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Update 2020-4-19-pytorch-library-updates-new-model-serving-library.md
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_posts/2020-4-19-pytorch-library-updates-new-model-serving-library.md

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@@ -20,7 +20,6 @@ TorchServe is a flexible and easy to use library for serving PyTorch models in p
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* Logging including common metrics, and the ability to incorporate custom metrics
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* Ready-made Dockerfile for easy deployment
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* HTTPS support for secure deployment
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To learn more about the APIs and the design of this feature, see the links below:
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* See <here> for a full multi-node deployment reference architecture.
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* The full documentation can be found [here](https://pytorch.org/serve).
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* Added the Griffin-Lim functional and transform, `InverseMelScale` and `Vol` transforms, and `DB_to_amplitude`.
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* Added support for `allpass`, `fade`, `bandpass`, `bandreject`, `band`, `treble`, `deemph`, and `riaa` filters and transformations.
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* New datasets added including `LJSpeech` and `SpeechCommands` datasets.
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See the release full notes [here](https://github.com/pytorch/audio/releases) and full docs can be found [here](https://pytorch.org/audio/).
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### torchvision 0.6
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* Faster R-CNN now supports negative samples which allows the feeding of images without annotations at training time.
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* Added `aligned` flag to `RoIAlign` to match Detectron2.
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* Refactored abstractions for C++ video decoder
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See the release full notes [here](https://github.com/pytorch/vision/releases) and full docs can be found [here](https://pytorch.org/docs/stable/torchvision/index.html).
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### torchtext 0.6
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*We’d like to thank the entire PyTorch team, the Amazon team and the community for all their contributions to this work.*
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Cheers!
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Team PyTorch

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