由于CKBERT采用PyTorch框架实现,与Tensorflow 1.x Graph Execution方式相比,PyTorch采用Eager Execution的方式运行,具有很好的易用性、容易开发调试等特点。但是,Pytorch缺少模型的Graph IR(Intermediate Representation)表达,因此无法进行更深度的优化。受到LazyTensor 和Pytorch/XLA(github.com/pytorch/xla)的启发,PAI团队在P...
This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code here will be included in upstream Pytorch eventually. The intent of Apex is to make up-to-date utilities available to users as quickly as possible. ...
The following steps are required to integrate Amp into an existing PyTorch script:Import Amp from the Apex library. Initialize Amp so it can insert the necessary modifications to the model, optimizer, and PyTorch internal functions. Mark where backpropagation (.backward()) occurs so that Amp can...
Our model is implemented with PyTorch and is trained with one NVIDIA GeForce RTX 3090 card. 对于分类部分,我们采用ResNet38[18]作为主干。For the classification part, we adopt ResNet38 [18] as the backbone.我们使用一个具有多项式衰减策略的SGD优化器,学习率为0.01。We use an SGD optimizer with a...
EasyNLP(https://github.com/alibaba/EasyNLP)是阿⾥云机器学习PAI 团队基于 PyTorch 开发的易⽤且丰富的中⽂NLP算法框架,⽀持常⽤的中⽂预训练模型和⼤模型落地技术,并且提供了从训练到部署的⼀站式 NLP 开发体验。EasyNLP 提供了简洁的接⼝供⽤户开发 NLP 模型,包括NLP应⽤ AppZoo 和预训...
As you can see in this example, by adding 5-lines to any standard PyTorch training script you can now run on any kind of single or distributed node setting (single CPU, single GPU, multi-GPUs and TPUs) as well as with or without mixed precision (fp8, fp16, bf16). ...
EasyNLP(https:///alibaba/EasyNLP)是阿⾥云机器学习PAI 团队基于 PyTorch 开发的易⽤且丰富的中⽂NLP算法框架,⽀持常⽤的中⽂预训练模型和⼤模型落地技术,并且提供了从训练到部署的⼀站式 NLP 开发体验。EasyNLP 提供了简洁的接⼝供⽤户开发 NLP 模型,包括NLP应⽤ AppZoo 和...
In each function, initialize and return the relevant PyTorch DataLoader object (e.g. val_loader from build_validation_data_loader, and train_loader in build_training_data_loader). Step 1.4: Port training and evaluation functions Finally, port your trai...
This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code here will be included in upstream Pytorch eventually. The intent of Apex is to make up-to-date utilities available to users as quickly as possible. ...
scale the training of a 2T parameter model with a streamlined user experience at 1K+ GPU scale. We are bringing these software innovations to you through AzureML (including a fully optimized PyTorch environment) that offers great performance and an easy-to-use interface for large-s...