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Update README and Troubleshooting for GCC versions 

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Janne Hellsten 2021-10-13 13:24:42 +03:00
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README.md
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@ -56,6 +56,7 @@ While new generator approaches enable new media synthesis capabilities, they may
* 1–8 high-end NVIDIA GPUs with at least 12 GB of memory. We have done all testing and development using Tesla V100 and A100 GPUs.
* 64-bit Python 3.8 and PyTorch 1.9.0 (or later). See https://pytorch.org for PyTorch install instructions.
* CUDA toolkit 11.1 or later. (Why is a separate CUDA toolkit installation required? See [Troubleshooting](./docs/troubleshooting.md#why-is-cuda-toolkit-installation-necessary)).
- GCC 7 or later (Linux) or Visual Studio (Windows) compilers. Recommended GCC version depends on CUDA version, see for example [CUDA 11.4 system requirements](https://docs.nvidia.com/cuda/archive/11.4.1/cuda-installation-guide-linux/index.html#system-requirements).
* Python libraries: see [environment.yml](./environment.yml) for exact library dependencies. You can use the following commands with Miniconda3 to create and activate your StyleGAN3 Python environment:
- `conda env create -f environment.yml`
- `conda activate stylegan3`

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docs/troubleshooting.md
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@ -18,6 +18,7 @@ Make sure you've installed everything listed on the requirements section in the
- **ninja**
- PyTorch uses [Ninja](https://ninja-build.org/) as its build system.
- **GCC** (Linux) or **Visual Studio** (Windows)
- GCC 7.x or later is required. Earlier versions such as GCC 6.3 [are known not to work](https://github.com/NVlabs/stylegan3/issues/2).
#### Why is CUDA toolkit installation necessary?