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Table of Contents

  • Overview
  • Installation
  • QuickStart
  • Auto (Hyper-parameter) Tuning
    • Write Trial
    • Tuners
    • Assessors
    • Training Platform
      • Overview
      • Local
      • Remote
      • OpenPAI
      • Kubeflow
      • AdaptDL
      • FrameworkController
      • DLTS
      • AML
      • Hybrid
    • Examples
    • WebUI
    • How to Debug
    • Advanced
  • Neural Architecture Search
  • Model Compression
  • Feature Engineering
  • References
  • Use Cases and Solutions
  • Research and Publications
  • FAQ
  • How to Contribute
  • Change Log
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  • Auto (Hyper-parameter) Tuning »
  • Introduction to NNI Training Services
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Introduction to NNI Training ServicesΒΆ

  • Overview
    • What is Training Service?
    • How to use Training Service?
    • Built-in Training Services
    • What does Training Service do?
  • Local
    • View experiment results
    • Using multiple local GPUs to speed up search
  • Remote
    • Requirements
      • Linux
      • Windows
    • Run an experiment
      • Configure python environment
  • OpenPAI
    • Setup environment
    • Run an experiment
      • Trial configurations
      • OpenPAI configurations
    • data management
    • version check
  • Kubeflow
    • Prerequisite for on-premises Kubernetes Service
    • Prerequisite for Azure Kubernetes Service
    • Design
    • Supported operator
    • Supported storage type
    • Run an experiment
    • version check
  • AdaptDL
    • Prerequisite for Kubernetes Service
      • Verify Prerequisites
    • Run an experiment
      • NFS Storage
    • Monitor via Log Stream
    • Monitor via TensorBoard
  • FrameworkController
    • Prerequisite for on-premises Kubernetes Service
    • Prerequisite for Azure Kubernetes Service
    • Setup FrameworkController
    • Design
    • Example
    • How to run example
    • version check
  • DLTS
    • Setup Environment
  • AML
    • Setup environment
    • Run an experiment
  • Hybrid
    • Setup environment
    • Run an experiment
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