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# NVIDIA Deep Learning Examples for Tensor Cores
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## Introduction
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This repository provides State-of-the-Art Deep Learning examples that are easy to train and deploy, achieving the best reproducible convergence and performance with NVIDIA CUDA-X software stack running on NVIDIA Volta, Turing and Ampere GPUs.
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## NVIDIA GPU Cloud (NGC) Container Registry
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:
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- The latest NVIDIA examples from this repository
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- 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 ](https://docs.nvidia.com/deeplearning/dgx/index.html#nvidia-optimized-frameworks-release-notes ) for each of the NVIDIA optimized containers
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## Computer Vision
| Models | Framework | DALI | AMP | Multi-GPU | Multi-Node | TensorRT | ONNX | Triton | TF-TRT | Notebook |
| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |------------- |
| Computer Vision |
| [ResNet-50 v1.5 ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Classification/ConvNets/resnet50v1.5 ) |PyTorch | Yes | Yes | Yes | - | - | - | - | - | - |
| [ResNeXt101-32x4d ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Classification/ConvNets/resnext101-32x4d ) |PyTorch | Yes | Yes | Yes | - | - | - | - | - | - |
| [SE-ResNeXt101-32x4d ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Classification/ConvNets/se-resnext101-32x4d ) |PyTorch | Yes | Yes | Yes | - | - | - | - | - | - |
| [Mask R-CNN ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Segmentation/MaskRCNN ) |PyTorch | N/A | Yes | Yes | - | - | - | - | - | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/Segmentation/MaskRCNN/pytorch/notebooks/pytorch_MaskRCNN_pyt_train_and_inference.ipynb ) |
| [SSD300 v1.1 ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Detection/SSD ) |PyTorch | Yes | Yes | Yes | - | - | - | - | - | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/Detection/SSD/examples/inference.ipynb ) |
| [ResNet-50 v1.5 ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Classification/ConvNets/resnet50v1.5 ) |TensorFlow | Yes | Yes | Yes | - | - | - | - | - | - |
| [ResNeXt101-32x4d ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Classification/ConvNets/resnext101-32x4d ) |TensorFlow | Yes | Yes | Yes | - | - | - | - | - | - |
| [SE-ResNeXt101-32x4d ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TEnsorFlow/Classification/ConvNets/se-resnext101-32x4d ) |TensorFlow | Yes | Yes | Yes | - | - | - | - | - | - |
| [Mask R-CNN ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN ) |TensorFlow | N/A | Yes | Yes | - | - | - | - | - | - |
| [SSD320 v1.2 ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Detection/SSD ) | TensorFlow | N/A | Yes | Yes | - | - | - | - | - | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/blob/master/TensorFlow/Detection/SSD/models/research/object_detection/object_detection_tutorial.ipynb ) |
| [U-Net Industrial ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Segmentation/UNet_Industrial ) |TensorFlow | N/A | Yes | Yes | - | Yes | - | - | Yes | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Segmentation/UNet_Industrial/notebooks ) |
| [U-Net Medical ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Segmentation/UNet_Medical ) | TensorFlow | N/A | Yes | Yes | - | Yes |- | - | Yes | - |
| [V-Net Medical ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Segmentation/VNet ) | TensorFlow | N/A | Yes | Yes | - | Yes | Yes | - | Yes | - |
| [U-Net Medical ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/UNet_Medical ) | TensorFlow-2 | N/A | Yes | Yes | - | Yes |- | - | Yes | - |
| [Mask R-CNN ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN ) |TensorFlow-2 | N/A | Yes | Yes | - | - |- | - | - | - |
| [ResNet50 v1.5 ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/MxNet/Classification/RN50v1.5 ) | MXNet | Yes | Yes | Yes | - | - | - | - | - | - |
## Natural Language Processing
| Models | Framework | DALI | AMP | Multi-GPU | Multi-Node | TensorRT | ONNX | Triton | TF-TRT | Notebook |
| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |------------- |
| [BERT ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/LanguageModeling/BERT ) |PyTorch | N/A | Yes | Yes | Yes | - | - | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/LanguageModeling/BERT/triton ) | - | - |
| [Transformer-XL ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/LanguageModeling/Transformer-XL ) |PyTorch | N/A | Yes | Yes | Yes | - | - | - | - | - |
| [GNMT v2 ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Translation/GNMT ) |PyTorch | N/A | Yes | Yes | - | - | - | - | - | - |
| [Transformer ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Translation/Transformer ) |PyTorch | N/A | Yes | Yes | - | - | - | - | - | - |
| [BERT ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/BERT ) |TensorFlow | N/A | Yes | Yes | Yes | Yes | - | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/BERT/triton ) | Yes | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/BERT/notebooks ) |
| [BioBert ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/BERT/biobert ) | TensorFlow | N/A | Yes | Yes | - | - | - | - | - | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/blob/master/TensorFlow/LanguageModeling/BERT/notebooks/biobert_ner_tf_inference.ipynb ) |
| [Transformer-XL ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/Transformer-XL ) |TensorFlow | N/A | Yes | Yes | - | - | - | - | - | - |
| [GNMT v2 ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Translation/GNMT ) | TensorFlow | N/A | Yes | Yes | - | - | - | - | - | - |
| [Faster Transformer ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/FasterTransformer ) | Tensorflow | N/A | - | - | - | Yes | - | - | - | - |
| [Transformer-XL ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/Transformer-XL ) |TensorFlow | N/A | Yes | Yes | - | - | - | - | - | - |
## Recommender Systems
| Models | Framework | DALI | AMP | Multi-GPU | Multi-Node | TensorRT | ONNX | Triton | TF-TRT | Notebook |
| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |------------- |
| [DLRM ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Recommendation/DLRM ) |PyTorch | N/A | Yes | Yes | - | - | Yes | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Recommendation/DLRM/triton ) | - | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Recommendation/DLRM/notebooks ) |
| [Neural Collaborative Filtering ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Recommendation/NCF ) |PyTorch | N/A | Yes | Yes | - | - |- | - | - | - |
| [Wide and Deep ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Recommendation/WideAndDeep ) | TensorFlow | N/A | Yes | Yes | - | - | - | - | - | - |
| [Neural Collaborative Filtering ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Recommendation/NCF ) |TensorFlow | N/A | Yes | Yes | - | - | - | - | - | - |
| [Variational Autoencoder Collaborative Filtering ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Recommendation/VAE-CF ) |TensorFlow | N/A | Yes | Yes | - | - | - | - | - | - |
## Speech to Text
| Models | Framework | DALI | AMP | Multi-GPU | Multi-Node | TensorRT | ONNX | Triton | TF-TRT | Notebook |
| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |------------- |
| [Jasper ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechRecognition/Jasper ) |PyTorch | N/A | Yes | Yes | - | Yes | Yes | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechRecognition/Jasper/trtis ) | - | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechRecognition/Jasper/notebooks ) |
| [HMM ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/Kaldi/SpeechRecognition ) | Kaldi | N/A | - | Yes | - | - | - | Yes | - | - |
## Text to Speech
| Models | Framework | DALI | AMP | Multi-GPU | Multi-Node | TensorRT | ONNX | Triton | TF-TRT | Notebook |
| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |------------- |
| [Tacotron 2 and WaveGlow ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechSynthesis/Tacotron2 ) | PyTorch | N/A | Yes | Yes | - | Yes | Yes | [Yes ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp ) | - | - |
| [FastPitch ](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechSynthesis/FastPitch ) | PyTorch | N/A | Yes | Yes | - | - | - | - | - | - |
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## NVIDIA support
In each of the network READMEs, we indicate the level of support that will be provided. The range is from ongoing updates and improvements to a point-in-time release for thought leadership.
## Feedback / Contributions
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We're posting these examples on GitHub to better support the community, facilitate feedback, as well as collect and implement contributions using GitHub Issues and pull requests. We welcome all contributions!
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## Known issues
In each of the network READMEs, we indicate any known issues and encourage the community to provide feedback.