pytorch12.4版本

### PyTorch 1.12.0 with CUDA 12.4 Information For installing PyTorch along with its dependencies like torchvision and torchaudio, specifically tailored to CUDA 12.4, the recommended installation command using conda is as follows: ```bash conda install pytorch torchvision torchaudio pytorch-cuda=12.4 -c pytorch -c nvidia ``` This ensures compatibility between PyTorch and CUDA versions while leveraging optimized builds provided by NVIDIA and PyTorch teams[^1]. However, it appears there might be a misunderstanding regarding the version numbers mentioned. The term "PyTorch 12.4" does not refer to any official PyTorch release; instead, this likely refers to the combination of PyTorch (a specific version such as v1.12.0) paired with CUDA 12.4 support. The actual PyTorch version that supports CUDA 12.4 can vary based on when CUDA 12.4 was released relative to PyTorch releases. For instance, an example given shows how one could use PyTorch version `1.12.0` alongside CUDA `11.6`, indicating different combinations are possible depending on availability at the time of setup[^2]: To find detailed **release notes**, including new features, bug fixes, performance improvements, or changes affecting backward compatibility for a particular PyTorch version supporting CUDA 12.4, visit the [official PyTorch GitHub repository](https://github.com/pytorch/pytorch/releases). Downloading pre-built binaries directly depends on whether these have been made available through channels such as Anaconda Cloud (`conda`) or Python Package Index (`pip`). Users should check both platforms regularly since updates may occur after initial announcements.