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 ...

For PyTorch multi-class classification you must encode the variable to predict using ordinal encoding. The demo sets conservative = 0, moderate = 1 and liberal = 2.

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。

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 ...

The goal of a multi-class classification problem is to predict a value that can be one of three or more possible discrete values, such as "red," "yellow" or "green" for a traffic signal. This article ...

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 ...

What is PyTorch? PyTorch is a deep learning framework designed to simplify AI model development. First released by Meta AI, it was built to improve the flexibility of deep learning research.

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.