Pytorch 加载 模型

Pytorch with CUDA-aware MPI backend for distributed training

Implementation of Fast Transformer in Pytorch

Implementation of Lumiere, SOTA text-to-video generation from Google Deepmind, in Pytorch

Implementation of Soft MoE, proposed by Brain's Vision team, in Pytorch

pytorch docker images

Implementation of Recurrent Interface Network (RIN), for highly efficient generation of images and video without cascading networks, in Pytorch

pytorch nightly + xformers + deepspeed

An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates concepts from neural fields, top-down-bottom-up processing, and attention (consensus between columns), for emergent part-whole heirarchies from data

一、神经网络的构造 PyTorch中神经网络构造一般是基于 Module 类的模型来完成的，它让模型构造更加灵活。Module 类是 nn 模块里提供的一个模型构造类，是所有神经网络模块的基类，我们可以继承它来定义我们想要的模型。下面继承 Module 类构造多层感知机。这里定义的 MLP 类重载了