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Add experimental `--torch-backend` to the PyTorch guide (#12317)
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@ -14,8 +14,7 @@ CUDA).
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!!! note
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!!! note
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Some of the features outlined in this guide require uv version 0.5.3 or later. If you're using an
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Some of the features outlined in this guide require uv version 0.5.3 or later. We recommend upgrading prior to configuring PyTorch.
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older version of uv, we recommend upgrading prior to configuring PyTorch.
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## Installing PyTorch
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## Installing PyTorch
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@ -396,3 +395,28 @@ To use the same workflow with uv, replace `pip3` with `uv pip`:
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```shell
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```shell
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$ uv pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
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$ uv pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
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```
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```
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## Automatic backend selection
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In [preview](../../reference/settings.md#preview), uv can automatically select the appropriate
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PyTorch index at runtime by inspecting the system configuration via `--torch-backend=auto` (or
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`UV_TORCH_BACKEND=auto`):
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```shell
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$ UV_TORCH_BACKEND=auto uv pip install torch
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```
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When enabled, uv will query for the installed CUDA driver version and use the most-compatible
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PyTorch index for all relevant packages (e.g., `torch`, `torchvision`, etc.). If no such CUDA driver
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is found, uv will fall back to the CPU-only index. uv will continue to respect existing index
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configuration for any packages outside the PyTorch ecosystem.
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To select a specific backend (e.g., `cu126`), set `--torch-backend=cu126` (or
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`UV_TORCH_BACKEND=cu126`).
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At present, `--torch-backend` is only available in the `uv pip` interface, and only supports
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detection of CUDA drivers (as opposed to other accelerators like ROCm or Intel GPUs).
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As `--torch-backend` is a preview feature, it should be considered experimental and is not governed
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by uv's standard [versioning policy](../../reference/policies/versioning.md). `--torch-backend` may
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change or be removed entirely in future versions of uv.
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