See the documentation in `docs/shape_lib.md` and
`docs/adding_a_shape_function.md` for an overview of the system.
This completely overhauls how we represent shape functions. In
particular, RefineTypes does not infer shapes anymore (only dtypes).
Shape functions are now written in (TorchScript'able) Python.
Recommended review order:
1. Read `docs/shape_lib.md` and `docs/adding_a_shape_function.md`.
1. Code and tests for ReifyShapeCalculations, DropShapeCalculations.
1. Code and tests for SimplifyShapeCalculations.
1. shape_lib_gen.py
1. Code and tests for new RefineTypes pass.
1. Random folders/canonicalizers in TorchOps.cpp and associated test in
`canonicalize.mlir`.
1. New ReadOnly trait inferred from the registry.
1. Any miscellaneous remaining stuff.
Example `-print-ir-after-all` for ElementwiseUnaryModule:
[IR lowering dump](https://gist.github.com/silvasean/e4dc8cbc8d00aac7819602e3cbd8e212).
Example `-print-ir-after-all` for ElementwiseBinaryModule:
[IR lowering dump](https://gist.github.com/silvasean/daf6860ecced732af3568af6b1899113).
* Forks a subset of my shell functions into docker_shell_funcs.sh, specifically needed to create docker images that run as yourself.
* Extends the readme with the three command bootstrap to get a dev container running.
* Step by step instructions for configuring VSCode for Intellisense in either npcomp or LLVM.
* Changes LLVM config options to enable tests. This setup is now suitable for upstream changes as well without rebuilding.
* This starts to lay down the infra for reasoning about calls
* Adds the importer code to generate IR for function calls of compiler recognized static functions.
Sean Silva
Brennan Saeta
Stella Laurenzo
Phoenix Meadowlark
Stella Laurenzo