Using torch.compile() on Windows

torch.compile() relies on TorchInductor, which JIT-compiles kernels and requires a working C/C++ compiler toolchain.

So, on Windows, the setup required to make torch.compile work can be a bit more involved than on Linux or macOS, which usually don't require any extra steps besides installing PyTorch.

If you are a Windows user and using torch.compile sounds too tricky or complicated, don't worry, all code examples in this repository will work fine without compilation.

Below are some tips that I compiled based on recommendations by Daniel Kleine and the following PyTorch guide.

 

1 Basic Setup (CPU or CUDA)

 

1.1 Install Visual Studio 2022

• Select the “Desktop development with C++” workload.
• Make sure to include the English language pack (without it, you may run into UTF-8 encoding errors.)

 

1.2 Open the correct command prompt

Launch Python from the

"x64 Native Tools Command Prompt for VS 2022"

or from the

"Visual Studio 2022 Developer Command Prompt".

Alternatively, you can initialize the environment manually by running:

"C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvars64.bat"

 

1.3 Verify that the compiler works

Run

cl.exe

If you see version information printed, the compiler is ready.

 

2 Troubleshooting Common Errors

 

2.1 Error: cl not found

Install Visual Studio Build Tools with the "C++ build tools" workload and run Python from a developer command prompt. (See this Microsoft guide for details)

 

2.2 Error: triton not found (when using CUDA)

Install the Windows build of Triton manually:

pip install "triton-windows<3.4"

or, if you are using uv:

uv pip install "triton-windows<3.4"

(As mentioned earlier, triton is required by TorchInductor for CUDA kernel compilation.)

 

3 Additional Notes

On Windows, the cl.exe compiler is only accessible from within the Visual Studio Developer environment. This means that using torch.compile() in notebooks such as Jupyter may not work unless the notebook was launched from a Developer Command Prompt.

As mentioned at the beginning of this article, there is also a PyTorch guide that some users found helpful when getting torch.compile() running on Windows CPU builds. However, note that it refers to PyTorch's unstable branch, so use it as a reference only.

If compilation continues to cause issues, please feel free to skip it. It's a nice bonus, but it's not important to follow the book.