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# NVIDIA Deep Learning Examples for Tensor Cores
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## Introduction
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This repository provides the latest deep learning example networks for training. These examples focus on achieving the best performance and convergence from NVIDIA Volta Tensor Cores.
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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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## Directory structure
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The examples are organized first by framework, such as TensorFlow, PyTorch, etc. and second by use case, such as computer vision, natural language processing, etc. We hope this structure enables you to quickly locate the example networks that best suit your needs. Here are the currently supported models:
### Computer Vision
[ConvNets/TF] Updating RN50, Adding ResNext and SE-ResNext
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- __ResNet-50__ [[MXNet](https://github.com/NVIDIA/DeepLearningExamples/tree/master/MxNet/Classification/RN50v1.5)] [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Classification/ConvNets)] [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Classification/ConvNets)]
- __ResNext__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Classification/ConvNets)] [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Classification/ConvNets)]
- __SE-ResNext__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Classification/ConvNets)] [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Classification/ConvNets)]
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- __SSD__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Detection/SSD)] [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Detection/SSD)]
[MaskRCNN/TF2] Adding MaskRCNN for TF1 and TF2
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- __Mask R-CNN__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Segmentation/MaskRCNN)] [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN)] [[TensorFlow 2](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN)]
Changes in TF models: * added UNet for medical image segmentation * added TF-AMP support for RN50 * small updates for other models (READMEs, benchmark & testing scripts)
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- __U-Net(industrial)__ [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Segmentation/UNet_Industrial)]
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- __U-Net(medical)__ [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Segmentation/UNet_Medical)] [[TensorFlow 2](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/UNet_Medical)]
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- __VNet__ [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Segmentation/VNet)]
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### Natural Language Processing
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- __BERT__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/LanguageModeling/BERT)] [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/BERT)]
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- __GNMT__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Translation/GNMT)] [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Translation/GNMT)]
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- __Transformer__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Translation/Transformer)]
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- __Transformer-XL__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/LanguageModeling/Transformer-XL)] [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/Transformer-XL)]
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### Recommender Systems
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- __DLRM__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Recommendation/DLRM)]
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- __NCF__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Recommendation/NCF)] [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Recommendation/NCF)]
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- __VAE-CF__ [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Recommendation/VAE-CF)]
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- __WideAndDeep__ [[TensorFlow](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Recommendation/WideAndDeep)]
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### Text to Speech
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- __Tacotron2 & WaveGlow__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechSynthesis/Tacotron2)]
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- __FastPitch (modified FastSpeech)__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechSynthesis/FastPitch)]
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Adding Jasper/PyT
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### Speech Recognition
- __Jasper__ [[PyTorch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechRecognition/Jasper)]
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### CUDA Accelerated Applications
- __Kaldi__ [[TRTIS](https://github.com/NVIDIA/DeepLearningExamples/tree/master/Kaldi/SpeechRecognition)]
## Jupyter Notebooks
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| Models | TensorFlow | PyTorch | TensorRT | Triton |
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| ------------- | ------------- | ------------- | ------------- | ------------- |
| SSD | [ Inference](https://github.com/NVIDIA/DeepLearningExamples/blob/master/TensorFlow/Detection/SSD/models/research/object_detection/object_detection_tutorial.ipynb) | [ Inference](https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/Detection/SSD/examples/inference.ipynb) | - | - |
| MaskRCNN | - | [ Training & Inference](https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/Segmentation/MaskRCNN/pytorch/notebooks/pytorch_MaskRCNN_pyt_train_and_inference.ipynb) | - | - |
| Jasper | - | - | [ PyTorch Inference TensorRT Colab](https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/SpeechRecognition/Jasper/notebooks/Colab_Jasper_TRT_inference_demo.ipynb), [ PyTorch Inference TensorRT](https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/SpeechRecognition/Jasper/notebooks/JasperTRT.ipynb) | [ PyTorch Inference TRTIS](https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/SpeechRecognition/Jasper/notebooks/JasperTRTIS.ipynb) |
| Tacotron2 & WaveGlow | - | [ Training & Inference](https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/SpeechSynthesis/Tacotron2/notebooks/Tacotron2.ipynb) | - | [ PyTorch Inference TRTIS](https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/SpeechSynthesis/Tacotron2/notebooks/trtis/notebook.ipynb) |
| BERT | [ Inference Movie Review Sentiment](https://github.com/NVIDIA/DeepLearningExamples/blob/master/TensorFlow/LanguageModeling/BERT/predicting_movie_reviews_with_bert_on_tf_hub.ipynb), [ Fine-Tuning SQuaD](https://github.com/NVIDIA/DeepLearningExamples/blob/80f9481ef8a2c61958f240618077bf89cfce78f6/TensorFlow/LanguageModeling/BERT/notebooks/bert_squad_tf_finetuning.ipynb), [ Inference Colab](https://github.com/NVIDIA/DeepLearningExamples/blob/master/TensorFlow/LanguageModeling/BERT/notebooks/bert_squad_tf_inference_colab.ipynb), [ Inference](https://github.com/NVIDIA/DeepLearningExamples/blob/80f9481ef8a2c61958f240618077bf89cfce78f6/TensorFlow/LanguageModeling/BERT/notebooks/bert_squad_tf_inference.ipynb) | - | - | - |
| BioBERT | [ Inference](https://github.com/NVIDIA/DeepLearningExamples/blob/master/TensorFlow/LanguageModeling/BERT/notebooks/biobert_ner_tf_inference.ipynb) | - | - | - |
| UNet Industrial | [ Export and Inference Colab](https://github.com/NVIDIA/DeepLearningExamples/blob/80f9481ef8a2c61958f240618077bf89cfce78f6/TensorFlow/Segmentation/UNet_Industrial/notebooks/Colab_UNet_Industrial_TF_TFHub_export.ipynb), [ Inference](https://github.com/NVIDIA/DeepLearningExamples/blob/80f9481ef8a2c61958f240618077bf89cfce78f6/TensorFlow/Segmentation/UNet_Industrial/notebooks/Colab_UNet_Industrial_TF_TFHub_inference_demo.ipynb) | - | - | - |
| Automatic Mixed Precision | [ AMP Training](https://github.com/NVIDIA/DeepLearningExamples/blob/80f9481ef8a2c61958f240618077bf89cfce78f6/TensorFlow/docs/amp/notebook_v1.14/auto_mixed_precision_demo_cifar10.ipynb) | - | - | - |
## Feature Matrix
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| Models | Framework | DALI | AMP | Multi-GPU | Multi-Node | TensorRT | ONNX | Triton | TF-TRT |
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| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |
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| [ResNet-50 v1.5](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Classification/ConvNets/resnet50v1.5) |PyTorch | Yes | Yes | Yes | - | - | - | - | - |
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| [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 | - | - | - | - | - |
| [SSD300 v1.1](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Detection/SSD) |PyTorch | Yes | Yes | Yes | - | - | - | - | - |
Added hyperlinks to TRTIS content in Feature Matrix
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| [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) | - |
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| [Transformer-XL](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/LanguageModeling/Transformer-XL) |PyTorch | N/A | Yes | Yes | Yes | - | - | - | - |
| [Neural Collaborative Filtering](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Recommendation/NCF) |PyTorch | N/A | Yes | Yes | - | - |- | - | - |
[WideAndDeep] Improved Spark preprocessing scripts performance
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| [DLRM](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Recommendation/NCF) |PyTorch | N/A | Yes | Yes | - | - |- | - | - |
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| [Mask R-CNN](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Segmentation/MaskRCNN) |PyTorch | N/A | Yes | Yes | - | - | - | - | - |
Added hyperlinks to TRTIS content in Feature Matrix
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| [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) | - |
| [Tacotron 2 And WaveGlow v1.10](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/notebooks/trtis) | - |
Adding FastPitch/PyT (modified version of FastSpeech)
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| [FastPitch](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/SpeechSynthesis/FastPitch) | PyTorch | N/A | Yes | Yes | - | - | - | - | - |
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| [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 | - | - | - | - | - |
[ConvNets/TF] Updating RN50, Adding ResNext and SE-ResNext
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| [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 | - | - | - | - | - |
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| [SSD320 v1.2](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Detection/SSD) | TensorFlow | N/A | Yes | Yes | - | - | - | - | - |
[FastPitch/PyT] Small README fixes
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| [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 |
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| [BioBert](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/BERT/biobert) | TensorFlow | N/A | Yes | Yes | - | - | - | - | - |
Adding Transformer-XL/TF
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| [Transformer-XL](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/Transformer-XL) |TensorFlow | N/A | Yes | Yes | - | - | - | - | - |
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| [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 | - | - | - | - | - |
Adding WideAndDeep/TF
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| [WideAndDeep](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Recommendation/WideAndDeep) | TensorFlow | N/A | Yes | Yes | - | - | - | - | - |
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| [U-Net Industrial](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/Segmentation/UNet_Industrial) |TensorFlow | N/A | Yes | Yes | - | Yes | - | - | Yes |
| [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 |
[MaskRCNN/TF2] Adding MaskRCNN for TF1 and TF2
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| [Mask R-CNN](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN) |TensorFlow | N/A | Yes | Yes | - | - | - | - | - |
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| [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 | - | - | - |
[WideAndDeep] Improved Spark preprocessing scripts performance
2020-05-18 01:11:27 +02:00
| [Transformer-XL](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/Transformer-XL) |TensorFlow | N/A | Yes | Yes | - | - | - | - | - |
[MaskRCNN/TF2] Adding MaskRCNN for TF1 and TF2
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| [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 | - | - |- | - | - |
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| [ResNet50 v1.5](https://github.com/NVIDIA/DeepLearningExamples/tree/master/MxNet/Classification/RN50v1.5) | MXNet | Yes | Yes | Yes | - | - | - | - | - |
| [HMM](https://github.com/NVIDIA/DeepLearningExamples/tree/master/Kaldi/SpeechRecognition) | Kaldi | 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.
Updating models and adding BERT/PyT Tacotron2+Waveglow/PyT * AMP support * Data preprocessing for Tacotron 2 training * Fixed dropouts on LSTMCells SSD/PyT * script and notebook for inference * AMP support * README update * updates to examples/* BERT/PyT * initial release GNMT/PyT * Default container updated to NGC PyTorch 19.05-py3 * Mixed precision training implemented using APEX AMP * Added inference throughput and latency results on NVIDIA Tesla V100 16G * Added option to run inference on user-provided raw input text from command line NCF/PyT * Updated performance tables. * Default container changed to PyTorch 19.06-py3. * Caching validation negatives between runs Transformer/PyT * new README * jit support added UNet Medical/TF * inference example scripts added * inference benchmark measuring latency added * TRT/TF-TRT support added * README updated GNMT/TF * Performance improvements Small updates (mostly README) for other models.
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Reference in a new issue Copy permalink