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Determined AI Documentation
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version 0.17.15
  • Quickstart for Model Developers

Introduction to Determined

  • Tutorials
    • PyTorch MNIST Tutorial
    • PyTorch Porting Tutorial
    • TensorFlow Keras Fashion MNIST Tutorial
  • Examples
  • Model Hub
    • Transformers
      • Tutorial
      • Examples
      • API
    • MMDetection
      • API
  • Concepts
    • Elastic Infrastructure
    • Resource Pools
    • Scheduling
    • YAML Configuration
  • Interact with Cluster
    • Command-line Interface (CLI)
    • Python API
    • REST APIs

Preparation

  • Prepare Environment
    • Custom Environment
    • Custom Pod Specs
  • Prepare Data

Training

  • Training APIs
    • PyTorch API
      • Advanced Usage
      • Porting Checklist
      • API Reference
    • PyTorch Lightning API
    • DeepSpeed API
      • Usage Guide
      • Advanced Usage
      • PyTorchTrial to DeepSpeedTrial
      • API Reference
    • Keras API
      • API Reference
    • Estimator API
      • API Reference
    • Data Layer API for Keras and Estimator
    • Experiment Configuration
    • Best Practices
  • Run Training Code
  • How to Debug Models
    • How To Profile An Experiment
  • Distributed Training
    • Effective Distributed Training
  • Hyperparameter Tuning
    • Hyperparameter Search: Adaptive (Asynchronous)
    • Hyperparameter Search Constraints
    • Hyperparameter Search: Grid
    • Hyperparameter Search: Population-based training
    • Hyperparameter Search: Random
    • Hyperparameter Search: Single
    • Hyperparameter Tuning Defined
  • Reproducibility
  • Post Training
    • Organizing Models in the Model Registry
    • Using Checkpoints

Additional Features

  • Interactive Job Configuration
  • Commands and Shells
  • Configuration Templates
  • Queue Management
  • Model Registry
  • Notebooks
  • TensorBoards

Cluster Setup

  • Basics
    • Network Requirements
    • Cluster Configuration
    • Elasticsearch-backed logging
    • Historical Cluster Usage Data
    • Upgrades
    • Troubleshooting Tips
    • Users
    • OAuth 2.0 (Enterprise Edition)
    • OpenID Connect Integration (Enterprise Edition)
    • SAML Integration (Enterprise Edition)
    • SCIM Integration (Enterprise Edition)
    • Transport Layer Security
  • Deploy on AWS
    • Install Determined on AWS
    • Dynamic Agents on AWS
    • AWS Spot Instances
  • Deploy on GCP
    • Install Determined on GCP
    • Dynamic Agents on GCP
  • Deploy on Prem
    • Installation Requirements
    • Install Determined Using Docker
    • Install Determined Using det deploy
    • Install Determined Using Linux Packages
  • Deploy on Kubernetes
    • Helm Chart Configuration
    • Install Determined on Kubernetes
    • Determined on K8s Development Guide
    • Setting up an Azure Kubernetes Service (AKS) Cluster
    • Managing an AKS Cluster
    • Setting up an AWS Kubernetes (EKS) Cluster
    • Managing an EKS Cluster
    • Setting up a Google Kubernetes Engine (GKE) Cluster
    • Managing a GKE Cluster

Integrations

  • Ecosystem Integration
  • Configure Determined with Prometheus and Grafana

Further

  • Join the Community
  • Open Source Licenses
  • Release Notes

Tutorials¶

These tutorials provide easy step-by-step guides for getting started with Determined, highlighting a number of features.

PyTorch¶

For PyTorch users, begin with the MNIST tutorial, which uses the simplest model. If you already have runnable code, follow the PyTorch Porting Tutorial steps to port your code to use Determined Pytorch APIs.

TensorFlow Keras¶

TensorFlow Keras users can begin with the MNIST tutorial, which uses the simplest model.

Next
PyTorch MNIST Tutorial
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Quickstart for Model Developers
Copyright © 2022, Determined AI
Contents
  • Tutorials
    • PyTorch
    • TensorFlow Keras