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notable co-releases along with PyTorch 1.5: - TorchServe: model serving infrastructure for scalable model deployment - TorchElastic w/Kubernetes: fault-tolera
by smhx 6y ago
notable co-releases along with PyTorch 1.5:
- TorchServe: model serving infrastructure for scalable model deployment
- TorchElastic w/Kubernetes: fault-tolerant "elastic" neural network training, allowing nodes to join and leave (for eg. to leverage spot pricing)
- Torch_XLA: updates for PyTorch TPU support
- New releases of torchvision, torchaudio and torchtext
Summary blogpost at https://pytorch.org/blog/pytorch-library-updates-new-model-serving-library/ https://pytorch.org/blog/pytorch-library-updates-new-model-s...
- mmq 6y agoAnyone with more info about the difference between TorchElastic and PytorchOperator?
- FridgeSeal 6y agoDamn they’re on fire at the moment (pun sort of intended). Particularly excited about the launch of Serve. I didn’t know about TorchElastic, the name makes me think of ElasticSearch but apart from that I’m keen to get stuck into that as well. Edit: C++ API now having complete parity with Python API is pretty cool, hopefully when that flows through into the Rust binding crate, that should make writing nn applications in Rust nicer.