![]() ![]() This includes tests for most of the Torch operators, gradient testing, and ModuleInfo based testing. The testing coverage has greatly improved. There is support for the top 60 most used Torch operators, including ops such as grid sampler, triangular solve, topk, and many more. Before covering all the nightly build features, I'll start with what is new in PyTorch 2.0. Latest PyTorch builds contain lots of new updates, such as MPS operation profiling, custom kernel, and Automatic Mixed precision support. This year, PyTorch 2.0 MPS Backend made a great leap forward and has been qualified for the Beta Stage. This was introduced last year into the PyTorch ecosystem, and since then, multiple improvements have been made for optimizing memory usage and view tensors. PyTorch Metal acceleration has been available since version 1.12 through the MPS backend. PyTorch and TensorFlow Metal acceleration enable you to use the highly efficient kernels from MPS to get the best performance on your Mac. This session focuses on the updates and enhancements added to PyTorch and TensorFlow Metal backends, the new GPU acceleration for JAX, and the features added this year to MPSGraph for ML Inference. To learn more about MPSGraph and ML Frameworks, please refer to the previous Metal WWDC talks listed here. MPSGraph also supports training frameworks, like TensorFlow and PyTorch. machine learning inference frameworks, like CoreML, build on top of the MPSGraph backend. MPSGraph is a general purpose compute graph, which sits on top of the MPS framework and extends support to multi-dimensional tensors. MPS is a collection of high-performance GPU primitives for various fields, like image processing, linear algebra, and machine learning. ![]() The Metal machine learning APIs are exposed through Metal Performance Shaders framework. ![]() ![]() I'll first recap the existing machine learning backends. Today I will present to you all the new features and enhancements introduced to machine learning this year in Metal. ♪ ♪ Denis: Hi, my name is Denis Vieriu, and I'm a software engineer in the GPU, Graphics, and Display Software group at Apple. ![]()
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