1. 概念介绍PyTorch 是一个开源的机器学习库，由 Facebook 的人工智能研究团队开发。它主要被用于创建和训练深度学习模型。PyTorch 的设计目标是让用户能够更加灵活、直观地进行模型的构建和调试，同时保持高性能。解决的核心问题•灵活性与易用性：传统的深度学习框架（如 ...

Dr. James McCaffrey of Microsoft Research continues his four-part series on multi-class classification, designed to predict a value that can be one of three or more possible discrete values, by ...

When using a PyTorch neural network, categorical predictor data must be encoded into a numeric form, and numeric predictor data should be normalized. For multi-class classification, the dependent ...

Learn how to create a simple neural network, and a more accurate convolutional neural network, with the PyTorch deep learning library PyTorch is a Python-based tensor computing library with high ...

PyTorch 于 2017 年 1 月对外发布，是专注于直接处理数组表达式的较低级别 API。 去年它受到了大量关注，成为学术研究和需要优化自定义表达式的深度 ...

端到端流程：PyTorch模型的RISC-V适配实践 针对PyTorch模型的部署挑战，SiFive提出了一套完整的迁移方案。 陈彦蓁以开源的BEVFormer感知模型为例，说明如何通过ONNX格式转换、IREE编译工具链优化及自定义算子注册，将模型适配至RISC-V平台。

But why should you choose to use PyTorch instead of other frameworks like MXNet, Chainer, or TensorFlow? Let’s look into five reasons that add up to a strong case for PyTorch.