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Determined AI Documentation
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version 0.21.0
  • Welcome

Getting Started

  • Try Determined
    • Run Your First Experiment
    • PyTorch MNIST Tutorial
    • PyTorch Porting Tutorial
    • TensorFlow Keras Fashion MNIST Tutorial
  • How It Works
    • Introduction to Determined
    • System Architecture
  • Quickstart for Model Developers
  • Examples
  • Model Hub Library
    • Huggingface Trainsformers
      • Tutorial
      • Examples
    • MMDetection

Set Up Determined

  • Set Up Guide
    • Deploy on Prem
      • Installation Requirements
      • Install Determined Using Docker
      • Install Determined Using det deploy
      • Install Determined Using Linux Packages
      • Install Determined Using Homebrew (macOS)
    • Deploy on AWS
      • Install Determined
      • Deploy Determined with Dynamic Agents
      • Use Spot Instances
    • Deploy on GCP
      • Install Determined
      • Deploy Determined with Dynamic Agents
    • Deploy on Kubernetes
      • Install Determined on Kubernetes
      • Set up and Manage an Azure Kubernetes Service (AKS) Cluster
      • Set up and Manage an AWS Kubernetes (EKS) Cluster
      • Set up and Manage a Google Kubernetes Engine (GKE) Cluster
      • Development Guide
      • Customize a Pod
      • Helm and Kubectl Command Examples
      • Troubleshooting
    • Deploy on Slurm/PBS
      • Installation Requirements
      • Install Determined on Slurm/PBS
      • Provide a Container Image Cache
      • HPC Launching Architecture
      • Known Issues
  • Basic Setup
  • Security
    • OAuth 2.0 Configuration
    • Transport Layer Security
    • OpenID Connect Integration
    • SAML Integration
    • SCIM Integration
    • RBAC
  • User Accounts
  • Workspaces and Projects
  • Logging and Elasticsearch
  • Cluster Usage History
  • Monitor Experiment Through Webhooks
    • Through Zapier
    • Through Slack
  • Upgrade
  • Troubleshooting

Model Developer Guide

  • Overview
  • Distributed Training
  • Prepare Container Environment
    • Set Environment Images
    • Customize Environment
  • Prepare Data
  • Training API Guides
    • Core API
    • PyTorch API
    • PyTorch Lightning API
    • Keras API
    • DeepSpeed API
      • Usage Guide
      • Advanced Usage
      • PyTorchTrial to DeepSpeedTrial
    • Estimator API
  • Hyperparameter Tuning
    • Configure Hyperparameter Ranges
    • Hyperparameter Search Constraints
    • Instrument Model Code
    • Handle Trial Errors and Early Stopping Requests
    • Search Methods
      • Adaptive (Asynchronous) Method
      • Grid Method
      • Random Method
      • Single Search Method
      • Custom Search Methods
  • Submit Experiment
  • How to Debug Models
  • Model Management
    • Checkpoints
    • Organize Models in the Model Registry
  • Best Practices

Reference

  • Overview
  • Python SDK
  • REST API
  • Training Reference
    • det
    • det.core
    • det.pytorch
    • det.pytorch.samplers
    • det.pytorch.deepspeed
    • det.pytorch.lightning
    • det.keras
    • det.estimator
    • Experiment Configuration
  • Model Hub Reference
    • MMDetection API
    • Transformers API
  • Deployment Reference
    • Common Configuration Options
    • Master Configuration Reference
    • Agent Configuration Reference
    • Helm Chart Configuration Reference
  • Job Configuration Reference
  • Custom Searcher Reference

Tools

  • Commands and Shells
  • WebUI Interface
  • Jupyter Notebooks
  • TensorBoards
  • Exposing Custom Ports

Integrations

  • Works with Determined
  • IDE Integration
  • Prometheus and Grafana
  • Open Source Licenses

Training Reference¶

Python Modules APIs¶

  • det

  • det.core

  • det.pytorch

  • det.pytorch.samplers

  • det.pytorch.deepspeed

  • det.pytorch.lightning

  • det.keras

  • det.estimator

Experiment Configuration File¶

  • Experiment Configuration Reference

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  • Training Reference
    • Python Modules APIs
    • Experiment Configuration File