base on Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow. <p align="center"><img width="400" src="determined-logo.svg" alt="Determined AI Logo"></p> Determined is an all-in-one deep learning platform, compatible with PyTorch and TensorFlow. It takes care of: - Distributed training for faster results. - Hyperparameter tuning for obtaining the best models. - Resource management for cutting cloud GPU costs. - Experiment tracking for analysis and reproducibility. <br/> <p align="center"> <img alt="Features gif" src="./docs/assets/readme_images/features.gif"> </p> # How Determined Works The main components of Determined are the Python library, the command line interface (CLI), and the Web UI. ## Python Library Use the Python library to make your existing PyTorch or Tensorflow code compatible with Determined. You can do this by organizing your code into one of the class-based APIs: ```python from determined.pytorch import PyTorchTrial class YourExperiment(PyTorchTrial): def __init__(self, context): ... ``` Or by using just the functions you want, via the Core API: ```python import determined as det with det.core.init() as core_context: ... ``` ## Command Line Interface (CLI) You can use the CLI to: - Start a Determined cluster locally: ``` det deploy local cluster-up ``` - Launch Determined on cloud services, such as Amazon Web Services (AWS) or Google Cloud Platform (GCP): ``` det deploy aws up ``` - Train your models: ```bash det experiment create gpt.yaml . ``` Configure everything from distributed training to hyperparameter tuning using YAML files: ```yaml resources: slots_per_trial: 8 priority: 1 hyperparameters: learning_rate: type: double minval: .0001 maxval: 1.0 searcher: name: adaptive_asha metric: validation_loss smaller_is_better: true ``` ## Web UI Use the Web UI to view loss curves, hyperparameter plots, code and configuration snapshots, model registries, cluster utilization, debugging logs, performance profiling reports, and more.  # Installation To install the CLI: ```bash pip install determined ``` Then use `det deploy` to start the Determined cluster locally, or on cloud services like AWS and GCP. For installation details, visit the the cluster deployment guide for your environment: - [Local (on-prem)](https://docs.determined.ai/latest/setup-cluster/deploy-cluster/on-prem/overview.html) - [AWS](https://docs.determined.ai/latest/setup-cluster/deploy-cluster/aws/overview.html) - [GCP](https://docs.determined.ai/latest/setup-cluster/deploy-cluster/gcp/overview.html) - [Kubernetes](https://docs.determined.ai/latest/setup-cluster/deploy-cluster/k8s/overview.html) - [Slurm/PBS](https://docs.determined.ai/latest/setup-cluster/deploy-cluster/slurm/overview.html) # Examples Get familiar with Determined by exploring the 30+ examples in the [examples folder](https://github.com/determined-ai/determined/tree/main/examples) and the [determined-examples repo](https://github.com/determined-ai/determined-examples). # Documentation - [Documentation](https://docs.determined.ai) - [Quick Start Guide](https://docs.determined.ai/latest/getting-started.html) - Tutorials: - [PyTorch MNIST Tutorial](https://docs.determined.ai/latest/tutorials/pytorch-mnist-tutorial.html) - [TensorFlow Keras MNIST Tutorial](https://docs.determined.ai/latest/tutorials/tf-mnist-tutorial.html) - User Guides: - [Core API](https://docs.determined.ai/latest/model-dev-guide/apis-howto/api-core-ug.html) - [PyTorch API](https://docs.determined.ai/latest/model-dev-guide/apis-howto/api-pytorch-ug.html) - [Keras API](https://docs.determined.ai/latest/model-dev-guide/apis-howto/api-keras-ug.html) - [DeepSpeed API](https://docs.determined.ai/latest/model-dev-guide/apis-howto/deepspeed/overview.html) # Community If you need help, want to file a bug report, or just want to keep up-to-date with the latest news about Determined, please join the Determined community! - [Slack](https://determined-community.slack.com) is the best place to ask questions about Determined and get support. [Click here to join our Slack](https://determined-community.slack.com). - You can also follow us on [YouTube](https://www.youtube.com/@DeterminedAI) and [Twitter](https://www.twitter.com/DeterminedAI). - You can also join the [community mailing list](https://groups.google.com/a/determined.ai/forum/#!forum/community) to ask questions about the project and receive announcements. - To report a bug, [open an issue](https://github.com/determined-ai/determined/issues) on GitHub. - To report a security issue, email [`[email protected]`](mailto:[email protected]). # Contributing [Contributor's Guide](CONTRIBUTING.md) # License [Apache V2](LICENSE) ", Assign "at most 3 tags" to the expected json: {"id":"4529","tags":[]} "only from the tags list I provide: []" returns me the "expected json"