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Small comment/doc fixes (#263)
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docs/docker.md

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@@ -185,7 +185,7 @@ The whole goal of building these kernels is to allow researchers, developers, an
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To load a kernel locally, you should add the kernel build that is compatible with the Torch and CUDA versions in your environment to `PYTHONPATH`. For example:
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```bash
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# PyTorch 2.6 and CUDA 12.6
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# PyTorch 2.9 and CUDA 12.6
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export PYTHONPATH="result/torch29-cxx11-cu126-x86_64-linux"
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```
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tests/Dockerfile.test-kernel

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# syntax=docker/dockerfile:1.4
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ARG PYTHON_VERSION=3.10
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# Ideally we'd test with 11.8, but the GELU kernel is subtly off.
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# Test with the oldest CUDA version supported by the latest PyTorch.
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ARG CUDA_VERSION=12.6.0
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ARG UBI_VERSION=8
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ARG TORCH_VERSION=2.9.0

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