[N] PyTorch 1.8 Release, including Compiler and Distributed Training updates, New Mobile Tutorials

• Pytorch

  341 78,205 10.0 Python

  Tensors and Dynamic neural networks in Python with strong GPU acceleration

  

We do allow for TorchScript -> TorchScript transformations, and core contributors like Thomas Viehmann (dunno if he's here on reddit) are working on making improving the Python interface to it (example). That functionality is not going away or anything.

• tutorials

  30 7,829 9.4 Jupyter Notebook

  PyTorch tutorials. (by pytorch)

  

Since it provides you a general computational graph, you can also perform arbitrary analyses on your graph, like using it to profile each operation in your graph (https://github.com/pytorch/tutorials/blob/master/intermediate_source/fx_profiling_tutorial.py).

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• FlexFlow

  2 1,521 9.1 C++

  FlexFlow Serve: Low-Latency, High-Performance LLM Serving

  

Oh, another cool user of FX is FlexFlow, which uses FX to take your PyTorch model and automatically parallelize it.

• dex-lang

  25 1,539 8.5 Haskell

  Research language for array processing in the Haskell/ML family

  

When I've interacted with this kind of thing before -- for example the PyTorch JIT (which I believe also parses an AST to produce an IR? Is this the same parser/IR as fx or different?), the JAX JIT, or something like Zygote in Julia -- I've always hit these kinds of issues. I think the fundamental problem is choosing to parse an AST for something inherently more flexible, rather than building a graph-based DSL a la TensorFlow v1 (despite its flaws), or though I've not tried it, maybe building something like dex.

Suggest a related project