Getting Started
Cosmos-RL is a flexible and scalable Reinforcement Learning framework specialized for Physical AI applications.
System Architecture
Cosmos-RL provides toolchain to enable large scale RL training workload with following features:
- Parallelism
- Tensor Parallelism
- Sequence Parallelism
- Context Parallelism
- FSDP Parallelism
- Pipeline Parallelism
- Fully asynchronous (replicas specialization)
- Policy (Consumer): Replicas of training instances
- Rollout (Producer): Replicas of generation engines
- Low-precision training (FP8) and rollout (FP8 & FP4) support
- Single-Controller Architecture
- Efficient messaging system (e.g.,
weight-sync,rollout,evaluate) to coordinate policy and rollout replicas - Dynamic NCCL Process Groups for on-the-fly GPU [un]registration to enable fault-tolerant and elastic large-scale RL training
- Efficient messaging system (e.g.,
License and Contact
This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.
NVIDIA Cosmos source code is released under the Apache 2 License.
NVIDIA Cosmos models are released under the NVIDIA Open Model License. For a custom license, please contact cosmos-license@nvidia.com.
1 maintainer
Metadata
1 maintainer
Release files for cosmos-rl 0.4.7
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| cosmos_rl-0.4.7.tar.gz | 6.7 MB | Without provenance | Details for cosmos_rl-0.4.7.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| cosmos_rl-0.4.7-py3-none-any.whl | Python 3 | none | any | Details for cosmos_rl-0.4.7-py3-none-any.whl |
Total release size: 8.8 MB
Release files / cosmos_rl-0.4.7.tar.gz
| Download URL | cosmos_rl-0.4.7.tar.gz |
|---|---|
| Size | 6.7 MB |
| Tags | Source |
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Release files / cosmos_rl-0.4.7-py3-none-any.whl
| Download URL | cosmos_rl-0.4.7-py3-none-any.whl |
|---|---|
| Size | 2.1 MB |
| Tags | Python 3 |
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