This repository provides State-of-the-Art Deep Learning examples that are easy to train and deploy, achieving the best reproducible accuracy and performance with NVIDIA CUDA-X software stack running on NVIDIA Volta, Turing and Ampere GPUs.
These examples, along with our NVIDIA deep learning software stack, are provided in a monthly updated Docker container on the NGC container registry (https://ngc.nvidia.com). These containers include:
- The latest NVIDIA examples from this repository
- The latest NVIDIA contributions shared upstream to the respective framework
- The latest NVIDIA Deep Learning software libraries, such as cuDNN, NCCL, cuBLAS, etc. which have all been through a rigorous monthly quality assurance process to ensure that they provide the best possible performance
- Monthly release notes for each of the NVIDIA optimized containers
| Models | Framework | AMP | Multi-GPU | Multi-Node | TensorRT | ONNX | Triton | DLC | NB |
|---|---|---|---|---|---|---|---|---|---|
| EfficientNet-B0 | PyTorch | Yes | Yes | - | Supported | - | Supported | Yes | - |
| EfficientNet-B4 | PyTorch | Yes | Yes | - | Supported | - | Supported | Yes | - |
| EfficientNet-WideSE-B0 | PyTorch | Yes | Yes | - | Supported | - | Supported | Yes | - |
| EfficientNet-WideSE-B4 | PyTorch | Yes | Yes | - | Supported | - | Supported | Yes | - |
| EfficientNet v1-B0 | TensorFlow2 | Yes | Yes | Yes | Example | - | Supported | Yes | - |
| EfficientNet v1-B4 | TensorFlow2 | Yes | Yes | Yes | Example | - | Supported | Yes | - |
| EfficientNet v2-S | TensorFlow2 | Yes | Yes | Yes | Example | - | Supported | Yes | - |
| GPUNet | PyTorch | Yes | Yes | - | Example | Yes | Example | Yes | - |
| Mask R-CNN | PyTorch | Yes | Yes | - | Example | - | Supported | - | Yes |
| Mask R-CNN | TensorFlow2 | Yes | Yes | - | Example | - | Supported | Yes | - |
| nnUNet | PyTorch | Yes | Yes | - | Supported | - | Supported | Yes | - |
| ResNet-50 | MXNet | Yes | Yes | - | Supported | - | Supported | - | - |
| ResNet-50 | PaddlePaddle | Yes | Yes | - | Example | - | Supported | - | - |
| ResNet-50 | PyTorch | Yes | Yes | - | Example | - | Example | Yes | - |
| ResNet-50 | TensorFlow | Yes | Yes | - | Supported | - | Supported | Yes | - |
| ResNeXt-101 | PyTorch |