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* Unify Sphinx build to build as one project instead
of separate User Guide and Deployment Guide builds
* Change hard-coded URLs to use Sphinx roles so
the correct multiversion link can be interpolated
at build time
The goal of this change is to make the links in our docs
version-aware after moving to multiversion docs in
#40. Normally the
way to do this is to reference roles like `:doc:` and
`:ref:` instead of hard-coding URLs, but since we have
cross-guide links we also have to unify the Sphinx build
to make the builds aware of roles across all our docs.
Copy file name to clipboardExpand all lines: README.md
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@@ -116,13 +116,13 @@ OSMO solves this [Three Computer Problem](https://blogs.nvidia.com/blog/three-co
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| **What You Can Do** | **Example** |
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|---------------------|----------------------|
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| **Interactively develop** on remote GPU nodes with VSCode, SSH, or Jupyter notebooks | [Interactive Workflows](https://nvidia.github.io/OSMO/user_guide/workflows/interactive/index.html) |
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| **Generate synthetic data** at scale using Isaac Sim or custom simulation environments | [Isaac Sim SDG](https://nvidia.github.io/OSMO/user_guide/how_to/isaac_sim_sdg.html) |
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| **Train models** with diverse datasets across distributed GPU clusters | [Model Training](https://nvidia.github.io/OSMO/user_guide/how_to/training.html) |
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| **Interactively develop** on remote GPU nodes with VSCode, SSH, or Jupyter notebooks | [Interactive Workflows](https://nvidia.github.io/OSMO/user_guide/main/workflows/interactive/index.html) |
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| **Generate synthetic data** at scale using Isaac Sim or custom simulation environments | [Isaac Sim SDG](https://nvidia.github.io/OSMO/user_guide/main/how_to/isaac_sim_sdg.html) |
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| **Train models** with diverse datasets across distributed GPU clusters | [Model Training](https://nvidia.github.io/OSMO/user_guide/main/how_to/training.html) |
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| **Train policies** for robots using data-parallel reinforcement learning | [Reinforcement Learning](https://nvidia.github.io/OSMO/user_guide/how_to/reinforcement_learning.html) |
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| **Validate models** in simulation with hardware-in-the-loop testing | [Hardware In The Loop](https://nvidia.github.io/OSMO/user_guide/tutorials/hardware_in_the_loop/index.html) |
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| **Transform and post-process data** for iterative improvement | [Working with Data](https://nvidia.github.io/OSMO/user_guide/tutorials/data/index.html) |
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| **Benchmark system software** on actual robot hardware (NVIDIA Jetson, custom platforms) | [Hardware Testing](https://nvidia.github.io/OSMO/user_guide/how_to/hil.html) |
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| **Validate models** in simulation with hardware-in-the-loop testing | [Hardware In The Loop](https://nvidia.github.io/OSMO/user_guide/main/tutorials/hardware_in_the_loop/index.html) |
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| **Transform and post-process data** for iterative improvement | [Working with Data](https://nvidia.github.io/OSMO/user_guide/main/tutorials/data/index.html) |
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| **Benchmark system software** on actual robot hardware (NVIDIA Jetson, custom platforms) | [Hardware Testing](https://nvidia.github.io/OSMO/user_guide/main/how_to/hil.html) |
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### Battle-Tested in Production
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| 🛠️ [**Cloud Deployment**](https://nvidia.github.io/OSMO/deployment_guide/) | Deploy production grade on cloud providers |
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| 📘 [**User Guide**](https://nvidia.github.io/OSMO/user_guide/) | Tutorials, workflows, and how-to guides for developers |
| 💻 [**Getting Started**](https://nvidia.github.io/OSMO/user_guide/getting_started/install/index.html) | Install command-line interface to get started |
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| 💻 [**Getting Started**](https://nvidia.github.io/OSMO/user_guide/main/getting_started/install/index.html) | Install command-line interface to get started |
Copy file name to clipboardExpand all lines: docs/deployment_guide/advanced_config/dataset_buckets.rst
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Dataset Buckets
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===============
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Register external cloud storage buckets (S3, GCS, Azure) with OSMO to organize `datasets <https://nvidia.github.io/OSMO/user_guide/tutorials/data/index.html#datasets>`_ across multiple storage locations (This configuration is optional)
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Register external cloud storage buckets (S3, GCS, Azure) with OSMO to organize :ref:`datasets <tutorials_working_with_data_datasets>` across multiple storage locations (This configuration is optional)
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Why Use Dataset Buckets?
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=========================
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.. seealso::
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- Learn more about datasets in OSMO at `Datasets <https://nvidia.github.io/OSMO/user_guide/tutorials/data/index.html#datasets>`_
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- Learn more about datasets in OSMO at :ref:`Datasets <tutorials_working_with_data_datasets>`
Copy file name to clipboardExpand all lines: docs/deployment_guide/appendix/deploy_local.rst
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Now that you have OSMO running locally, explore the platform:
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1. **Run Your First Workflow**: Visit the `User Guide <https://nvidia.github.io/OSMO/user_guide/getting_started/next_steps.html>`_ for tutorials on submitting workflows, interactive development, distributed training, and more.
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1. **Run Your First Workflow**: Visit the :doc:`User Guide </user_guide/getting_started/next_steps>` for tutorials on submitting workflows, interactive development, distributed training, and more.
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2. **Explore the Web UI**: Visit ``http://quick-start.osmo`` to access the OSMO dashboard.
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