Pytorch
About
Production Ready
Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe.
Distributed Training
Scalable distributed training and performance optimization in research and production is enabled by the torch.distributed backend.
Robust Ecosystem
A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more.
Cloud Support
PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling.
Specification
Specification
Package
Pytorch
You May Also Like
Related products
-
CUDA
SKU: N/ACUDA is a parallel computing platform and programming model developed by Nvidia for general computing on its own GPUs (graphics processing units). CUDA enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation. This post is a super simple introduction to CUDA, the popular parallel computing ...More Information -
DOCKER
SKU: N/AMore InformationDocker is the de facto developer standard for building and sharing apps that enable simplicity, agility and choice for software development across any infrastructure so that you can get your job done and deploy your applications faster. Docker provides developer-friendly, CLI-based workflow and makes it easy to build, share, and run containerized applications. Even your most complex applications can be containerized. You can build locally, deploy to the cloud, and run anywhere. -
cuDNN
SKU: N/ANVIDIA cuDNN The NVIDIA CUDA® Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. Deep learning researchers and framework developers worldwide rely on cuDNN for high-performance GPU acceleration. It allows them ...More Information
Our Customers
Previous
Next