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OVERVIEW

This chapter introduces you to the framework of YSAutoML, and provides links to detailed tutorials about YSAutoML

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What is YSAutoML

YSAutoML is an open-source library designed for the automated construction of AI systems. It integrates independent utilities across data, network, and optimization into a unified platform, enabling efficient model building for tasks such as image recognition, segmentation, and object detection.

The project is developed by Yonsei CVLab, as part of a multi-year initiative on building a next-generation automated AI platform.

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How to Use this Guide

Here is a detailed step-by-step guide to learn more about YSAutoML:

  1. For installation instructions, please see get_started.

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Major Features

  • Data Utilities

    • fyi: Dataset condensation (Flip Your Images), reducing large datasets into compact synthetic sets.

    • dsbn: Domain-Specific BatchNorm for source/target or augmentation-aware training.

  • Network Utilities (NAS)

    • fewshot: Few-shot NAS, exploring architectures with limited data.

    • zeroshot: Zero-shot NAS, searching architectures without labeled training data.

    • oneshot: One-shot NAS, training a supernet and searching subnets efficiently.

  • Optimization Utilities

    • fxp: Fixed-point quantization (W/A/G bitwidth 4–8).

    • losssearch: Automated loss function search.

    • mtlloss: Multi-task loss integration for classification, segmentation, and beyond.

  • Unified Workflow

    • Users specify task, dataset, resource budget, and memory constraints.

    • YSAutoML automatically builds and trains optimized AI systems under these requirements.

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Library Structure

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License

This project is released under the Apache 2.0 License

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