Mobile build customization, Distributed model parallel training, Java bindings, and more

Mobile build customization, Distributed model parallel training, Java bindings, and more pytorch / pytorch Public Notifications You must be signed in to change notification settings Fork 30.5k Star 103k Mobile build customization, Distributed model parallel training, Java bindings, and more nairbv released this 16 Jan 00:03 v1.4.0 7f73f1d PyTorch 1.4.0 Release Notes Highlights Backwards Incompatible Changes Python JIT C++ New Features torch.optim Distributed RPC [Experimental] JIT Mobile Improvements Distributed JIT Mobile Named Tensors C++ API AMD Support ONNX Quantization Visualization Other Improvements Bug Fixes Distributed RPC C++ API JIT Quantization Mobile Other Bug fixes Deprecations Performance The PyTorch v1.4.0 release is now available. The release contains over 1,500 commits and a significant amount of effort in areas spanning existing areas like JIT, ONNX, Distributed, Performance and Eager Frontend Improvements and improvements to experimental areas like mobile and quantization.

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• pytorch / pytorch Public Notifications You must be signed in to change notification settings Fork 30.5k Star 103k Mobile build customization, Distributed model parallel training, Java bindings, and more nairbv released this 16 Jan 00:03 v1.4.0 7f73f1d PyTorch 1.4.0 Release Notes Highlights Backwards Incompatible Changes Python JIT C++ New Features torch.optim Distributed RPC [Experimental] JIT Mobile Improvements Distributed JIT Mobile Named Tensors C++ API AMD Support ONNX Quantization Visualization Other Improvements Bug Fixes Distributed RPC C++ API JIT Quantization Mobile Other Bug fixes Deprecations Performance The PyTorch v1.4.0 release is now available.
• The release contains over 1,500 commits and a significant amount of effort in areas spanning existing areas like JIT, ONNX, Distributed, Performance and Eager Frontend Improvements and improvements to experimental areas like mobile and quantization.
• It also contains new experimental features including rpc-based model parallel distributed training and language bindings for the Java language (inference only).
• PyTorch 1.4 is the last release that supports Python 2 .
• For the C++ API, it is the last release that supports C++11: you should start migrating to Python 3 and building with C++14 to make the future transition from 1.4 to 1.5 easier.
• Highlights PyTorch Mobile - Build level customization Following the experimental release of PyTorch Mobile in the 1.3 release , PyTorch 1.4 adds additional mobile support including the ability to customize build scripts at a fine-grain level.