pytoch安装指定版本教程&pytorch1.3安装笔记

### PyTorch 1.3 Installation Guide and Release Notes For users interested in the specifics of PyTorch version 1.3, including its installation process and notable changes introduced during this release, several key points can be highlighted. The official documentation recommends installing PyTorch through Anaconda or using pip directly; however, specific instructions may vary depending on whether CUDA support is required[^2]. For a precise setup targeting PyTorch 1.3 with CUDA compatibility, one should ensure that compatible versions of CUDA and cuDNN are installed prior to setting up PyTorch itself. Regarding detailed installation steps tailored specifically for PyTorch 1.3: To install via `pip`, it's important to specify the exact version number when executing commands such as: ```bash pip install torch==1.3.0 torchvision==0.4.0 ``` This command installs both PyTorch (version 1.3) along with TorchVision at an appropriate matching version which works well together. In terms of new features added within PyTorch 1.3, highlights include improvements aimed at enhancing performance across various hardware platforms while also expanding support for additional functionalities like JIT scripting capabilities among others. --related questions-- 1. What were some major enhancements made available in PyTorch 1.3? 2. How does one verify successful installation after completing all necessary setups? 3. Are there any known issues associated particularly with PyTorch 1.3 installations? 4. Can TensorRT integration work seamlessly alongside PyTorch 1.3 given proper configurations have been applied according to provided guidelines?