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Add notice about RTX 3090
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README.md
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@@ -63,7 +63,7 @@ This repository is a faithful reimplementation of [StyleGAN2-ADA](https://github
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* Linux and Windows are supported, but we recommend Linux for performance and compatibility reasons.
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* 1–8 high-end NVIDIA GPUs with at least 12 GB of memory. We have done all testing and development using NVIDIA DGX-1 with 8 Tesla V100 GPUs.
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* 64-bit Python 3.7, PyTorch 1.7.1, and CUDA toolkit 11.0 or newer.
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* Docker users: use the [provided Dockerfile](./Dockerfile) to build an image with the required library dependencies.
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The code relies heavily on custom PyTorch extensions that are compiled on the fly using NVCC. On Windows, the compilation requires Microsoft Visual Studio. We recommend installing [Visual Studio Community Edition](https://visualstudio.microsoft.com/vs/) and adding it into `PATH` using `"C:\Program Files (x86)\Microsoft Visual Studio\<VERSION>\Community\VC\Auxiliary\Build\vcvars64.bat"`.
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* Linux and Windows are supported, but we recommend Linux for performance and compatibility reasons.
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* 1–8 high-end NVIDIA GPUs with at least 12 GB of memory. We have done all testing and development using NVIDIA DGX-1 with 8 Tesla V100 GPUs.
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* 64-bit Python 3.7, PyTorch 1.7.1, and CUDA toolkit 11.0 or newer. Use CUDA toolkit 11.1 or later with RTX 3090.
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* Docker users: use the [provided Dockerfile](./Dockerfile) to build an image with the required library dependencies.
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The code relies heavily on custom PyTorch extensions that are compiled on the fly using NVCC. On Windows, the compilation requires Microsoft Visual Studio. We recommend installing [Visual Studio Community Edition](https://visualstudio.microsoft.com/vs/) and adding it into `PATH` using `"C:\Program Files (x86)\Microsoft Visual Studio\<VERSION>\Community\VC\Auxiliary\Build\vcvars64.bat"`.
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