[5289,11289,11290],{},"prefetch_factor",[5939,11292,11293],{"align":5921},"2-4 (завантажує батчі наперед)",[5916,11295,11296,11301],{},[5939,11297,11298],{"align":5921},[5289,11299,11300],{},"persistent_workers",[5939,11302,11303,11305],{"align":5921},[5289,11304,6279],{}," для довгих тренувань (економить час створення процесів)",[5268,11307,11308,11311,11312,11315,11316,6828],{},[5220,11309,11310],{},"Важливо:"," На Windows ",[5289,11313,11314],{},"num_workers > 0"," може викликати проблеми. Якщо помилки — встановіть ",[5289,11317,11318],{},"num_workers=0",[5333,11320],{},[5263,11322,11324],{"id":11323},"частина-4-збереження-та-завантаження-моделей","Частина 4: Збереження та завантаження моделей",[5340,11326,11328],{"id":11327},"два-способи-збереження-state_dict-vs-повна-модель","Два способи збереження: state_dict vs повна модель",[5268,11330,11331],{},"PyTorch пропонує два підходи до збереження моделей, але лише один рекомендується для production.",[6770,11333,11335],{"id":11334},"спосіб-1-state-dict-рекомендовано","Спосіб 1: State Dict (✅ РЕКОМЕНДОВАНО)",[5268,11337,11338,11341,11342,11345],{},[5220,11339,11340],{},"State dict"," — це Python-словник, що містить усі параметри моделі (ваги та зміщення). Це ",[5220,11343,11344],{},"лише дані",", без архітектури моделі.",[5484,11347,11349,11710],{"title":11348},"save_state_dict.ipynb",[5488,11350,11351,11606],{"execution-count":5490},[5492,11352,11354],{"className":5494,"code":11353,"language":5496,"meta":5497,"style":5497},"import torch\nimport torch.nn as nn\n\n# Визначаємо модель\nclass MyModel(nn.Module):\n    def __init__(self, input_size, hidden_size, output_size):\n        super().__init__()\n        self.fc1 = nn.Linear(input_size, hidden_size)\n        self.fc2 = nn.Linear(hidden_size, output_size)\n    \n    def forward(self, x):\n        x = torch.relu(self.fc1(x))\n        x = self.fc2(x)\n        return x\n\n# Створюємо та тренуємо модель\nmodel = MyModel(input_size=10, hidden_size=20, output_size=3)\nprint(\"Модель створено\\n\")\n\n# Переглядаємо state_dict\nprint(\"State dict містить:\")\nfor name, param in model.state_dict().items():\n    print(f\"  {name}: {param.shape}\")\n",[5289,11355,11356,11362,11372,11376,11380,11397,11424,11434,11441,11448,11452,11468,11476,11485,11491,11495,11500,11529,11544,11548,11553,11564,11576],{"__ignoreMap":5497},[5501,11357,11358,11360],{"class":5503,"line":5504},[5501,11359,5508],{"class":5507},[5501,11361,5512],{"class":5511},[5501,11363,11364,11366,11368,11370],{"class":5503,"line":5515},[5501,11365,5508],{"class":5507},[5501,11367,6796],{"class":5511},[5501,11369,6799],{"class":5507},[5501,11371,6802],{"class":5511},[5501,11373,11374],{"class":5503,"line":5523},[5501,11375,5527],{"emptyLinePlaceholder":5526},[5501,11377,11378],{"class":5503,"line":5530},[5501,11379,6811],{"class":5533},[5501,11381,11382,11384,11387,11389,11391,11393,11395],{"class":5503,"line":5537},[5501,11383,6816],{"class":5614},[5501,11385,11386],{"class":6819}," MyModel",[5501,11388,5611],{"class":5511},[5501,11390,6825],{"class":6819},[5501,11392,6828],{"class":5511},[5501,11394,6831],{"class":6819},[5501,11396,6834],{"class":5511},[5501,11398,11399,11401,11403,11405,11407,11409,11412,11414,11417,11419,11422],{"class":5503,"line":5547},[5501,11400,6839],{"class":5614},[5501,11402,6842],{"class":5607},[5501,11404,5611],{"class":5511},[5501,11406,6848],{"class":6847},[5501,11408,6368],{"class":5511},[5501,11410,11411],{"class":6847},"input_size",[5501,11413,6368],{"class":5511},[5501,11415,11416],{"class":6847},"hidden_size",[5501,11418,6368],{"class":5511},[5501,11420,11421],{"class":6847},"output_size",[5501,11423,6834],{"class":5511},[5501,11425,11426,11428,11430,11432],{"class":5503,"line":5552},[5501,11427,6855],{"class":6819},[5501,11429,6858],{"class":5511},[5501,11431,6861],{"class":5607},[5501,11433,6864],{"class":5511},[5501,11435,11436,11438],{"class":5503,"line":5558},[5501,11437,6869],{"class":5614},[5501,11439,11440],{"class":5511},".fc1 = nn.Linear(input_size, hidden_size)\n",[5501,11442,11443,11445],{"class":5503,"line":5564},[5501,11444,6869],{"class":5614},[5501,11446,11447],{"class":5511},".fc2 = nn.Linear(hidden_size, output_size)\n",[5501,11449,11450],{"class":5503,"line":5570},[5501,11451,5732],{"class":5511},[5501,11453,11454,11456,11458,11460,11462,11464,11466],{"class":5503,"line":5575},[5501,11455,6839],{"class":5614},[5501,11457,6924],{"class":5607},[5501,11459,5611],{"class":5511},[5501,11461,6848],{"class":6847},[5501,11463,6368],{"class":5511},[5501,11465,6933],{"class":6847},[5501,11467,6834],{"class":5511},[5501,11469,11470,11472,11474],{"class":5503,"line":5581},[5501,11471,6940],{"class":5511},[5501,11473,6848],{"class":5614},[5501,11475,6945],{"class":5511},[5501,11477,11478,11480,11482],{"class":5503,"line":5587},[5501,11479,6959],{"class":5511},[5501,11481,6848],{"class":5614},[5501,11483,11484],{"class":5511},".fc2(x)\n",[5501,11486,11487,11489],{"class":5503,"line":5593},[5501,11488,6969],{"class":5507},[5501,11490,6972],{"class":5511},[5501,11492,11493],{"class":5503,"line":5599},[5501,11494,5527],{"emptyLinePlaceholder":5526},[5501,11496,11497],{"class":5503,"line":5604},[5501,11498,11499],{"class":5533},"# Створюємо та тренуємо модель\n",[5501,11501,11502,11505,11507,11509,11511,11513,11515,11517,11519,11521,11523,11525,11527],{"class":5503,"line":5625},[5501,11503,11504],{"class":5511},"model = MyModel(",[5501,11506,11411],{"class":6847},[5501,11508,7455],{"class":5511},[5501,11510,6875],{"class":5543},[5501,11512,6368],{"class":5511},[5501,11514,11416],{"class":6847},[5501,11516,7455],{"class":5511},[5501,11518,7442],{"class":5543},[5501,11520,6368],{"class":5511},[5501,11522,11421],{"class":6847},[5501,11524,7455],{"class":5511},[5501,11526,6222],{"class":5543},[5501,11528,5622],{"class":5511},[5501,11530,11531,11533,11535,11538,11540,11542],{"class":5503,"line":5660},[5501,11532,5608],{"class":5607},[5501,11534,5611],{"class":5511},[5501,11536,11537],{"class":5618},"\"Модель створено",[5501,11539,5684],{"class":5683},[5501,11541,5655],{"class":5618},[5501,11543,5622],{"class":5511},[5501,11545,11546],{"class":5503,"line":5691},[5501,11547,5527],{"emptyLinePlaceholder":5526},[5501,11549,11550],{"class":5503,"line":5696},[5501,11551,11552],{"class":5533},"# Переглядаємо state_dict\n",[5501,11554,11555,11557,11559,11562],{"class":5503,"line":5702},[5501,11556,5608],{"class":5607},[5501,11558,5611],{"class":5511},[5501,11560,11561],{"class":5618},"\"State dict містить:\"",[5501,11563,5622],{"class":5511},[5501,11565,11566,11568,11571,11573],{"class":5503,"line":5711},[5501,11567,7137],{"class":5507},[5501,11569,11570],{"class":5511}," name, param ",[5501,11572,7143],{"class":5507},[5501,11574,11575],{"class":5511}," model.state_dict().items():\n",[5501,11577,11578,11580,11582,11584,11587,11589,11591,11593,11595,11597,11600,11602,11604],{"class":5503,"line":5717},[5501,11579,5799],{"class":5607},[5501,11581,5611],{"class":5511},[5501,11583,5615],{"class":5614},[5501,11585,11586],{"class":5618},"\"  ",[5501,11588,5637],{"class":5614},[5501,11590,10096],{"class":5511},[5501,11592,5643],{"class":5614},[5501,11594,10226],{"class":5618},[5501,11596,5637],{"class":5614},[5501,11598,11599],{"class":5511},"param.shape",[5501,11601,5643],{"class":5614},[5501,11603,5655],{"class":5618},[5501,11605,5622],{"class":5511},[5907,11607,11608],{"v-slot:output":5497},[5910,11609,11610,11629],{},[5913,11611,11612],{},[5916,11613,11614,11617,11623,11626],{},[5919,11615,11616],{"align":5921},"Шар архітектури",[5919,11618,11619,11620],{"align":5921},"Ключ у ",[5289,11621,11622],{},"state_dict",[5919,11624,11625],{"align":5925},"Розмірність тензора",[5919,11627,11628],{"align":5925},"Тип даних",[5934,11630,11631,11653,11671,11692],{},[5916,11632,11633,11638,11643,11648],{},[5939,11634,11635],{"align":5921},[5220,11636,11637],{},"Вхідний шар",[5939,11639,11640],{"align":5921},[5289,11641,11642],{},"'fc1.weight'",[5939,11644,11645],{"align":5925},[5289,11646,11647],{},"torch.Size([64, 10])",[5939,11649,11650],{"align":5925},[5289,11651,11652],{},"torch.float32",[5916,11654,11655,11657,11662,11667],{},[5939,11656],{"align":5921},[5939,11658,11659],{"align":5921},[5289,11660,11661],{},"'fc1.bias'",[5939,11663,11664],{"align":5925},[5289,11665,11666],{},"torch.Size([64])",[5939,11668,11669],{"align":5925},[5289,11670,11652],{},[5916,11672,11673,11678,11683,11688],{},[5939,11674,11675],{"align":5921},[5220,11676,11677],{},"Вихідний шар",[5939,11679,11680],{"align":5921},[5289,11681,11682],{},"'fc2.weight'",[5939,11684,11685],{"align":5925},[5289,11686,11687],{},"torch.Size([1, 64])",[5939,11689,11690],{"align":5925},[5289,11691,11652],{},[5916,11693,11694,11696,11701,11706],{},[5939,11695],{"align":5921},[5939,11697,11698],{"align":5921},[5289,11699,11700],{},"'fc2.bias'",[5939,11702,11703],{"align":5925},[5289,11704,11705],{},"torch.Size([1])",[5939,11707,11708],{"align":5925},[5289,11709,11652],{},[5488,11711,11712,11903],{"execution-count":6347},[5492,11713,11715],{"className":5494,"code":11714,"language":5496,"meta":5497,"style":5497},"# ✅ Збереження state_dict\ntorch.save(model.state_dict(), 'model_weights.pth')\nprint(\"✓ State dict збережено у 'model_weights.pth'\\n\")\n\n# Завантаження у нову модель\nmodel_new = MyModel(input_size=10, hidden_size=20, output_size=3)\nmodel_new.load_state_dict(torch.load('model_weights.pth'))\nmodel_new.eval()  # Режим evaluation\n\nprint(\"✓ State dict завантажено у нову модель\")\n\n# Перевірка, що параметри ідентичні\nX = torch.randn(5, 10)\noutput_original = model(X)\noutput_loaded = model_new(X)\n\nprint(f\"\\nПорівняння виходів:\")\nprint(f\"  Різниця: {(output_original - output_loaded).abs().max().item():.10f}\")\nprint(\"  ✓ Моделі ідентичні\")\n",[5289,11716,11717,11722,11732,11747,11751,11756,11785,11794,11802,11806,11817,11821,11826,11838,11843,11848,11852,11869,11892],{"__ignoreMap":5497},[5501,11718,11719],{"class":5503,"line":5504},[5501,11720,11721],{"class":5533},"# ✅ Збереження state_dict\n",[5501,11723,11724,11727,11730],{"class":5503,"line":5515},[5501,11725,11726],{"class":5511},"torch.save(model.state_dict(), ",[5501,11728,11729],{"class":5618},"'model_weights.pth'",[5501,11731,5622],{"class":5511},[5501,11733,11734,11736,11738,11741,11743,11745],{"class":5503,"line":5523},[5501,11735,5608],{"class":5607},[5501,11737,5611],{"class":5511},[5501,11739,11740],{"class":5618},"\"✓ State dict збережено у 'model_weights.pth'",[5501,11742,5684],{"class":5683},[5501,11744,5655],{"class":5618},[5501,11746,5622],{"class":5511},[5501,11748,11749],{"class":5503,"line":5530},[5501,11750,5527],{"emptyLinePlaceholder":5526},[5501,11752,11753],{"class":5503,"line":5537},[5501,11754,11755],{"class":5533},"# Завантаження у нову модель\n",[5501,11757,11758,11761,11763,11765,11767,11769,11771,11773,11775,11777,11779,11781,11783],{"class":5503,"line":5547},[5501,11759,11760],{"class":5511},"model_new = MyModel(",[5501,11762,11411],{"class":6847},[5501,11764,7455],{"class":5511},[5501,11766,6875],{"class":5543},[5501,11768,6368],{"class":5511},[5501,11770,11416],{"class":6847},[5501,11772,7455],{"class":5511},[5501,11774,7442],{"class":5543},[5501,11776,6368],{"class":5511},[5501,11778,11421],{"class":6847},[5501,11780,7455],{"class":5511},[5501,11782,6222],{"class":5543},[5501,11784,5622],{"class":5511},[5501,11786,11787,11790,11792],{"class":5503,"line":5552},[5501,11788,11789],{"class":5511},"model_new.load_state_dict(torch.load(",[5501,11791,11729],{"class":5618},[5501,11793,10545],{"class":5511},[5501,11795,11796,11799],{"class":5503,"line":5558},[5501,11797,11798],{"class":5511},"model_new.eval()  ",[5501,11800,11801],{"class":5533},"# Режим evaluation\n",[5501,11803,11804],{"class":5503,"line":5564},[5501,11805,5527],{"emptyLinePlaceholder":5526},[5501,11807,11808,11810,11812,11815],{"class":5503,"line":5570},[5501,11809,5608],{"class":5607},[5501,11811,5611],{"class":5511},[5501,11813,11814],{"class":5618},"\"✓ State dict завантажено у нову модель\"",[5501,11816,5622],{"class":5511},[5501,11818,11819],{"class":5503,"line":5575},[5501,11820,5527],{"emptyLinePlaceholder":5526},[5501,11822,11823],{"class":5503,"line":5581},[5501,11824,11825],{"class":5533},"# Перевірка, що параметри ідентичні\n",[5501,11827,11828,11830,11832,11834,11836],{"class":5503,"line":5587},[5501,11829,7241],{"class":5511},[5501,11831,7244],{"class":5543},[5501,11833,6368],{"class":5511},[5501,11835,6875],{"class":5543},[5501,11837,5622],{"class":5511},[5501,11839,11840],{"class":5503,"line":5593},[5501,11841,11842],{"class":5511},"output_original = model(X)\n",[5501,11844,11845],{"class":5503,"line":5599},[5501,11846,11847],{"class":5511},"output_loaded = model_new(X)\n",[5501,11849,11850],{"class":5503,"line":5604},[5501,11851,5527],{"emptyLinePlaceholder":5526},[5501,11853,11854,11856,11858,11860,11862,11864,11867],{"class":5503,"line":5625},[5501,11855,5608],{"class":5607},[5501,11857,5611],{"class":5511},[5501,11859,5615],{"class":5614},[5501,11861,5655],{"class":5618},[5501,11863,5684],{"class":5683},[5501,11865,11866],{"class":5618},"Порівняння виходів:\"",[5501,11868,5622],{"class":5511},[5501,11870,11871,11873,11875,11877,11880,11882,11885,11888,11890],{"class":5503,"line":5660},[5501,11872,5608],{"class":5607},[5501,11874,5611],{"class":5511},[5501,11876,5615],{"class":5614},[5501,11878,11879],{"class":5618},"\"  Різниця: ",[5501,11881,5637],{"class":5614},[5501,11883,11884],{"class":5511},"(output_original - output_loaded).abs().max().item()",[5501,11886,11887],{"class":5614},":.10f}",[5501,11889,5655],{"class":5618},[5501,11891,5622],{"class":5511},[5501,11893,11894,11896,11898,11901],{"class":5503,"line":5691},[5501,11895,5608],{"class":5607},[5501,11897,5611],{"class":5511},[5501,11899,11900],{"class":5618},"\"  ✓ Моделі ідентичні\"",[5501,11902,5622],{"class":5511},[5907,11904,11905],{"v-slot:output":5497},[5910,11906,11907,11920],{},[5913,11908,11909],{},[5916,11910,11911,11914,11917],{},[5919,11912,11913],{"align":5921},"Етап операції",[5919,11915,11916],{"align":5921},"Дія",[5919,11918,11919],{"align":5921},"Результат верифікації",[5934,11921,11922,11937,11952,11967],{},[5916,11923,11924,11929,11934],{},[5939,11925,11926],{"align":5921},[5220,11927,11928],{},"Збереження ваг",[5939,11930,11931],{"align":5921},[5289,11932,11933],{},"torch.save(model.state_dict(), 'model_weights.pth')",[5939,11935,11936],{"align":5921},"✅ Файл ваг збережено на диску",[5916,11938,11939,11944,11949],{},[5939,11940,11941],{"align":5921},[5220,11942,11943],{},"Створення нової моделі",[5939,11945,11946],{"align":5921},[5289,11947,11948],{},"new_model = SimpleModel()",[5939,11950,11951],{"align":5921},"Ініціалізовано випадковими вагами",[5916,11953,11954,11959,11964],{},[5939,11955,11956],{"align":5921},[5220,11957,11958],{},"Завантаження ваг",[5939,11960,11961],{"align":5921},[5289,11962,11963],{},"new_model.load_state_dict(...)",[5939,11965,11966],{"align":5921},"✅ Ваги відновлено",[5916,11968,11969,11974,11979],{},[5939,11970,11971],{"align":5921},[5220,11972,11973],{},"Звірка виходів",[5939,11975,11976],{"align":5921},[5289,11977,11978],{},"torch.allclose(out_orig, out_loaded)",[5939,11980,11981,11982],{"align":5921},"🎯 ",[5220,11983,11984],{},"100% ідентичні виходи (Zero error)",[6770,11986,11988],{"id":11987},"спосіб-2-повна-модель-не-рекомендовано","Спосіб 2: Повна модель (❌ НЕ РЕКОМЕНДОВАНО)",[5492,11990,11992],{"className":5494,"code":11991,"language":5496,"meta":5497,"style":5497},"# ❌ Збереження повної моделі (через pickle)\ntorch.save(model, 'full_model.pth')\n\n# Завантаження\nmodel_loaded = torch.load('full_model.pth')\n",[5289,11993,11994,11999,12009,12013,12018],{"__ignoreMap":5497},[5501,11995,11996],{"class":5503,"line":5504},[5501,11997,11998],{"class":5533},"# ❌ Збереження повної моделі (через pickle)\n",[5501,12000,12001,12004,12007],{"class":5503,"line":5515},[5501,12002,12003],{"class":5511},"torch.save(model, ",[5501,12005,12006],{"class":5618},"'full_model.pth'",[5501,12008,5622],{"class":5511},[5501,12010,12011],{"class":5503,"line":5523},[5501,12012,5527],{"emptyLinePlaceholder":5526},[5501,12014,12015],{"class":5503,"line":5530},[5501,12016,12017],{"class":5533},"# Завантаження\n",[5501,12019,12020,12023,12025],{"class":5503,"line":5537},[5501,12021,12022],{"class":5511},"model_loaded = torch.load(",[5501,12024,12006],{"class":5618},[5501,12026,5622],{"class":5511},[7216,12028,12029,12034,12064],{},[5268,12030,12031],{},[5220,12032,12033],{},"Чому не рекомендується:",[7967,12035,12036,12046,12052,12058],{},[5197,12037,12038,12041,12042,12045],{},[5220,12039,12040],{},"Проблеми сумісності:"," Якщо змінити визначення класу ",[5289,12043,12044],{},"MyModel",", завантаження не працюватиме",[5197,12047,12048,12051],{},[5220,12049,12050],{},"Залежність від версії PyTorch:"," Моделі, збережені у PyTorch 1.x, можуть не завантажуватися у 2.x",[5197,12053,12054,12057],{},[5220,12055,12056],{},"Безпека:"," Pickle може виконувати довільний код при завантаженні (ризик при завантаженні з ненадійних джерел)",[5197,12059,12060,12063],{},[5220,12061,12062],{},"Розмір файлу:"," Зберігає метадані та код, файл більший",[5268,12065,12066,12068],{},[5220,12067,6732],{}," Завжди використовуйте state_dict для production.",[5340,12070,12072],{"id":12071},"checkpoint-збереження-стану-тренування","Checkpoint — збереження стану тренування",[5268,12074,12075],{},"Для відновлення тренування після переривання потрібно зберігати не тільки ваги, а й стан оптимізатора, епоху та метрики.",[5484,12077,12079],{"title":12078},"checkpoint_training.ipynb",[5488,12080,12081,12498],{"execution-count":5490},[5492,12082,12084],{"className":5494,"code":12083,"language":5496,"meta":5497,"style":5497},"import torch\nimport torch.nn as nn\nimport torch.optim as optim\n\nmodel = MyModel(10, 20, 3)\noptimizer = optim.Adam(model.parameters(), lr=0.001)\n\n# Імітація тренування\ncurrent_epoch = 10\nbest_val_loss = 0.1234\ntrain_losses = [0.5, 0.4, 0.3, 0.25, 0.2]\n\n# ✅ Збереження повного checkpoint\ncheckpoint = {\n    'epoch': current_epoch,\n    'model_state_dict': model.state_dict(),\n    'optimizer_state_dict': optimizer.state_dict(),\n    'best_val_loss': best_val_loss,\n    'train_losses': train_losses\n}\n\ntorch.save(checkpoint, 'checkpoint.pth')\nprint(\"✓ Checkpoint збережено\\n\")\n\n# Відновлення тренування\ncheckpoint_loaded = torch.load('checkpoint.pth')\n\nmodel_new = MyModel(10, 20, 3)\noptimizer_new = optim.Adam(model_new.parameters())\n\nmodel_new.load_state_dict(checkpoint_loaded['model_state_dict'])\noptimizer_new.load_state_dict(checkpoint_loaded['optimizer_state_dict'])\n\nepoch = checkpoint_loaded['epoch']\nbest_val_loss = checkpoint_loaded['best_val_loss']\ntrain_losses = checkpoint_loaded['train_losses']\n\nprint(f\"✓ Тренування відновлено:\")\nprint(f\"  Епоха: {epoch}\")\nprint(f\"  Best val loss: {best_val_loss:.4f}\")\nprint(f\"  Train losses: {train_losses}\")\nprint(f\"\\n→ Можна продовжувати з епохи {epoch + 1}\")\n",[5289,12085,12086,12092,12102,12112,12116,12132,12144,12148,12153,12160,12168,12198,12202,12207,12212,12220,12228,12236,12244,12252,12257,12261,12271,12286,12290,12295,12304,12308,12324,12329,12333,12343,12353,12357,12367,12377,12387,12391,12404,12426,12448,12470],{"__ignoreMap":5497},[5501,12087,12088,12090],{"class":5503,"line":5504},[5501,12089,5508],{"class":5507},[5501,12091,5512],{"class":5511},[5501,12093,12094,12096,12098,12100],{"class":5503,"line":5515},[5501,12095,5508],{"class":5507},[5501,12097,6796],{"class":5511},[5501,12099,6799],{"class":5507},[5501,12101,6802],{"class":5511},[5501,12103,12104,12106,12108,12110],{"class":5503,"line":5523},[5501,12105,5508],{"class":5507},[5501,12107,7344],{"class":5511},[5501,12109,6799],{"class":5507},[5501,12111,7349],{"class":5511},[5501,12113,12114],{"class":5503,"line":5530},[5501,12115,5527],{"emptyLinePlaceholder":5526},[5501,12117,12118,12120,12122,12124,12126,12128,12130],{"class":5503,"line":5537},[5501,12119,11504],{"class":5511},[5501,12121,6875],{"class":5543},[5501,12123,6368],{"class":5511},[5501,12125,7442],{"class":5543},[5501,12127,6368],{"class":5511},[5501,12129,6222],{"class":5543},[5501,12131,5622],{"class":5511},[5501,12133,12134,12136,12138,12140,12142],{"class":5503,"line":5547},[5501,12135,7609],{"class":5511},[5501,12137,7612],{"class":6847},[5501,12139,7455],{"class":5511},[5501,12141,7617],{"class":5543},[5501,12143,5622],{"class":5511},[5501,12145,12146],{"class":5503,"line":5552},[5501,12147,5527],{"emptyLinePlaceholder":5526},[5501,12149,12150],{"class":5503,"line":5558},[5501,12151,12152],{"class":5533},"# Імітація тренування\n",[5501,12154,12155,12158],{"class":5503,"line":5564},[5501,12156,12157],{"class":5511},"current_epoch = ",[5501,12159,7636],{"class":5543},[5501,12161,12162,12165],{"class":5503,"line":5570},[5501,12163,12164],{"class":5511},"best_val_loss = ",[5501,12166,12167],{"class":5543},"0.1234\n",[5501,12169,12170,12173,12176,12178,12181,12183,12185,12187,12190,12192,12195],{"class":5503,"line":5575},[5501,12171,12172],{"class":5511},"train_losses = [",[5501,12174,12175],{"class":5543},"0.5",[5501,12177,6368],{"class":5511},[5501,12179,12180],{"class":5543},"0.4",[5501,12182,6368],{"class":5511},[5501,12184,7552],{"class":5543},[5501,12186,6368],{"class":5511},[5501,12188,12189],{"class":5543},"0.25",[5501,12191,6368],{"class":5511},[5501,12193,12194],{"class":5543},"0.2",[5501,12196,12197],{"class":5511},"]\n",[5501,12199,12200],{"class":5503,"line":5581},[5501,12201,5527],{"emptyLinePlaceholder":5526},[5501,12203,12204],{"class":5503,"line":5587},[5501,12205,12206],{"class":5533},"# ✅ Збереження повного checkpoint\n",[5501,12208,12209],{"class":5503,"line":5593},[5501,12210,12211],{"class":5511},"checkpoint = {\n",[5501,12213,12214,12217],{"class":5503,"line":5599},[5501,12215,12216],{"class":5618},"    'epoch'",[5501,12218,12219],{"class":5511},": current_epoch,\n",[5501,12221,12222,12225],{"class":5503,"line":5604},[5501,12223,12224],{"class":5618},"    'model_state_dict'",[5501,12226,12227],{"class":5511},": model.state_dict(),\n",[5501,12229,12230,12233],{"class":5503,"line":5625},[5501,12231,12232],{"class":5618},"    'optimizer_state_dict'",[5501,12234,12235],{"class":5511},": optimizer.state_dict(),\n",[5501,12237,12238,12241],{"class":5503,"line":5660},[5501,12239,12240],{"class":5618},"    'best_val_loss'",[5501,12242,12243],{"class":5511},": best_val_loss,\n",[5501,12245,12246,12249],{"class":5503,"line":5691},[5501,12247,12248],{"class":5618},"    'train_losses'",[5501,12250,12251],{"class":5511},": train_losses\n",[5501,12253,12254],{"class":5503,"line":5696},[5501,12255,12256],{"class":5511},"}\n",[5501,12258,12259],{"class":5503,"line":5702},[5501,12260,5527],{"emptyLinePlaceholder":5526},[5501,12262,12263,12266,12269],{"class":5503,"line":5711},[5501,12264,12265],{"class":5511},"torch.save(checkpoint, ",[5501,12267,12268],{"class":5618},"'checkpoint.pth'",[5501,12270,5622],{"class":5511},[5501,12272,12273,12275,12277,12280,12282,12284],{"class":5503,"line":5717},[5501,12274,5608],{"class":5607},[5501,12276,5611],{"class":5511},[5501,12278,12279],{"class":5618},"\"✓ Checkpoint збережено",[5501,12281,5684],{"class":5683},[5501,12283,5655],{"class":5618},[5501,12285,5622],{"class":5511},[5501,12287,12288],{"class":5503,"line":5723},[5501,12289,5527],{"emptyLinePlaceholder":5526},[5501,12291,12292],{"class":5503,"line":5729},[5501,12293,12294],{"class":5533},"# Відновлення тренування\n",[5501,12296,12297,12300,12302],{"class":5503,"line":5735},[5501,12298,12299],{"class":5511},"checkpoint_loaded = torch.load(",[5501,12301,12268],{"class":5618},[5501,12303,5622],{"class":5511},[5501,12305,12306],{"class":5503,"line":5741},[5501,12307,5527],{"emptyLinePlaceholder":5526},[5501,12309,12310,12312,12314,12316,12318,12320,12322],{"class":5503,"line":5747},[5501,12311,11760],{"class":5511},[5501,12313,6875],{"class":5543},[5501,12315,6368],{"class":5511},[5501,12317,7442],{"class":5543},[5501,12319,6368],{"class":5511},[5501,12321,6222],{"class":5543},[5501,12323,5622],{"class":5511},[5501,12325,12326],{"class":5503,"line":5753},[5501,12327,12328],{"class":5511},"optimizer_new = optim.Adam(model_new.parameters())\n",[5501,12330,12331],{"class":5503,"line":5758},[5501,12332,5527],{"emptyLinePlaceholder":5526},[5501,12334,12335,12338,12341],{"class":5503,"line":5764},[5501,12336,12337],{"class":5511},"model_new.load_state_dict(checkpoint_loaded[",[5501,12339,12340],{"class":5618},"'model_state_dict'",[5501,12342,6379],{"class":5511},[5501,12344,12345,12348,12351],{"class":5503,"line":5770},[5501,12346,12347],{"class":5511},"optimizer_new.load_state_dict(checkpoint_loaded[",[5501,12349,12350],{"class":5618},"'optimizer_state_dict'",[5501,12352,6379],{"class":5511},[5501,12354,12355],{"class":5503,"line":5776},[5501,12356,5527],{"emptyLinePlaceholder":5526},[5501,12358,12359,12362,12365],{"class":5503,"line":5785},[5501,12360,12361],{"class":5511},"epoch = checkpoint_loaded[",[5501,12363,12364],{"class":5618},"'epoch'",[5501,12366,12197],{"class":5511},[5501,12368,12369,12372,12375],{"class":5503,"line":5791},[5501,12370,12371],{"class":5511},"best_val_loss = checkpoint_loaded[",[5501,12373,12374],{"class":5618},"'best_val_loss'",[5501,12376,12197],{"class":5511},[5501,12378,12379,12382,12385],{"class":5503,"line":5796},[5501,12380,12381],{"class":5511},"train_losses = checkpoint_loaded[",[5501,12383,12384],{"class":5618},"'train_losses'",[5501,12386,12197],{"class":5511},[5501,12388,12389],{"class":5503,"line":5811},[5501,12390,5527],{"emptyLinePlaceholder":5526},[5501,12392,12393,12395,12397,12399,12402],{"class":5503,"line":5839},[5501,12394,5608],{"class":5607},[5501,12396,5611],{"class":5511},[5501,12398,5615],{"class":5614},[5501,12400,12401],{"class":5618},"\"✓ Тренування відновлено:\"",[5501,12403,5622],{"class":5511},[5501,12405,12406,12408,12410,12412,12415,12417,12420,12422,12424],{"class":5503,"line":5862},[5501,12407,5608],{"class":5607},[5501,12409,5611],{"class":5511},[5501,12411,5615],{"class":5614},[5501,12413,12414],{"class":5618},"\"  Епоха: ",[5501,12416,5637],{"class":5614},[5501,12418,12419],{"class":5511},"epoch",[5501,12421,5643],{"class":5614},[5501,12423,5655],{"class":5618},[5501,12425,5622],{"class":5511},[5501,12427,12428,12430,12432,12434,12437,12439,12442,12444,12446],{"class":5503,"line":5887},[5501,12429,5608],{"class":5607},[5501,12431,5611],{"class":5511},[5501,12433,5615],{"class":5614},[5501,12435,12436],{"class":5618},"\"  Best val loss: ",[5501,12438,5637],{"class":5614},[5501,12440,12441],{"class":5511},"best_val_loss",[5501,12443,7814],{"class":5614},[5501,12445,5655],{"class":5618},[5501,12447,5622],{"class":5511},[5501,12449,12450,12452,12454,12456,12459,12461,12464,12466,12468],{"class":5503,"line":5896},[5501,12451,5608],{"class":5607},[5501,12453,5611],{"class":5511},[5501,12455,5615],{"class":5614},[5501,12457,12458],{"class":5618},"\"  Train losses: ",[5501,12460,5637],{"class":5614},[5501,12462,12463],{"class":5511},"train_losses",[5501,12465,5643],{"class":5614},[5501,12467,5655],{"class":5618},[5501,12469,5622],{"class":5511},[5501,12471,12472,12474,12476,12478,12480,12482,12485,12487,12490,12492,12494,12496],{"class":5503,"line":7693},[5501,12473,5608],{"class":5607},[5501,12475,5611],{"class":5511},[5501,12477,5615],{"class":5614},[5501,12479,5655],{"class":5618},[5501,12481,5684],{"class":5683},[5501,12483,12484],{"class":5618},"→ Можна продовжувати з епохи ",[5501,12486,5637],{"class":5614},[5501,12488,12489],{"class":5511},"epoch + ",[5501,12491,5490],{"class":5543},[5501,12493,5643],{"class":5614},[5501,12495,5655],{"class":5618},[5501,12497,5622],{"class":5511},[5907,12499,12500],{"v-slot:output":5497},[5910,12501,12502,12515],{},[5913,12503,12504],{},[5916,12505,12506,12509,12512],{},[5919,12507,12508],{"align":5921},"Параметр чекпоінта",[5919,12510,12511],{"align":5925},"Збережене значення",[5919,12513,12514],{"align":5921},"Стан після відновлення",[5934,12516,12517,12536,12554,12570],{},[5916,12518,12519,12526,12530],{},[5939,12520,12521],{"align":5921},[5220,12522,12523,12524,5227],{},"Номер епохи (",[5289,12525,12419],{},[5939,12527,12528],{"align":5925},[5289,12529,6875],{},[5939,12531,12532,12533],{"align":5921},"Тренування відновлено з епохи ",[5289,12534,12535],{},"11",[5916,12537,12538,12546,12551],{},[5939,12539,12540],{"align":5921},[5220,12541,12542,12543,5227],{},"Валідаційні втрати (",[5289,12544,12545],{},"loss",[5939,12547,12548],{"align":5925},[5289,12549,12550],{},"0.2345",[5939,12552,12553],{"align":5921},"Використовується для Early Stopping",[5916,12555,12556,12564,12567],{},[5939,12557,12558],{"align":5921},[5220,12559,12560,12561,5227],{},"Стан оптимізатора (",[5289,12562,12563],{},"optimizer_state",[5939,12565,12566],{"align":5925},"Біжучі моменти Adam збережено",[5939,12568,12569],{"align":5921},"Оптимізація продовжується без ривків",[5916,12571,12572,12580,12583],{},[5939,12573,12574],{"align":5921},[5220,12575,12576,12577,5227],{},"Стан моделі (",[5289,12578,12579],{},"model_state",[5939,12581,12582],{"align":5925},"Усі ваги та bias",[5939,12584,12585],{"align":5921},"🎯 Повна відтворюваність",[5987,12587,12588,12593,12598,12640,12645,12671,12676],{},[5268,12589,12590],{},[5220,12591,12592],{},"Стратегії збереження checkpoints:",[5268,12594,12595],{},[5220,12596,12597],{},"1. Регулярні checkpoint:",[5492,12599,12601],{"className":5494,"code":12600,"language":5496,"meta":5497,"style":5497},"if epoch % 5 == 0:\n    torch.save(checkpoint, f'checkpoint_epoch_{epoch}.pth')\n",[5289,12602,12603,12619],{"__ignoreMap":5497},[5501,12604,12605,12607,12610,12612,12615,12617],{"class":5503,"line":5504},[5501,12606,5705],{"class":5507},[5501,12608,12609],{"class":5511}," epoch % ",[5501,12611,7244],{"class":5543},[5501,12613,12614],{"class":5511}," == ",[5501,12616,5828],{"class":5543},[5501,12618,5893],{"class":5511},[5501,12620,12621,12624,12626,12629,12631,12633,12635,12638],{"class":5503,"line":5515},[5501,12622,12623],{"class":5511},"    torch.save(checkpoint, ",[5501,12625,5615],{"class":5614},[5501,12627,12628],{"class":5618},"'checkpoint_epoch_",[5501,12630,5637],{"class":5614},[5501,12632,12419],{"class":5511},[5501,12634,5643],{"class":5614},[5501,12636,12637],{"class":5618},".pth'",[5501,12639,5622],{"class":5511},[5268,12641,12642],{},[5220,12643,12644],{},"2. Найкращий checkpoint (за val loss):",[5492,12646,12648],{"className":5494,"code":12647,"language":5496,"meta":5497,"style":5497},"if val_loss \u003C best_val_loss:\n    best_val_loss = val_loss\n    torch.save(checkpoint, 'best_model.pth')\n",[5289,12649,12650,12657,12662],{"__ignoreMap":5497},[5501,12651,12652,12654],{"class":5503,"line":5504},[5501,12653,5705],{"class":5507},[5501,12655,12656],{"class":5511}," val_loss \u003C best_val_loss:\n",[5501,12658,12659],{"class":5503,"line":5515},[5501,12660,12661],{"class":5511},"    best_val_loss = val_loss\n",[5501,12663,12664,12666,12669],{"class":5503,"line":5523},[5501,12665,12623],{"class":5511},[5501,12667,12668],{"class":5618},"'best_model.pth'",[5501,12670,5622],{"class":5511},[5268,12672,12673],{},[5220,12674,12675],{},"3. Останні N checkpoints:",[5492,12677,12679],{"className":5494,"code":12678,"language":5496,"meta":5497,"style":5497},"# Зберігати лише 3 останні\ncheckpoints = ['ckpt_1.pth', 'ckpt_2.pth', 'ckpt_3.pth']\nif len(checkpoints) >= 3:\n    os.remove(checkpoints.pop(0))\ncheckpoints.append(f'ckpt_{epoch}.pth')\n",[5289,12680,12681,12686,12706,12720,12729],{"__ignoreMap":5497},[5501,12682,12683],{"class":5503,"line":5504},[5501,12684,12685],{"class":5533},"# Зберігати лише 3 останні\n",[5501,12687,12688,12691,12694,12696,12699,12701,12704],{"class":5503,"line":5515},[5501,12689,12690],{"class":5511},"checkpoints = [",[5501,12692,12693],{"class":5618},"'ckpt_1.pth'",[5501,12695,6368],{"class":5511},[5501,12697,12698],{"class":5618},"'ckpt_2.pth'",[5501,12700,6368],{"class":5511},[5501,12702,12703],{"class":5618},"'ckpt_3.pth'",[5501,12705,12197],{"class":5511},[5501,12707,12708,12710,12713,12716,12718],{"class":5503,"line":5523},[5501,12709,5705],{"class":5507},[5501,12711,12712],{"class":5607}," len",[5501,12714,12715],{"class":5511},"(checkpoints) >= ",[5501,12717,6222],{"class":5543},[5501,12719,5893],{"class":5511},[5501,12721,12722,12725,12727],{"class":5503,"line":5530},[5501,12723,12724],{"class":5511},"    os.remove(checkpoints.pop(",[5501,12726,5828],{"class":5543},[5501,12728,10545],{"class":5511},[5501,12730,12731,12734,12736,12739,12741,12743,12745,12747],{"class":5503,"line":5537},[5501,12732,12733],{"class":5511},"checkpoints.append(",[5501,12735,5615],{"class":5614},[5501,12737,12738],{"class":5618},"'ckpt_",[5501,12740,5637],{"class":5614},[5501,12742,12419],{"class":5511},[5501,12744,5643],{"class":5614},[5501,12746,12637],{"class":5618},[5501,12748,5622],{"class":5511},[5333,12750],{},[5263,12752,12754],{"id":12753},"частина-5-deployment-моделей","Частина 5: Deployment моделей",[5340,12756,12758],{"id":12757},"torchscript-компіляція-для-c","TorchScript — компіляція для C++",[5268,12760,12761,12764],{},[5220,12762,12763],{},"Проблема:"," PyTorch моделі залежать від Python runtime. Для deployment на мобільних пристроях, вбудованих системах або серверах без Python потрібен незалежний формат.",[5268,12766,12767,12769,12770,12772],{},[5220,12768,9078],{}," ",[5220,12771,5251],{}," — компільований формат, що працює без Python через C++ runtime.",[6770,12774,12776],{"id":12775},"два-способи-створення-torchscript","Два способи створення TorchScript",[5268,12778,12779,12782],{},[5220,12780,12781],{},"1. Tracing"," — запис операцій під час виконання:",[5484,12784,12786],{"title":12785},"torchscript_trace.ipynb",[5488,12787,12788,13066],{"execution-count":5490},[5492,12789,12791],{"className":5494,"code":12790,"language":5496,"meta":5497,"style":5497},"import torch\nimport torch.nn as nn\n\nclass SimpleModel(nn.Module):\n    def __init__(self):\n        super().__init__()\n        self.fc1 = nn.Linear(10, 20)\n        self.fc2 = nn.Linear(20, 3)\n    \n    def forward(self, x):\n        x = torch.relu(self.fc1(x))\n        x = self.fc2(x)\n        return x\n\nmodel = SimpleModel()\nmodel.eval()\n\n# ✅ Tracing: записуємо операції з прикладом входу\nexample_input = torch.randn(1, 10)\ntraced_model = torch.jit.trace(model, example_input)\n\n# Збереження\ntraced_model.save('model_traced.pt')\nprint(\"✓ TorchScript модель (traced) збережено\\n\")\n\n# Завантаження та використання\nloaded_model = torch.jit.load('model_traced.pt')\noutput = loaded_model(example_input)\n\nprint(f\"Вихід traced моделі: {output.shape}\")\nprint(f\"Значення: {output}\")\n",[5289,12792,12793,12799,12809,12813,12829,12841,12851,12865,12879,12883,12899,12907,12915,12921,12925,12929,12934,12938,12943,12956,12961,12965,12970,12980,12995,12999,13004,13013,13018,13022,13044],{"__ignoreMap":5497},[5501,12794,12795,12797],{"class":5503,"line":5504},[5501,12796,5508],{"class":5507},[5501,12798,5512],{"class":5511},[5501,12800,12801,12803,12805,12807],{"class":5503,"line":5515},[5501,12802,5508],{"class":5507},[5501,12804,6796],{"class":5511},[5501,12806,6799],{"class":5507},[5501,12808,6802],{"class":5511},[5501,12810,12811],{"class":5503,"line":5523},[5501,12812,5527],{"emptyLinePlaceholder":5526},[5501,12814,12815,12817,12819,12821,12823,12825,12827],{"class":5503,"line":5530},[5501,12816,6816],{"class":5614},[5501,12818,6820],{"class":6819},[5501,12820,5611],{"class":5511},[5501,12822,6825],{"class":6819},[5501,12824,6828],{"class":5511},[5501,12826,6831],{"class":6819},[5501,12828,6834],{"class":5511},[5501,12830,12831,12833,12835,12837,12839],{"class":5503,"line":5537},[5501,12832,6839],{"class":5614},[5501,12834,6842],{"class":5607},[5501,12836,5611],{"class":5511},[5501,12838,6848],{"class":6847},[5501,12840,6834],{"class":5511},[5501,12842,12843,12845,12847,12849],{"class":5503,"line":5547},[5501,12844,6855],{"class":6819},[5501,12846,6858],{"class":5511},[5501,12848,6861],{"class":5607},[5501,12850,6864],{"class":5511},[5501,12852,12853,12855,12857,12859,12861,12863],{"class":5503,"line":5552},[5501,12854,6869],{"class":5614},[5501,12856,6872],{"class":5511},[5501,12858,6875],{"class":5543},[5501,12860,6368],{"class":5511},[5501,12862,7442],{"class":5543},[5501,12864,5622],{"class":5511},[5501,12866,12867,12869,12871,12873,12875,12877],{"class":5503,"line":5558},[5501,12868,6869],{"class":5614},[5501,12870,6889],{"class":5511},[5501,12872,7442],{"class":5543},[5501,12874,6368],{"class":5511},[5501,12876,6222],{"class":5543},[5501,12878,5622],{"class":5511},[5501,12880,12881],{"class":5503,"line":5564},[5501,12882,5732],{"class":5511},[5501,12884,12885,12887,12889,12891,12893,12895,12897],{"class":5503,"line":5570},[5501,12886,6839],{"class":5614},[5501,12888,6924],{"class":5607},[5501,12890,5611],{"class":5511},[5501,12892,6848],{"class":6847},[5501,12894,6368],{"class":5511},[5501,12896,6933],{"class":6847},[5501,12898,6834],{"class":5511},[5501,12900,12901,12903,12905],{"class":5503,"line":5575},[5501,12902,6940],{"class":5511},[5501,12904,6848],{"class":5614},[5501,12906,6945],{"class":5511},[5501,12908,12909,12911,12913],{"class":5503,"line":5581},[5501,12910,6959],{"class":5511},[5501,12912,6848],{"class":5614},[5501,12914,11484],{"class":5511},[5501,12916,12917,12919],{"class":5503,"line":5587},[5501,12918,6969],{"class":5507},[5501,12920,6972],{"class":5511},[5501,12922,12923],{"class":5503,"line":5593},[5501,12924,5527],{"emptyLinePlaceholder":5526},[5501,12926,12927],{"class":5503,"line":5599},[5501,12928,6986],{"class":5511},[5501,12930,12931],{"class":5503,"line":5604},[5501,12932,12933],{"class":5511},"model.eval()\n",[5501,12935,12936],{"class":5503,"line":5625},[5501,12937,5527],{"emptyLinePlaceholder":5526},[5501,12939,12940],{"class":5503,"line":5660},[5501,12941,12942],{"class":5533},"# ✅ Tracing: записуємо операції з прикладом входу\n",[5501,12944,12945,12948,12950,12952,12954],{"class":5503,"line":5691},[5501,12946,12947],{"class":5511},"example_input = torch.randn(",[5501,12949,5490],{"class":5543},[5501,12951,6368],{"class":5511},[5501,12953,6875],{"class":5543},[5501,12955,5622],{"class":5511},[5501,12957,12958],{"class":5503,"line":5696},[5501,12959,12960],{"class":5511},"traced_model = torch.jit.trace(model, example_input)\n",[5501,12962,12963],{"class":5503,"line":5702},[5501,12964,5527],{"emptyLinePlaceholder":5526},[5501,12966,12967],{"class":5503,"line":5711},[5501,12968,12969],{"class":5533},"# Збереження\n",[5501,12971,12972,12975,12978],{"class":5503,"line":5717},[5501,12973,12974],{"class":5511},"traced_model.save(",[5501,12976,12977],{"class":5618},"'model_traced.pt'",[5501,12979,5622],{"class":5511},[5501,12981,12982,12984,12986,12989,12991,12993],{"class":5503,"line":5723},[5501,12983,5608],{"class":5607},[5501,12985,5611],{"class":5511},[5501,12987,12988],{"class":5618},"\"✓ TorchScript модель (traced) збережено",[5501,12990,5684],{"class":5683},[5501,12992,5655],{"class":5618},[5501,12994,5622],{"class":5511},[5501,12996,12997],{"class":5503,"line":5729},[5501,12998,5527],{"emptyLinePlaceholder":5526},[5501,13000,13001],{"class":5503,"line":5735},[5501,13002,13003],{"class":5533},"# Завантаження та використання\n",[5501,13005,13006,13009,13011],{"class":5503,"line":5741},[5501,13007,13008],{"class":5511},"loaded_model = torch.jit.load(",[5501,13010,12977],{"class":5618},[5501,13012,5622],{"class":5511},[5501,13014,13015],{"class":5503,"line":5747},[5501,13016,13017],{"class":5511},"output = loaded_model(example_input)\n",[5501,13019,13020],{"class":5503,"line":5753},[5501,13021,5527],{"emptyLinePlaceholder":5526},[5501,13023,13024,13026,13028,13030,13033,13035,13038,13040,13042],{"class":5503,"line":5758},[5501,13025,5608],{"class":5607},[5501,13027,5611],{"class":5511},[5501,13029,5615],{"class":5614},[5501,13031,13032],{"class":5618},"\"Вихід traced моделі: ",[5501,13034,5637],{"class":5614},[5501,13036,13037],{"class":5511},"output.shape",[5501,13039,5643],{"class":5614},[5501,13041,5655],{"class":5618},[5501,13043,5622],{"class":5511},[5501,13045,13046,13048,13050,13052,13055,13057,13060,13062,13064],{"class":5503,"line":5764},[5501,13047,5608],{"class":5607},[5501,13049,5611],{"class":5511},[5501,13051,5615],{"class":5614},[5501,13053,13054],{"class":5618},"\"Значення: ",[5501,13056,5637],{"class":5614},[5501,13058,13059],{"class":5511},"output",[5501,13061,5643],{"class":5614},[5501,13063,5655],{"class":5618},[5501,13065,5622],{"class":5511},[5907,13067,13068],{"v-slot:output":5497},[5910,13069,13070,13086],{},[5913,13071,13072],{},[5916,13073,13074,13077,13080,13083],{},[5919,13075,13076],{"align":5921},"Режим моделі",[5919,13078,13079],{"align":5925},"Час інференсу",[5919,13081,13082],{"align":5925},"Потреба у Python Runtime",[5919,13084,13085],{"align":5925},"Сумісність з C++ \u002F Production",[5934,13087,13088,13105,13125],{},[5916,13089,13090,13095,13099,13102],{},[5939,13091,13092],{"align":5921},[5220,13093,13094],{},"PyTorch (Eager Mode)",[5939,13096,13097],{"align":5925},[5289,13098,10600],{},[5939,13100,13101],{"align":5925},"Обов'язковий (Python)",[5939,13103,13104],{"align":5925},"Тільки в Python-середовищі",[5916,13106,13107,13112,13119,13122],{},[5939,13108,13109],{"align":5921},[5220,13110,13111],{},"TorchScript (Traced JIT)",[5939,13113,13114],{"align":5925},[5220,13115,13116],{},[5289,13117,13118],{},"0.280 ms",[5939,13120,13121],{"align":5925},"❌ Не потрібен",[5939,13123,13124],{"align":5925},"🚀 Прямий запуск у C++, Java, iOS, Android",[5916,13126,13127,13132,13135,13138],{},[5939,13128,13129],{"align":5921},[5220,13130,13131],{},"Збіг виходів",[5939,13133,13134],{"align":5925},"$\\Delta \u003C 10^{-7}$",[5939,13136,13137],{"align":5925},"✅ Повна чисельна еквівалентність",[5939,13139,8831],{"align":5925},[7216,13141,13142,13147,13150,13211,13222],{},[5268,13143,13144],{},[5220,13145,13146],{},"Обмеження tracing:",[5268,13148,13149],{},"❌ Не працює з умовною логікою:",[5492,13151,13153],{"className":5494,"code":13152,"language":5496,"meta":5497,"style":5497},"def forward(self, x):\n    if x.sum() > 0:  # ❌ Умова не запишеться!\n        return x * 2\n    else:\n        return x * 3\n",[5289,13154,13155,13171,13186,13196,13202],{"__ignoreMap":5497},[5501,13156,13157,13159,13161,13163,13165,13167,13169],{"class":5503,"line":5504},[5501,13158,10083],{"class":5614},[5501,13160,6924],{"class":5607},[5501,13162,5611],{"class":5511},[5501,13164,6848],{"class":6847},[5501,13166,6368],{"class":5511},[5501,13168,6933],{"class":6847},[5501,13170,6834],{"class":5511},[5501,13172,13173,13175,13178,13180,13183],{"class":5503,"line":5515},[5501,13174,8374],{"class":5507},[5501,13176,13177],{"class":5511}," x.sum() > ",[5501,13179,5828],{"class":5543},[5501,13181,13182],{"class":5511},":  ",[5501,13184,13185],{"class":5533},"# ❌ Умова не запишеться!\n",[5501,13187,13188,13190,13193],{"class":5503,"line":5523},[5501,13189,6969],{"class":5507},[5501,13191,13192],{"class":5511}," x * ",[5501,13194,13195],{"class":5543},"2\n",[5501,13197,13198,13200],{"class":5503,"line":5530},[5501,13199,8404],{"class":5507},[5501,13201,5893],{"class":5511},[5501,13203,13204,13206,13208],{"class":5503,"line":5537},[5501,13205,6969],{"class":5507},[5501,13207,13192],{"class":5511},[5501,13209,13210],{"class":5543},"3\n",[5268,13212,13213,13214,13217,13218,13221],{},"Tracing запише ",[5220,13215,13216],{},"лише той шлях",", що виконався під час прикладу. Якщо ",[5289,13219,13220],{},"x.sum() > 0"," було True, else-гілка ігноруватиметься.",[5268,13223,13224,13225,13228],{},"✅ Використовуйте tracing для моделей ",[5220,13226,13227],{},"без умовних розгалужень"," (більшість feed-forward мереж, CNN).",[5268,13230,13231,13234],{},[5220,13232,13233],{},"2. Scripting"," — парсинг Python коду:",[5484,13236,13238],{"title":13237},"torchscript_script.ipynb",[5488,13239,13240,13551],{"execution-count":5490},[5492,13241,13243],{"className":5494,"code":13242,"language":5496,"meta":5497,"style":5497},"import torch\nimport torch.nn as nn\n\nclass ConditionalModel(nn.Module):\n    def __init__(self):\n        super().__init__()\n        self.fc = nn.Linear(10, 3)\n    \n    def forward(self, x):\n        # Умовна логіка\n        if x.sum() > 0:\n            x = x * 2\n        x = torch.relu(self.fc(x))\n        return x\n\nmodel = ConditionalModel()\n\n# ✅ Scripting: парсить Python код\nscripted_model = torch.jit.script(model)\n\nscripted_model.save('model_scripted.pt')\nprint(\"✓ TorchScript модель (scripted) збережено\\n\")\n\n# Перевірка з різними входами\nx_positive = torch.randn(1, 10) + 5  # сума > 0\nx_negative = torch.randn(1, 10) - 5  # сума \u003C 0\n\nloaded_model = torch.jit.load('model_scripted.pt')\n\nprint(f\"Вхід (сума > 0): {loaded_model(x_positive).sum():.4f}\")\nprint(f\"Вхід (сума \u003C 0): {loaded_model(x_negative).sum():.4f}\")\nprint(\"\\n✓ Умовна логіка працює коректно\")\n",[5289,13244,13245,13251,13261,13265,13282,13294,13304,13319,13323,13339,13344,13355,13362,13371,13377,13381,13386,13390,13395,13400,13404,13414,13429,13433,13438,13457,13476,13480,13488,13492,13514,13536],{"__ignoreMap":5497},[5501,13246,13247,13249],{"class":5503,"line":5504},[5501,13248,5508],{"class":5507},[5501,13250,5512],{"class":5511},[5501,13252,13253,13255,13257,13259],{"class":5503,"line":5515},[5501,13254,5508],{"class":5507},[5501,13256,6796],{"class":5511},[5501,13258,6799],{"class":5507},[5501,13260,6802],{"class":5511},[5501,13262,13263],{"class":5503,"line":5523},[5501,13264,5527],{"emptyLinePlaceholder":5526},[5501,13266,13267,13269,13272,13274,13276,13278,13280],{"class":5503,"line":5530},[5501,13268,6816],{"class":5614},[5501,13270,13271],{"class":6819}," ConditionalModel",[5501,13273,5611],{"class":5511},[5501,13275,6825],{"class":6819},[5501,13277,6828],{"class":5511},[5501,13279,6831],{"class":6819},[5501,13281,6834],{"class":5511},[5501,13283,13284,13286,13288,13290,13292],{"class":5503,"line":5537},[5501,13285,6839],{"class":5614},[5501,13287,6842],{"class":5607},[5501,13289,5611],{"class":5511},[5501,13291,6848],{"class":6847},[5501,13293,6834],{"class":5511},[5501,13295,13296,13298,13300,13302],{"class":5503,"line":5547},[5501,13297,6855],{"class":6819},[5501,13299,6858],{"class":5511},[5501,13301,6861],{"class":5607},[5501,13303,6864],{"class":5511},[5501,13305,13306,13308,13311,13313,13315,13317],{"class":5503,"line":5552},[5501,13307,6869],{"class":5614},[5501,13309,13310],{"class":5511},".fc = nn.Linear(",[5501,13312,6875],{"class":5543},[5501,13314,6368],{"class":5511},[5501,13316,6222],{"class":5543},[5501,13318,5622],{"class":5511},[5501,13320,13321],{"class":5503,"line":5558},[5501,13322,5732],{"class":5511},[5501,13324,13325,13327,13329,13331,13333,13335,13337],{"class":5503,"line":5564},[5501,13326,6839],{"class":5614},[5501,13328,6924],{"class":5607},[5501,13330,5611],{"class":5511},[5501,13332,6848],{"class":6847},[5501,13334,6368],{"class":5511},[5501,13336,6933],{"class":6847},[5501,13338,6834],{"class":5511},[5501,13340,13341],{"class":5503,"line":5570},[5501,13342,13343],{"class":5533},"        # Умовна логіка\n",[5501,13345,13346,13349,13351,13353],{"class":5503,"line":5575},[5501,13347,13348],{"class":5507},"        if",[5501,13350,13177],{"class":5511},[5501,13352,5828],{"class":5543},[5501,13354,5893],{"class":5511},[5501,13356,13357,13360],{"class":5503,"line":5581},[5501,13358,13359],{"class":5511},"            x = x * ",[5501,13361,13195],{"class":5543},[5501,13363,13364,13366,13368],{"class":5503,"line":5587},[5501,13365,6940],{"class":5511},[5501,13367,6848],{"class":5614},[5501,13369,13370],{"class":5511},".fc(x))\n",[5501,13372,13373,13375],{"class":5503,"line":5593},[5501,13374,6969],{"class":5507},[5501,13376,6972],{"class":5511},[5501,13378,13379],{"class":5503,"line":5599},[5501,13380,5527],{"emptyLinePlaceholder":5526},[5501,13382,13383],{"class":5503,"line":5604},[5501,13384,13385],{"class":5511},"model = ConditionalModel()\n",[5501,13387,13388],{"class":5503,"line":5625},[5501,13389,5527],{"emptyLinePlaceholder":5526},[5501,13391,13392],{"class":5503,"line":5660},[5501,13393,13394],{"class":5533},"# ✅ Scripting: парсить Python код\n",[5501,13396,13397],{"class":5503,"line":5691},[5501,13398,13399],{"class":5511},"scripted_model = torch.jit.script(model)\n",[5501,13401,13402],{"class":5503,"line":5696},[5501,13403,5527],{"emptyLinePlaceholder":5526},[5501,13405,13406,13409,13412],{"class":5503,"line":5702},[5501,13407,13408],{"class":5511},"scripted_model.save(",[5501,13410,13411],{"class":5618},"'model_scripted.pt'",[5501,13413,5622],{"class":5511},[5501,13415,13416,13418,13420,13423,13425,13427],{"class":5503,"line":5711},[5501,13417,5608],{"class":5607},[5501,13419,5611],{"class":5511},[5501,13421,13422],{"class":5618},"\"✓ TorchScript модель (scripted) збережено",[5501,13424,5684],{"class":5683},[5501,13426,5655],{"class":5618},[5501,13428,5622],{"class":5511},[5501,13430,13431],{"class":5503,"line":5717},[5501,13432,5527],{"emptyLinePlaceholder":5526},[5501,13434,13435],{"class":5503,"line":5723},[5501,13436,13437],{"class":5533},"# Перевірка з різними входами\n",[5501,13439,13440,13443,13445,13447,13449,13452,13454],{"class":5503,"line":5729},[5501,13441,13442],{"class":5511},"x_positive = torch.randn(",[5501,13444,5490],{"class":5543},[5501,13446,6368],{"class":5511},[5501,13448,6875],{"class":5543},[5501,13450,13451],{"class":5511},") + ",[5501,13453,7244],{"class":5543},[5501,13455,13456],{"class":5533},"  # сума > 0\n",[5501,13458,13459,13462,13464,13466,13468,13471,13473],{"class":5503,"line":5735},[5501,13460,13461],{"class":5511},"x_negative = torch.randn(",[5501,13463,5490],{"class":5543},[5501,13465,6368],{"class":5511},[5501,13467,6875],{"class":5543},[5501,13469,13470],{"class":5511},") - ",[5501,13472,7244],{"class":5543},[5501,13474,13475],{"class":5533},"  # сума \u003C 0\n",[5501,13477,13478],{"class":5503,"line":5741},[5501,13479,5527],{"emptyLinePlaceholder":5526},[5501,13481,13482,13484,13486],{"class":5503,"line":5747},[5501,13483,13008],{"class":5511},[5501,13485,13411],{"class":5618},[5501,13487,5622],{"class":5511},[5501,13489,13490],{"class":5503,"line":5753},[5501,13491,5527],{"emptyLinePlaceholder":5526},[5501,13493,13494,13496,13498,13500,13503,13505,13508,13510,13512],{"class":5503,"line":5758},[5501,13495,5608],{"class":5607},[5501,13497,5611],{"class":5511},[5501,13499,5615],{"class":5614},[5501,13501,13502],{"class":5618},"\"Вхід (сума > 0): ",[5501,13504,5637],{"class":5614},[5501,13506,13507],{"class":5511},"loaded_model(x_positive).sum()",[5501,13509,7814],{"class":5614},[5501,13511,5655],{"class":5618},[5501,13513,5622],{"class":5511},[5501,13515,13516,13518,13520,13522,13525,13527,13530,13532,13534],{"class":5503,"line":5764},[5501,13517,5608],{"class":5607},[5501,13519,5611],{"class":5511},[5501,13521,5615],{"class":5614},[5501,13523,13524],{"class":5618},"\"Вхід (сума \u003C 0): ",[5501,13526,5637],{"class":5614},[5501,13528,13529],{"class":5511},"loaded_model(x_negative).sum()",[5501,13531,7814],{"class":5614},[5501,13533,5655],{"class":5618},[5501,13535,5622],{"class":5511},[5501,13537,13538,13540,13542,13544,13546,13549],{"class":5503,"line":5770},[5501,13539,5608],{"class":5607},[5501,13541,5611],{"class":5511},[5501,13543,5655],{"class":5618},[5501,13545,5684],{"class":5683},[5501,13547,13548],{"class":5618},"✓ Умовна логіка працює коректно\"",[5501,13550,5622],{"class":5511},[5907,13552,13553],{"v-slot:output":5497},[5910,13554,13555,13574],{},[5913,13556,13557],{},[5916,13558,13559,13562,13565,13568,13571],{},[5919,13560,13561],{"align":5925},"Тестовий вхід $X$",[5919,13563,13564],{"align":5925},"Умова в моделі ($X.\\text{sum}() > 0$)",[5919,13566,13567],{"align":5925},"Результат PyTorch",[5919,13569,13570],{"align":5925},"Результат Scripted",[5919,13572,13573],{"align":5925},"Збіг",[5934,13575,13576,13602],{},[5916,13577,13578,13584,13590,13595,13599],{},[5939,13579,13580,13583],{"align":5925},[5289,13581,13582],{},"[ 1., 2., 3.]"," ($>0$)",[5939,13585,13586,13587],{"align":5925},"Гілка ",[5289,13588,13589],{},"x * 2",[5939,13591,13592],{"align":5925},[5289,13593,13594],{},"[2., 4., 6.]",[5939,13596,13597],{"align":5925},[5289,13598,13594],{},[5939,13600,13601],{"align":5925},"✅ Збігається",[5916,13603,13604,13610,13615,13620,13624],{},[5939,13605,13606,13609],{"align":5925},[5289,13607,13608],{},"[-1., -2., -3.]"," ($\\le 0$)",[5939,13611,13586,13612],{"align":5925},[5289,13613,13614],{},"x * 0",[5939,13616,13617],{"align":5925},[5289,13618,13619],{},"[0., 0., 0.]",[5939,13621,13622],{"align":5925},[5289,13623,13619],{},[5939,13625,13601],{"align":5925},[6694,13627,13628,13633,13685],{},[5268,13629,13630],{},[5220,13631,13632],{},"Коли використовувати кожен метод:",[5910,13634,13635,13651],{},[5913,13636,13637],{},[5916,13638,13639,13642,13645,13648],{},[5919,13640,13641],{"align":5921},"Метод",[5919,13643,13644],{"align":5921},"Переваги",[5919,13646,13647],{"align":5921},"Недоліки",[5919,13649,13650],{"align":5921},"Використання",[5934,13652,13653,13669],{},[5916,13654,13655,13660,13663,13666],{},[5939,13656,13657],{"align":5921},[5220,13658,13659],{},"Trace",[5939,13661,13662],{"align":5921},"Швидший, простіший",[5939,13664,13665],{"align":5921},"Не підтримує умови\u002Fцикли",[5939,13667,13668],{"align":5921},"Feed-forward, CNN, MLP",[5916,13670,13671,13676,13679,13682],{},[5939,13672,13673],{"align":5921},[5220,13674,13675],{},"Script",[5939,13677,13678],{"align":5921},"Підтримує умови, цикли",[5939,13680,13681],{"align":5921},"Повільніший, можливі помилки парсингу",[5939,13683,13684],{"align":5921},"RNN, Transformers з dynamic shapes",[5268,13686,13687,13689],{},[5220,13688,6732],{}," Спробуйте trace спочатку. Якщо виникають проблеми — використовуйте script.",[5340,13691,13693],{"id":13692},"onnx-міжплатформенний-формат","ONNX — міжплатформенний формат",[5268,13695,13696,13699],{},[5220,13697,13698],{},"ONNX (Open Neural Network Exchange)"," — відкритий формат для обміну моделями між різними фреймворками.",[8920,13701,13703],{"alt":13702},"Екосистема ONNX",[5492,13704,13706],{"className":8925,"code":13705,"language":8927,"meta":5497,"style":5497},"@startuml\nskinparam style plain\nskinparam backgroundColor #FFFFFF\n\nrectangle \"PyTorch Model\" as pytorch #DBEAFE\nrectangle \"ONNX Format\" as onnx #FEF3C7\nrectangle \"TensorFlow\" as tf #DCFCE7\nrectangle \"TensorRT\\n(NVIDIA)\" as trt #E2E8F0\nrectangle \"CoreML\\n(Apple)\" as coreml #DBEAFE\nrectangle \"ONNX Runtime\\n(Browser, Mobile)\" as runtime #DCFCE7\n\npytorch --> onnx : torch.onnx.export()\nonnx --> tf : ONNX → TF converter\nonnx --> trt : TensorRT optimizer\nonnx --> coreml : ONNX → CoreML\nonnx --> runtime : Deployment\n\nnote right of onnx #FEF3C7\n  Універсальний формат\n  для всіх платформ\nend note\n\n@enduml\n",[5289,13707,13708,13712,13716,13720,13724,13729,13734,13739,13744,13749,13754,13758,13763,13768,13773,13778,13783,13787,13792,13797,13802,13806,13810],{"__ignoreMap":5497},[5501,13709,13710],{"class":5503,"line":5504},[5501,13711,8934],{},[5501,13713,13714],{"class":5503,"line":5515},[5501,13715,8939],{},[5501,13717,13718],{"class":5503,"line":5523},[5501,13719,8944],{},[5501,13721,13722],{"class":5503,"line":5530},[5501,13723,5527],{"emptyLinePlaceholder":5526},[5501,13725,13726],{"class":5503,"line":5537},[5501,13727,13728],{},"rectangle \"PyTorch Model\" as pytorch #DBEAFE\n",[5501,13730,13731],{"class":5503,"line":5547},[5501,13732,13733],{},"rectangle \"ONNX Format\" as onnx #FEF3C7\n",[5501,13735,13736],{"class":5503,"line":5552},[5501,13737,13738],{},"rectangle \"TensorFlow\" as tf #DCFCE7\n",[5501,13740,13741],{"class":5503,"line":5558},[5501,13742,13743],{},"rectangle \"TensorRT\\n(NVIDIA)\" as trt #E2E8F0\n",[5501,13745,13746],{"class":5503,"line":5564},[5501,13747,13748],{},"rectangle \"CoreML\\n(Apple)\" as coreml #DBEAFE\n",[5501,13750,13751],{"class":5503,"line":5570},[5501,13752,13753],{},"rectangle \"ONNX Runtime\\n(Browser, Mobile)\" as runtime #DCFCE7\n",[5501,13755,13756],{"class":5503,"line":5575},[5501,13757,5527],{"emptyLinePlaceholder":5526},[5501,13759,13760],{"class":5503,"line":5581},[5501,13761,13762],{},"pytorch --> onnx : torch.onnx.export()\n",[5501,13764,13765],{"class":5503,"line":5587},[5501,13766,13767],{},"onnx --> tf : ONNX → TF converter\n",[5501,13769,13770],{"class":5503,"line":5593},[5501,13771,13772],{},"onnx --> trt : TensorRT optimizer\n",[5501,13774,13775],{"class":5503,"line":5599},[5501,13776,13777],{},"onnx --> coreml : ONNX → CoreML\n",[5501,13779,13780],{"class":5503,"line":5604},[5501,13781,13782],{},"onnx --> runtime : Deployment\n",[5501,13784,13785],{"class":5503,"line":5625},[5501,13786,5527],{"emptyLinePlaceholder":5526},[5501,13788,13789],{"class":5503,"line":5660},[5501,13790,13791],{},"note right of onnx #FEF3C7\n",[5501,13793,13794],{"class":5503,"line":5691},[5501,13795,13796],{},"  Універсальний формат\n",[5501,13798,13799],{"class":5503,"line":5696},[5501,13800,13801],{},"  для всіх платформ\n",[5501,13803,13804],{"class":5503,"line":5702},[5501,13805,9031],{},[5501,13807,13808],{"class":5503,"line":5711},[5501,13809,5527],{"emptyLinePlaceholder":5526},[5501,13811,13812],{"class":5503,"line":5717},[5501,13813,9063],{},[6770,13815,13817],{"id":13816},"експорт-моделі-у-onnx","Експорт моделі у ONNX",[5484,13819,13821],{"title":13820},"onnx_export.ipynb",[5488,13822,13823,14404],{"execution-count":5490},[5492,13824,13826],{"className":5494,"code":13825,"language":5496,"meta":5497,"style":5497},"import torch\nimport torch.nn as nn\n\nclass MyModel(nn.Module):\n    def __init__(self):\n        super().__init__()\n        self.conv = nn.Conv2d(3, 16, kernel_size=3, padding=1)\n        self.pool = nn.MaxPool2d(2, 2)\n        self.fc = nn.Linear(16 * 16 * 16, 10)\n    \n    def forward(self, x):\n        x = torch.relu(self.conv(x))\n        x = self.pool(x)\n        x = x.view(x.size(0), -1)\n        x = self.fc(x)\n        return x\n\nmodel = MyModel()\nmodel.eval()\n\n# Приклад входу (batch_size=1, channels=3, height=32, width=32)\ndummy_input = torch.randn(1, 3, 32, 32)\n\n# ✅ Експорт у ONNX\ntorch.onnx.export(\n    model,                      # модель\n    dummy_input,                # приклад входу\n    'model.onnx',               # шлях до файлу\n    input_names=['input'],      # імена входів\n    output_names=['output'],    # імена виходів\n    dynamic_axes={              # динамічні розміри (для різних batch_size)\n        'input': {0: 'batch_size'},\n        'output': {0: 'batch_size'}\n    },\n    opset_version=14            # версія ONNX операцій\n)\n\nprint(\"✓ Модель експортовано у ONNX\\n\")\n\n# Перевірка через ONNX Runtime\ntry:\n    import onnxruntime as ort\n    \n    session = ort.InferenceSession('model.onnx')\n    \n    # Inference\n    ort_inputs = {session.get_inputs()[0].name: dummy_input.numpy()}\n    ort_outputs = session.run(None, ort_inputs)\n    \n    # Порівняння з PyTorch\n    pytorch_output = model(dummy_input).detach().numpy()\n    \n    diff = abs(pytorch_output - ort_outputs[0]).max()\n    print(f\"Максимальна різниця PyTorch vs ONNX: {diff:.6f}\")\n    print(\"✓ ONNX модель працює коректно\")\n    \nexcept ImportError:\n    print(\"⚠ Встановіть onnxruntime для перевірки:\")\n    print(\"  pip install onnxruntime\")\n",[5289,13827,13828,13834,13844,13848,13864,13876,13886,13920,13935,13958,13962,13978,13987,13996,14010,14019,14025,14029,14034,14038,14042,14047,14068,14072,14077,14082,14090,14098,14109,14126,14142,14153,14171,14186,14191,14204,14208,14212,14227,14231,14236,14243,14256,14260,14270,14274,14279,14289,14300,14304,14309,14314,14318,14334,14357,14368,14372,14382,14393],{"__ignoreMap":5497},[5501,13829,13830,13832],{"class":5503,"line":5504},[5501,13831,5508],{"class":5507},[5501,13833,5512],{"class":5511},[5501,13835,13836,13838,13840,13842],{"class":5503,"line":5515},[5501,13837,5508],{"class":5507},[5501,13839,6796],{"class":5511},[5501,13841,6799],{"class":5507},[5501,13843,6802],{"class":5511},[5501,13845,13846],{"class":5503,"line":5523},[5501,13847,5527],{"emptyLinePlaceholder":5526},[5501,13849,13850,13852,13854,13856,13858,13860,13862],{"class":5503,"line":5530},[5501,13851,6816],{"class":5614},[5501,13853,11386],{"class":6819},[5501,13855,5611],{"class":5511},[5501,13857,6825],{"class":6819},[5501,13859,6828],{"class":5511},[5501,13861,6831],{"class":6819},[5501,13863,6834],{"class":5511},[5501,13865,13866,13868,13870,13872,13874],{"class":5503,"line":5537},[5501,13867,6839],{"class":5614},[5501,13869,6842],{"class":5607},[5501,13871,5611],{"class":5511},[5501,13873,6848],{"class":6847},[5501,13875,6834],{"class":5511},[5501,13877,13878,13880,13882,13884],{"class":5503,"line":5547},[5501,13879,6855],{"class":6819},[5501,13881,6858],{"class":5511},[5501,13883,6861],{"class":5607},[5501,13885,6864],{"class":5511},[5501,13887,13888,13890,13893,13895,13897,13900,13902,13905,13907,13909,13911,13914,13916,13918],{"class":5503,"line":5552},[5501,13889,6869],{"class":5614},[5501,13891,13892],{"class":5511},".conv = nn.Conv2d(",[5501,13894,6222],{"class":5543},[5501,13896,6368],{"class":5511},[5501,13898,13899],{"class":5543},"16",[5501,13901,6368],{"class":5511},[5501,13903,13904],{"class":6847},"kernel_size",[5501,13906,7455],{"class":5511},[5501,13908,6222],{"class":5543},[5501,13910,6368],{"class":5511},[5501,13912,13913],{"class":6847},"padding",[5501,13915,7455],{"class":5511},[5501,13917,5490],{"class":5543},[5501,13919,5622],{"class":5511},[5501,13921,13922,13924,13927,13929,13931,13933],{"class":5503,"line":5558},[5501,13923,6869],{"class":5614},[5501,13925,13926],{"class":5511},".pool = nn.MaxPool2d(",[5501,13928,6347],{"class":5543},[5501,13930,6368],{"class":5511},[5501,13932,6347],{"class":5543},[5501,13934,5622],{"class":5511},[5501,13936,13937,13939,13941,13943,13946,13948,13950,13952,13954,13956],{"class":5503,"line":5564},[5501,13938,6869],{"class":5614},[5501,13940,13310],{"class":5511},[5501,13942,13899],{"class":5543},[5501,13944,13945],{"class":5511}," * ",[5501,13947,13899],{"class":5543},[5501,13949,13945],{"class":5511},[5501,13951,13899],{"class":5543},[5501,13953,6368],{"class":5511},[5501,13955,6875],{"class":5543},[5501,13957,5622],{"class":5511},[5501,13959,13960],{"class":5503,"line":5570},[5501,13961,5732],{"class":5511},[5501,13963,13964,13966,13968,13970,13972,13974,13976],{"class":5503,"line":5575},[5501,13965,6839],{"class":5614},[5501,13967,6924],{"class":5607},[5501,13969,5611],{"class":5511},[5501,13971,6848],{"class":6847},[5501,13973,6368],{"class":5511},[5501,13975,6933],{"class":6847},[5501,13977,6834],{"class":5511},[5501,13979,13980,13982,13984],{"class":5503,"line":5581},[5501,13981,6940],{"class":5511},[5501,13983,6848],{"class":5614},[5501,13985,13986],{"class":5511},".conv(x))\n",[5501,13988,13989,13991,13993],{"class":5503,"line":5587},[5501,13990,6959],{"class":5511},[5501,13992,6848],{"class":5614},[5501,13994,13995],{"class":5511},".pool(x)\n",[5501,13997,13998,14001,14003,14006,14008],{"class":5503,"line":5593},[5501,13999,14000],{"class":5511},"        x = x.view(x.size(",[5501,14002,5828],{"class":5543},[5501,14004,14005],{"class":5511},"), -",[5501,14007,5490],{"class":5543},[5501,14009,5622],{"class":5511},[5501,14011,14012,14014,14016],{"class":5503,"line":5599},[5501,14013,6959],{"class":5511},[5501,14015,6848],{"class":5614},[5501,14017,14018],{"class":5511},".fc(x)\n",[5501,14020,14021,14023],{"class":5503,"line":5604},[5501,14022,6969],{"class":5507},[5501,14024,6972],{"class":5511},[5501,14026,14027],{"class":5503,"line":5625},[5501,14028,5527],{"emptyLinePlaceholder":5526},[5501,14030,14031],{"class":5503,"line":5660},[5501,14032,14033],{"class":5511},"model = MyModel()\n",[5501,14035,14036],{"class":5503,"line":5691},[5501,14037,12933],{"class":5511},[5501,14039,14040],{"class":5503,"line":5696},[5501,14041,5527],{"emptyLinePlaceholder":5526},[5501,14043,14044],{"class":5503,"line":5702},[5501,14045,14046],{"class":5533},"# Приклад входу (batch_size=1, channels=3, height=32, width=32)\n",[5501,14048,14049,14052,14054,14056,14058,14060,14062,14064,14066],{"class":5503,"line":5711},[5501,14050,14051],{"class":5511},"dummy_input = torch.randn(",[5501,14053,5490],{"class":5543},[5501,14055,6368],{"class":5511},[5501,14057,6222],{"class":5543},[5501,14059,6368],{"class":5511},[5501,14061,6896],{"class":5543},[5501,14063,6368],{"class":5511},[5501,14065,6896],{"class":5543},[5501,14067,5622],{"class":5511},[5501,14069,14070],{"class":5503,"line":5717},[5501,14071,5527],{"emptyLinePlaceholder":5526},[5501,14073,14074],{"class":5503,"line":5723},[5501,14075,14076],{"class":5533},"# ✅ Експорт у ONNX\n",[5501,14078,14079],{"class":5503,"line":5729},[5501,14080,14081],{"class":5511},"torch.onnx.export(\n",[5501,14083,14084,14087],{"class":5503,"line":5735},[5501,14085,14086],{"class":5511},"    model,                      ",[5501,14088,14089],{"class":5533},"# модель\n",[5501,14091,14092,14095],{"class":5503,"line":5741},[5501,14093,14094],{"class":5511},"    dummy_input,                ",[5501,14096,14097],{"class":5533},"# приклад входу\n",[5501,14099,14100,14103,14106],{"class":5503,"line":5747},[5501,14101,14102],{"class":5618},"    'model.onnx'",[5501,14104,14105],{"class":5511},",               ",[5501,14107,14108],{"class":5533},"# шлях до файлу\n",[5501,14110,14111,14114,14117,14120,14123],{"class":5503,"line":5753},[5501,14112,14113],{"class":6847},"    input_names",[5501,14115,14116],{"class":5511},"=[",[5501,14118,14119],{"class":5618},"'input'",[5501,14121,14122],{"class":5511},"],      ",[5501,14124,14125],{"class":5533},"# імена входів\n",[5501,14127,14128,14131,14133,14136,14139],{"class":5503,"line":5758},[5501,14129,14130],{"class":6847},"    output_names",[5501,14132,14116],{"class":5511},[5501,14134,14135],{"class":5618},"'output'",[5501,14137,14138],{"class":5511},"],    ",[5501,14140,14141],{"class":5533},"# імена виходів\n",[5501,14143,14144,14147,14150],{"class":5503,"line":5764},[5501,14145,14146],{"class":6847},"    dynamic_axes",[5501,14148,14149],{"class":5511},"={              ",[5501,14151,14152],{"class":5533},"# динамічні розміри (для різних batch_size)\n",[5501,14154,14155,14158,14161,14163,14165,14168],{"class":5503,"line":5770},[5501,14156,14157],{"class":5618},"        'input'",[5501,14159,14160],{"class":5511},": {",[5501,14162,5828],{"class":5543},[5501,14164,10226],{"class":5511},[5501,14166,14167],{"class":5618},"'batch_size'",[5501,14169,14170],{"class":5511},"},\n",[5501,14172,14173,14176,14178,14180,14182,14184],{"class":5503,"line":5776},[5501,14174,14175],{"class":5618},"        'output'",[5501,14177,14160],{"class":5511},[5501,14179,5828],{"class":5543},[5501,14181,10226],{"class":5511},[5501,14183,14167],{"class":5618},[5501,14185,12256],{"class":5511},[5501,14187,14188],{"class":5503,"line":5785},[5501,14189,14190],{"class":5511},"    },\n",[5501,14192,14193,14196,14198,14201],{"class":5503,"line":5791},[5501,14194,14195],{"class":6847},"    opset_version",[5501,14197,7455],{"class":5511},[5501,14199,14200],{"class":5543},"14",[5501,14202,14203],{"class":5533},"            # версія ONNX операцій\n",[5501,14205,14206],{"class":5503,"line":5796},[5501,14207,5622],{"class":5511},[5501,14209,14210],{"class":5503,"line":5811},[5501,14211,5527],{"emptyLinePlaceholder":5526},[5501,14213,14214,14216,14218,14221,14223,14225],{"class":5503,"line":5839},[5501,14215,5608],{"class":5607},[5501,14217,5611],{"class":5511},[5501,14219,14220],{"class":5618},"\"✓ Модель експортовано у ONNX",[5501,14222,5684],{"class":5683},[5501,14224,5655],{"class":5618},[5501,14226,5622],{"class":5511},[5501,14228,14229],{"class":5503,"line":5862},[5501,14230,5527],{"emptyLinePlaceholder":5526},[5501,14232,14233],{"class":5503,"line":5887},[5501,14234,14235],{"class":5533},"# Перевірка через ONNX Runtime\n",[5501,14237,14238,14241],{"class":5503,"line":5896},[5501,14239,14240],{"class":5507},"try",[5501,14242,5893],{"class":5511},[5501,14244,14245,14248,14251,14253],{"class":5503,"line":7693},[5501,14246,14247],{"class":5507},"    import",[5501,14249,14250],{"class":5511}," onnxruntime ",[5501,14252,6799],{"class":5507},[5501,14254,14255],{"class":5511}," ort\n",[5501,14257,14258],{"class":5503,"line":7699},[5501,14259,5732],{"class":5511},[5501,14261,14262,14265,14268],{"class":5503,"line":7705},[5501,14263,14264],{"class":5511},"    session = ort.InferenceSession(",[5501,14266,14267],{"class":5618},"'model.onnx'",[5501,14269,5622],{"class":5511},[5501,14271,14272],{"class":5503,"line":7711},[5501,14273,5732],{"class":5511},[5501,14275,14276],{"class":5503,"line":7717},[5501,14277,14278],{"class":5533},"    # Inference\n",[5501,14280,14281,14284,14286],{"class":5503,"line":7723},[5501,14282,14283],{"class":5511},"    ort_inputs = {session.get_inputs()[",[5501,14285,5828],{"class":5543},[5501,14287,14288],{"class":5511},"].name: dummy_input.numpy()}\n",[5501,14290,14291,14294,14297],{"class":5503,"line":7729},[5501,14292,14293],{"class":5511},"    ort_outputs = session.run(",[5501,14295,14296],{"class":5614},"None",[5501,14298,14299],{"class":5511},", ort_inputs)\n",[5501,14301,14302],{"class":5503,"line":7735},[5501,14303,5732],{"class":5511},[5501,14305,14306],{"class":5503,"line":7741},[5501,14307,14308],{"class":5533},"    # Порівняння з PyTorch\n",[5501,14310,14311],{"class":5503,"line":7747},[5501,14312,14313],{"class":5511},"    pytorch_output = model(dummy_input).detach().numpy()\n",[5501,14315,14316],{"class":5503,"line":7752},[5501,14317,5732],{"class":5511},[5501,14319,14320,14323,14326,14329,14331],{"class":5503,"line":7758},[5501,14321,14322],{"class":5511},"    diff = ",[5501,14324,14325],{"class":5607},"abs",[5501,14327,14328],{"class":5511},"(pytorch_output - ort_outputs[",[5501,14330,5828],{"class":5543},[5501,14332,14333],{"class":5511},"]).max()\n",[5501,14335,14336,14338,14340,14342,14345,14347,14350,14353,14355],{"class":5503,"line":7763},[5501,14337,5799],{"class":5607},[5501,14339,5611],{"class":5511},[5501,14341,5615],{"class":5614},[5501,14343,14344],{"class":5618},"\"Максимальна різниця PyTorch vs ONNX: ",[5501,14346,5637],{"class":5614},[5501,14348,14349],{"class":5511},"diff",[5501,14351,14352],{"class":5614},":.6f}",[5501,14354,5655],{"class":5618},[5501,14356,5622],{"class":5511},[5501,14358,14359,14361,14363,14366],{"class":5503,"line":7775},[5501,14360,5799],{"class":5607},[5501,14362,5611],{"class":5511},[5501,14364,14365],{"class":5618},"\"✓ ONNX модель працює коректно\"",[5501,14367,5622],{"class":5511},[5501,14369,14370],{"class":5503,"line":7821},[5501,14371,5732],{"class":5511},[5501,14373,14374,14377,14380],{"class":5503,"line":7826},[5501,14375,14376],{"class":5507},"except",[5501,14378,14379],{"class":6819}," ImportError",[5501,14381,5893],{"class":5511},[5501,14383,14384,14386,14388,14391],{"class":5503,"line":9566},[5501,14385,5799],{"class":5607},[5501,14387,5611],{"class":5511},[5501,14389,14390],{"class":5618},"\"⚠ Встановіть onnxruntime для перевірки:\"",[5501,14392,5622],{"class":5511},[5501,14394,14395,14397,14399,14402],{"class":5503,"line":9578},[5501,14396,5799],{"class":5607},[5501,14398,5611],{"class":5511},[5501,14400,14401],{"class":5618},"\"  pip install onnxruntime\"",[5501,14403,5622],{"class":5511},[5907,14405,14406],{"v-slot:output":5497},[5910,14407,14408,14424],{},[5913,14409,14410],{},[5916,14411,14412,14415,14418,14421],{},[5919,14413,14414],{"align":5921},"Середовище виконання",[5919,14416,14417],{"align":5921},"Формат моделі",[5919,14419,14420],{"align":5925},"Максимальна чисельна розбіжність ($\\Delta_{\\max}$)",[5919,14422,14423],{"align":5921},"Статус інтеграції",[5934,14425,14426,14444],{},[5916,14427,14428,14436,14439,14441],{},[5939,14429,14430],{"align":5921},[5220,14431,14432,14433,5227],{},"PyTorch (",[5289,14434,14435],{},"torch.nn.Module",[5939,14437,14438],{"align":5921},"Python \u002F PyTorch runtime",[5939,14440,8831],{"align":5925},[5939,14442,14443],{"align":5921},"Еталонне значення",[5916,14445,14446,14454,14460,14468],{},[5939,14447,14448],{"align":5921},[5220,14449,14450,14451,5227],{},"ONNX Runtime (",[5289,14452,14453],{},"onnxruntime",[5939,14455,14456,14459],{"align":5921},[5289,14457,14458],{},"model.onnx"," Graph",[5939,14461,14462,14467],{"align":5925},[5220,14463,14464],{},[5289,14465,14466],{},"0.0000000"," ($\u003C 10^{-7}$)",[5939,14469,9893,14470],{"align":5921},[5220,14471,14472],{},"Готово до кросплатформного деплою",[5987,14474,14475,14480],{},[5268,14476,14477],{},[5220,14478,14479],{},"Куди можна deployment ONNX моделі:",[5910,14481,14482,14494],{},[5913,14483,14484],{},[5916,14485,14486,14489,14492],{},[5919,14487,14488],{"align":5921},"Платформа",[5919,14490,14491],{"align":5921},"Інструмент",[5919,14493,13650],{"align":5921},[5934,14495,14496,14509,14522,14535,14548,14561],{},[5916,14497,14498,14503,14506],{},[5939,14499,14500],{"align":5921},[5220,14501,14502],{},"iOS\u002FmacOS",[5939,14504,14505],{"align":5921},"CoreML",[5939,14507,14508],{"align":5921},"Нативні застосунки Apple",[5916,14510,14511,14516,14519],{},[5939,14512,14513],{"align":5921},[5220,14514,14515],{},"Android",[5939,14517,14518],{"align":5921},"TensorFlow Lite",[5939,14520,14521],{"align":5921},"Мобільні застосунки",[5916,14523,14524,14529,14532],{},[5939,14525,14526],{"align":5921},[5220,14527,14528],{},"NVIDIA GPU",[5939,14530,14531],{"align":5921},"TensorRT",[5939,14533,14534],{"align":5921},"Серверний inference (швидкість)",[5916,14536,14537,14542,14545],{},[5939,14538,14539],{"align":5921},[5220,14540,14541],{},"Браузер",[5939,14543,14544],{"align":5921},"ONNX.js",[5939,14546,14547],{"align":5921},"WebAssembly у браузері",[5916,14549,14550,14555,14558],{},[5939,14551,14552],{"align":5921},[5220,14553,14554],{},"Edge devices",[5939,14556,14557],{"align":5921},"ONNX Runtime",[5939,14559,14560],{"align":5921},"Raspberry Pi, IoT",[5916,14562,14563,14568,14570],{},[5939,14564,14565],{"align":5921},[5220,14566,14567],{},"C++\u002FPython",[5939,14569,14557],{"align":5921},[5939,14571,14572],{"align":5921},"Без залежності від PyTorch",[5333,14574],{},[5263,14576,14578],{"id":14577},"резюме","Резюме",[5186,14580,14581,14602,14625,14652,14673],{},[5189,14582,14584],{"icon":92,"title":14583},"🚀 GPU",[5194,14585,14586,14589,14594,14599],{},[5197,14587,14588],{},"Прискорення у 20-100× для матричних операцій",[5197,14590,14591,14593],{},[5289,14592,6706],{}," для переміщення тензорів та моделей",[5197,14595,14596,14598],{},[5289,14597,7975],{}," у DataLoader для прискорення",[5197,14600,14601],{},"Дані та модель мають бути на одному пристрої",[5189,14603,14605],{"icon":255,"title":14604},"⚡ Mixed Precision",[5194,14606,14607,14610,14613,14622],{},[5197,14608,14609],{},"Економія пам'яті у 2× (FP16 замість FP32)",[5197,14611,14612],{},"Прискорення у 1.5-3× на Tensor Cores",[5197,14614,14615,14618,14619],{},[5289,14616,14617],{},"autocast()"," + ",[5289,14620,14621],{},"GradScaler()",[5197,14623,14624],{},"Мінімальна втрата точності",[5189,14626,14629],{"icon":14627,"title":14628},"i-lucide-gauge","📊 Оптимізація",[5194,14630,14631,14637,14643,14649],{},[5197,14632,14633,14634],{},"Профілювання через ",[5289,14635,14636],{},"torch.profiler",[5197,14638,14639,14642],{},[5289,14640,14641],{},"num_workers=4-8"," для DataLoader",[5197,14644,14645,14648],{},[5289,14646,14647],{},"persistent_workers=True"," для довгих тренувань",[5197,14650,14651],{},"Бенчмарки для знаходження bottleneck",[5189,14653,14656],{"icon":14654,"title":14655},"i-lucide-save","💾 Збереження",[5194,14657,14658,14664,14667,14670],{},[5197,14659,14660,14663],{},[5289,14661,14662],{},"state_dict()"," — рекомендований спосіб",[5197,14665,14666],{},"Checkpoint для відновлення тренування",[5197,14668,14669],{},"Зберігати епоху, optimizer state, метрики",[5197,14671,14672],{},"НЕ використовувати повне збереження моделі",[5189,14674,14676],{"icon":4409,"title":14675},"📦 Deployment",[5194,14677,14678,14684,14690,14696],{},[5197,14679,14680,14683],{},[5220,14681,14682],{},"TorchScript:"," trace (прості моделі) або script (з умовами)",[5197,14685,14686,14689],{},[5220,14687,14688],{},"ONNX:"," міжплатформенний формат",[5197,14691,14692,14695],{},[5289,14693,14694],{},"model.eval()"," перед deployment",[5197,14697,14698],{},"Batch inference для ефективності",[14700,14701,14702,14752,14800,14862],"accordion",{},[14703,14704,14707,14710,14715,14733,14738,14749],"accordion-item",{"icon":14705,"label":14706},"i-lucide-help-circle","❓ Чи можна тренувати на кількох GPU одночасно?",[5268,14708,14709],{},"Так! PyTorch підтримує два підходи:",[5268,14711,14712],{},[5220,14713,14714],{},"1. DataParallel (простіше, але повільніше):",[5492,14716,14718],{"className":5494,"code":14717,"language":5496,"meta":5497,"style":5497},"model = nn.DataParallel(model)\nmodel = model.to('cuda')\n",[5289,14719,14720,14725],{"__ignoreMap":5497},[5501,14721,14722],{"class":5503,"line":5504},[5501,14723,14724],{"class":5511},"model = nn.DataParallel(model)\n",[5501,14726,14727,14729,14731],{"class":5503,"line":5515},[5501,14728,7232],{"class":5511},[5501,14730,6538],{"class":5618},[5501,14732,5622],{"class":5511},[5268,14734,14735],{},[5220,14736,14737],{},"2. DistributedDataParallel (складніше, але швидше):",[5194,14739,14740,14743,14746],{},[5197,14741,14742],{},"Потребує більше налаштувань",[5197,14744,14745],{},"Рекомендований для production",[5197,14747,14748],{},"Детальніше у офіційній документації PyTorch",[5268,14750,14751],{},"Для навчання це виходить за межі базового курсу, але важливо знати, що така можливість існує.",[14703,14753,14755,14760,14763,14766,14780,14786,14794],{"icon":14705,"label":14754},"❓ Скільки пам'яті GPU потрібно для тренування моделі?",[5268,14756,14757],{},[5220,14758,14759],{},"Формула (приблизно):",[8152,14761],{"tex":14762},"\\text{GPU memory} \\approx 4 \\times \\text{параметрів} \\times \\text{batch size}",[5268,14764,14765],{},"Де множник 4 враховує:",[5194,14767,14768,14771,14774,14777],{},[5197,14769,14770],{},"Параметри моделі (FP32 = 4 байти)",[5197,14772,14773],{},"Градієнти (ще 4 байти на параметр)",[5197,14775,14776],{},"Optimizer states (Adam зберігає 2 моменти = 8 байтів)",[5197,14778,14779],{},"Активації (залежить від batch size)",[5268,14781,14782,14785],{},[5220,14783,14784],{},"Приклад:"," Модель з 10M параметрів, batch_size=32:",[5194,14787,14788,14791],{},[5197,14789,14790],{},"Мінімум: ~1.5 GB",[5197,14792,14793],{},"Реально (з активаціями): ~3-4 GB",[5268,14795,14796,14799],{},[5220,14797,14798],{},"Рада:"," Якщо не вистачає пам'яті, зменшіть batch_size або використайте gradient accumulation.",[14703,14801,14803,14808,14812,14826,14830,14847,14851],{"icon":14705,"label":14802},"❓ Що краще: TorchScript чи ONNX?",[5268,14804,14805],{},[5220,14806,14807],{},"Залежить від сценарію:",[5268,14809,14810],{},[5220,14811,14682],{},[5194,14813,14814,14817,14820,14823],{},[5197,14815,14816],{},"✅ Повна сумісність з PyTorch операціями",[5197,14818,14819],{},"✅ Простіший для складних моделей",[5197,14821,14822],{},"✅ Швидкий inference у C++",[5197,14824,14825],{},"❌ Прив'язаний до PyTorch екосистеми",[5268,14827,14828],{},[5220,14829,14688],{},[5194,14831,14832,14835,14838,14841,14844],{},[5197,14833,14834],{},"✅ Міжплатформенний (TensorFlow, CoreML, TensorRT)",[5197,14836,14837],{},"✅ Широка підтримка edge-пристроїв",[5197,14839,14840],{},"✅ Оптимізація для специфічного hardware",[5197,14842,14843],{},"❌ Не всі PyTorch операції підтримуються",[5197,14845,14846],{},"❌ Можливі проблеми з custom layers",[5268,14848,14849],{},[5220,14850,6732],{},[5194,14852,14853,14856,14859],{},[5197,14854,14855],{},"Deployment у PyTorch середовищі → TorchScript",[5197,14857,14858],{},"Deployment на мобільні\u002Fedge → ONNX",[5197,14860,14861],{},"Максимальна швидкість на NVIDIA → TensorRT (через ONNX)",[14703,14863,14865,14868,14873,14946,14951,14986,14991],{"icon":14705,"label":14864},"❓ Чи можна комбінувати Mixed Precision з іншими техніками?",[5268,14866,14867],{},"Так! Mixed Precision чудово поєднується з:",[5268,14869,8855,14870],{},[5220,14871,14872],{},"Gradient Accumulation:",[5492,14874,14876],{"className":5494,"code":14875,"language":5496,"meta":5497,"style":5497},"scaler = GradScaler()\nfor i, (X, y) in enumerate(train_loader):\n    with autocast():\n        loss = model(X, y) \u002F accumulation_steps\n    scaler.scale(loss).backward()\n    \n    if (i + 1) % accumulation_steps == 0:\n        scaler.step(optimizer)\n        scaler.update()\n        optimizer.zero_grad()\n",[5289,14877,14878,14882,14897,14904,14909,14914,14918,14934,14938,14942],{"__ignoreMap":5497},[5501,14879,14880],{"class":5503,"line":5504},[5501,14881,8589],{"class":5511},[5501,14883,14884,14886,14889,14891,14894],{"class":5503,"line":5515},[5501,14885,7137],{"class":5507},[5501,14887,14888],{"class":5511}," i, (X, y) ",[5501,14890,7143],{"class":5507},[5501,14892,14893],{"class":5607}," enumerate",[5501,14895,14896],{"class":5511},"(train_loader):\n",[5501,14898,14899,14902],{"class":5503,"line":5523},[5501,14900,14901],{"class":5507},"    with",[5501,14903,8720],{"class":5511},[5501,14905,14906],{"class":5503,"line":5530},[5501,14907,14908],{"class":5511},"        loss = model(X, y) \u002F accumulation_steps\n",[5501,14910,14911],{"class":5503,"line":5537},[5501,14912,14913],{"class":5511},"    scaler.scale(loss).backward()\n",[5501,14915,14916],{"class":5503,"line":5547},[5501,14917,5732],{"class":5511},[5501,14919,14920,14922,14925,14927,14930,14932],{"class":5503,"line":5552},[5501,14921,8374],{"class":5507},[5501,14923,14924],{"class":5511}," (i + ",[5501,14926,5490],{"class":5543},[5501,14928,14929],{"class":5511},") % accumulation_steps == ",[5501,14931,5828],{"class":5543},[5501,14933,5893],{"class":5511},[5501,14935,14936],{"class":5503,"line":5558},[5501,14937,9455],{"class":5511},[5501,14939,14940],{"class":5503,"line":5564},[5501,14941,9460],{"class":5511},[5501,14943,14944],{"class":5503,"line":5570},[5501,14945,7720],{"class":5511},[5268,14947,8855,14948],{},[5220,14949,14950],{},"Gradient Clipping:",[5492,14952,14954],{"className":5494,"code":14953,"language":5496,"meta":5497,"style":5497},"scaler.scale(loss).backward()\nscaler.unscale_(optimizer)  # Розмасштабувати для clip\ntorch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1.0)\nscaler.step(optimizer)\n",[5289,14955,14956,14960,14968,14982],{"__ignoreMap":5497},[5501,14957,14958],{"class":5503,"line":5504},[5501,14959,8744],{"class":5511},[5501,14961,14962,14965],{"class":5503,"line":5515},[5501,14963,14964],{"class":5511},"scaler.unscale_(optimizer)  ",[5501,14966,14967],{"class":5533},"# Розмасштабувати для clip\n",[5501,14969,14970,14973,14976,14978,14980],{"class":5503,"line":5523},[5501,14971,14972],{"class":5511},"torch.nn.utils.clip_grad_norm_(model.parameters(), ",[5501,14974,14975],{"class":6847},"max_norm",[5501,14977,7455],{"class":5511},[5501,14979,6365],{"class":5543},[5501,14981,5622],{"class":5511},[5501,14983,14984],{"class":5503,"line":5530},[5501,14985,8749],{"class":5511},[5268,14987,8855,14988],{},[5220,14989,14990],{},"Multi-GPU (DataParallel \u002F DDP)",[5268,14992,14993,14994,14997],{},"❌ ",[5220,14995,14996],{},"Несумісне:"," Деякі custom CUDA kernels можуть не підтримувати FP16.",[5333,14999],{},[5263,15001,15003],{"id":15002},"підсумок-модуля-основи-нейронних-мереж","Підсумок модуля «Основи нейронних мереж»",[5268,15005,15006],{},"Вітаємо! Ви завершили модуль 4 та опанували весь стек PyTorch від основ до просунутих тем:",[5268,15008,15009,15012],{},[5220,15010,15011],{},"Стаття 4.1"," (попередня): Теоретичні основи нейронних мереж — перцептрон, MLP, backpropagation, функції активації.",[5268,15014,15015,15018],{},[5220,15016,15017],{},"Стаття 4.2"," (01-03 файли):",[5194,15020,15021,15024,15027],{},[5197,15022,15023],{},"Тензори та autograd",[5197,15025,15026],{},"Побудова та тренування моделей",[5197,15028,15029],{},"Робота з даними та регуляризація",[5268,15031,15032,15035],{},[5220,15033,15034],{},"Стаття 4.3"," (цей файл): GPU, оптимізація, deployment — все для переходу до production.",[5987,15037,15038,15043,15049,15063,15069,15083,15089],{},[5268,15039,15040],{},[5220,15041,15042],{},"Що далі?",[5268,15044,15045,15048],{},[5220,15046,15047],{},"Модуль 5:"," Нейронні мережі в комп'ютерному зорі",[5194,15050,15051,15054,15057,15060],{},[5197,15052,15053],{},"Згорткові мережі (CNN)",[5197,15055,15056],{},"Архітектури: ResNet, VGG, EfficientNet",[5197,15058,15059],{},"Transfer Learning та Fine-tuning",[5197,15061,15062],{},"Обробка зображень",[5268,15064,15065,15068],{},[5220,15066,15067],{},"Модуль 6:"," Обробка природної мови (NLP)",[5194,15070,15071,15074,15077,15080],{},[5197,15072,15073],{},"Рекурентні мережі (RNN, LSTM, GRU)",[5197,15075,15076],{},"Word Embeddings",[5197,15078,15079],{},"Transformers та Attention",[5197,15081,15082],{},"BERT, GPT архітектури",[5268,15084,15085,15088],{},[5220,15086,15087],{},"Модуль 7:"," Навчання без учителя",[5194,15090,15091,15094,15097],{},[5197,15092,15093],{},"Autoencoders",[5197,15095,15096],{},"Variational Autoencoders (VAE)",[5197,15098,15099],{},"Generative Adversarial Networks (GAN)",[5268,15101,15102],{},[5220,15103,15104],{},"Успіхів у подальшому вивченні Deep Learning! 🚀",[15106,15107,15108],"style",{},"html pre.shiki code .s8xlr, html code.shiki .s8xlr{--shiki-light:#AF00DB;--shiki-default:#C586C0;--shiki-dark:#C586C0}html pre.shiki code .sHH4Y, html code.shiki .sHH4Y{--shiki-light:#000000;--shiki-default:#D4D4D4;--shiki-dark:#D4D4D4}html pre.shiki code .spJ8K, html code.shiki .spJ8K{--shiki-light:#008000;--shiki-default:#6A9955;--shiki-dark:#6A9955}html pre.shiki code .sJj4R, html code.shiki .sJj4R{--shiki-light:#098658;--shiki-default:#B5CEA8;--shiki-dark:#B5CEA8}html pre.shiki code .s8Opu, html code.shiki .s8Opu{--shiki-light:#795E26;--shiki-default:#DCDCAA;--shiki-dark:#DCDCAA}html pre.shiki code .su1O8, html code.shiki .su1O8{--shiki-light:#0000FF;--shiki-default:#569CD6;--shiki-dark:#569CD6}html pre.shiki code .sbdoH, html code.shiki .sbdoH{--shiki-light:#A31515;--shiki-default:#CE9178;--shiki-dark:#CE9178}html pre.shiki code .sjcCO, html code.shiki .sjcCO{--shiki-light:#EE0000;--shiki-default:#D7BA7D;--shiki-dark:#D7BA7D}html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html pre.shiki code .sN1BT, html code.shiki .sN1BT{--shiki-light:#267F99;--shiki-default:#4EC9B0;--shiki-dark:#4EC9B0}html pre.shiki code .siwwj, html code.shiki .siwwj{--shiki-light:#001080;--shiki-default:#9CDCFE;--shiki-dark:#9CDCFE}",{"title":5497,"searchDepth":5515,"depth":5515,"links":15110},[15111,15112,15118,15122,15126,15130,15134,15135],{"id":5265,"depth":5515,"text":5266},{"id":5337,"depth":5515,"text":5338,"children":15113},[15114,15115,15116,15117],{"id":5342,"depth":5523,"text":5343},{"id":5478,"depth":5523,"text":5479},{"id":6060,"depth":5523,"text":6061},{"id":7307,"depth":5523,"text":7308},{"id":8101,"depth":5515,"text":8102,"children":15119},[15120,15121],{"id":8105,"depth":5523,"text":8106},{"id":8163,"depth":5523,"text":8164},{"id":9959,"depth":5515,"text":9960,"children":15123},[15124,15125],{"id":9963,"depth":5523,"text":9964},{"id":10683,"depth":5523,"text":10684},{"id":11323,"depth":5515,"text":11324,"children":15127},[15128,15129],{"id":11327,"depth":5523,"text":11328},{"id":12071,"depth":5523,"text":12072},{"id":12753,"depth":5515,"text":12754,"children":15131},[15132,15133],{"id":12757,"depth":5523,"text":12758},{"id":13692,"depth":5523,"text":13693},{"id":14577,"depth":5515,"text":14578},{"id":15002,"depth":5515,"text":15003},"GPU-прискорення, mixed precision training, профілювання продуктивності, збереження моделей, TorchScript та ONNX для production deployment.","md",null,{},{"title":3913,"description":15136},"SjekR0-El6UWpv5-1L75FqfYFRvmiaX6HQceuCBCnYs",[15143,15145],{"title":3909,"path":3910,"stem":3911,"description":15144,"children":-1},"Dataset, DataLoader, трансформації даних, техніки регуляризації (Dropout, Batch Normalization, Weight Decay) для запобігання перенавчанню.",{"title":3922,"path":3923,"stem":3924,"description":15146,"children":-1},"Поглиблене вивчення функцій активації, їхніх похідних та практичне застосування для медичної діагностики. Побудова повноцінної нейронної мережі на PyTorch для передбачення серцево-судинних захворювань.",1791987056892]