Blog post to address Pytorch channel deprecation

blog/2024-11-20-pytorch-channel-deprecation.md

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+---
+authors:
+  - core
+tags: [pytorch]
+---
+
+# About Pytorch Channel Deprecation
+
+[PyTorch team announced](https://github.com/pytorch/pytorch/issues/138506) that they will stop publishing packages to their official channel on Anaconda.org (`-c pytorch`) after the `2.5` release. We want to address this change and clarify our commitment to maintaining PyTorch packages on conda-forge. 
+
+First and foremost, we deeply appreciate the PyTorch team’s significant contributions to the conda packaging ecosystem and their ongoing collaboration with conda-forge. The conda-forge team sees this transition as an opportunity to strengthen the conda ecosystem and create more stable and reliable environments for users.
+
+<!-- truncate -->
+
+Dependency conflicts have long been a pain point for users when mixing packages from the conda-forge and Anaconda "defaults." These conflicts arise because different channels build packages against different versions of core dependencies (packages on pytorch channel had dependancies in Anaconda `defaults` cannels). By consolidating PyTorch packages entirely under conda-forge, we can provide a more consistent and reliable experience, reducing conflicts and improving installation stability.
+
+
+## Our Commitment
+
+- Conda-forge is actively working with PyTorch maintainers and the broader open-source community to address potential gaps, ensure stability, and improve package availability.
+- We will continue to maintain [pytorch-cpu](https://anaconda.org/conda-forge/pytorch-cpu) and [pytorch-gpu](https://anaconda.org/conda-forge/pytorch-gpu) packages, ensuring they are up to date and aligned with PyTorch releases.
+- While Windows support is currently limited, we are making it a top priority to improve this and deliver a consistent experience across all platforms ([see #231](https://github.com/conda-forge/pytorch-cpu-feedstock/pull/231)).
+- We aim to release updates as close as possible to official PyTorch releases. As a volunteer-driven community, we follow a best-effort approach while prioritizing quality and reliability.
+- We welcome community [feedback and contributions](#getting-help-and-contributing), which are essential to improving the ecosystem. Your input directly informs our priorities and helps shape the future of PyTorch on conda-forge.
+
+
+## Current Package Support
+
+Fully Supported:
+- Linux: Full support for both Pytorch CPU and Pytorch GPU (CUDA versions 11.8, 12.1, and 12.4).
+- macOS: CPU-only support.
+
+**Known Limitations:**
+- Windows: Limited support currently, but improving Windows support is a top priority.
+
+
+## Migration Guide
+
+For Current PyTorch Channel Users
+
+Update your conda configuration:
+```bash
+mamba/conda config --remove channels pytorch
+mamba/conda config --add channels conda-forge
+mamba/conda config --set channel_priority strict
+```
+
+Update your PyTorch installation
+```bash
+mamba install pytorch-cpu
+mamba install pytorch-gpu # for GPU support
+# OR
+conda install pytorch-cpu
+conda install pytorch-gpu # for GPU support
+```
+
+## Getting Help and Contributing
+The success of this transition depends on collaboration with the community. Here’s how you can get involved:
+- Report issues: Use the [pytorch-cpu-feedstock](https://github.com/conda-forge/pytorch-cpu-feedstock) repository to report bugs or request features.
+- Join discussions: Share feedback and ideas on the conda-forge [Zulip chat](https://conda-forge.zulipchat.com/).
+- Contribute: Help maintain [Pytorch package on conda-forge](https://github.com/conda-forge/pytorch-cpu-feedstock/issues/273) or support ongoing improvements.
+
+## Frequently Asked Questions
+
+**Will my existing PyTorch installations stop working?**
+No, existing installations will continue to work. However, we recommend transitioning to conda-forge packages for future updates.
+
+**How quickly will conda-forge release new PyTorch versions?**
+We aim to release updates as close as possible to official PyTorch releases. But as a volunteer-driven community, we follow a best-effort approach while prioritizing quality and reliability..
+
+**What about PyTorch's ecosystem packages (torchvision, torchaudio, etc.)?**
+We maintain these packages as well, and they will continue to be available through conda-forge (see [torchvision](https://github.com/conda-forge/torchvision-feedstock) and [torchaudio](https://github.com/conda-forge/torchaudio-feedstock) feedstocks). 
+
+**How can I ensure package compatibility?**
+Using `conda-forge` as your primary channel with strict channel priority will ensure package compatibility.