Determined is an open-source deep learning training platform that makes building models fast and easy. Determined enables you to:
Train models faster using state-of-the-art distributed training, without changing your model code
Automatically find high-quality models with advanced hyperparameter tuning from the creators of Hyperband
Get more from your GPUs with smart scheduling and cut cloud GPU costs by seamlessly using preemptible instances
Track and reproduce your work with experiment tracking that works out-of-the-box, covering code versions, metrics, checkpoints, and hyperparameters
Determined integrates these features into an easy-to-use, high-performance deep learning environment — which means you can spend your time building models instead of managing infrastructure.
To use Determined, you can continue using popular DL frameworks such as TensorFlow and PyTorch; you just need to update your model code to integrate with the Determined API.
More information about Determined can be found on the website.
Get Started Locally¶
Follow these instructions to install and set up Docker.
# Start a Determined cluster locally. python3.7 -m venv ~/.virtualenvs/test . ~/.virtualenvs/test/bin/activate pip install determined # To start a cluster with GPUs, remove `no-gpu` flag. det deploy local cluster-up --no-gpu # Access web UI at localhost:8080. By default, "determined" user accepts a blank password. # Navigate to a Determined example. git clone https://github.com/determined-ai/determined cd determined/examples/computer_vision/cifar10_pytorch # Submit job to train a single model on a single node. det experiment create const.yaml .
To install Determined, please follow the installation instructions. Determined can be installed on the public cloud, an on-premise cluster, or a local development machine.
Each user should also install the Determined command-line tools on systems they will use to access Determined.
We recommend starting with the Quick Start Guide if you’re new to Determined.
Next, learn more about Determined’s Python APIs by following a tutorial. Follow the tutorial for your preferred framework:
Join the Community¶
Whether you’re trying our software for the first time or you’re training production models, we’d love to hear from you!
Use the links below to start learning more about Determined’s capabilities.
Reproducibility, TensorBoard, and Notebooks
The Determined documentation is divided up into five main categories:
Tutorials are simple step-by-step guides about getting started with different topics of Determined. Tutorials are a good place to get started with using the product.
Topic Guides discuss concepts and topics at a high level. They provide useful information and explanation.
Reference guides contain technical reference for our APIs. They describe how to use it; however, these guides assume you have a working understanding of key concepts of Determined.
How-to guides take you through the steps needed to address key use-cases. You can think of them as advanced tutorials that assume some knowledge of key concepts of Determined.
System administration guides take you through what’s needed to set up and configure the Determined system.