Commit Graph

12 Commits (3ccc2214a7adadb1307683b872f8b8dbdc677f40)

Author SHA1 Message Date
Stella Laurenzo 2c9ca79c89 Add boilerplate for Torch dialect. 2020-09-28 15:26:17 -07:00
Stella Laurenzo dd9172fd75 Run clang-format on files that do not comply. 2020-09-15 17:54:58 -07:00
Stella Laurenzo 97d83f786a Bump submodule versions.
* llvm-project: b5924a8e27536d19dd5c4d302db29fb6163d5faa
* mhlo: 848ca244d20f045b7921da55a98a04d95ef94f0e
* Multiple breakages that need to be fixed.

Fixes:
* Refactor dialect registration
* Remove all kindof methods (Casting functionality has been added upstream and is implicitly
available, see https://llvm.discourse.group/t/removing-kinds-from-attributes-and-types/1547.)
* Update dialect registration to comply with https://reviews.llvm.org/D85495.
* Remove type kinds and update some changed dialect signatures.
* Upgrade ATen dialect to match upstream needs.
  * Move dialect registration to tablegen.
  * Register the ListType in tablegen.
  * Change dialect initialization signature.
* Use TypeSwitch in MlirIr location printer.
* Remove global registry depends from npcomp-opt.
* Change LowerToLLVM to pass an MLIRContext vs an LLVMDialect for type creation.
* Remove dep on MLIREDSCInterface that is removed upstream.
* Thread through the DialectRegistry for opt and python-like tools.
* Modernize pass registration (This was forced because the GEN_PASS_REGISTRATION code now generates inline functions vs literal pass registration statements)

Co-authored-by: Marius Brehler <marius.brehler@iml.fraunhofer.de>
2020-09-08 13:26:42 -07:00
stephenneuendorffer bb668e6e26
Add ATen Dialect (#16)
This patch adds a dialect intended to be used as a frontend dialect
to facilitate lowering from "A Tensor Library" in torch/pytorch.

This patch includes several passes that are useful in conjuction with the
dialect:

--aten-layer-name: Generates layer names for each operation, which are not
  present in the original pytorch.
--aten-to-std: Lower the ATen dialect into standard dialect function calls.
--return-elimination-pass: convert functions (primarily the toplevel function)
  to pass return values by reference.  This simplifies pytorch integration.
--aten-op-report: generate a textual report about the model
--liveness-report

Future patches will implement actual integration with the pytorch jit to
intercept and generates MLIR in this dialect, then lower the resulting MLIR
into function calls through aten-layer-name -> aten-to-std ->
return-elimination -> std-to-llvm. The result would then jitted using the LLVM
jit, linked against a runtime library which makes calls back into pytorch to
implement all the layers.

Co-authored-by: Jeff Fifield <jeff.fifield@xilinx.com>

Co-authored-by: Jeff Fifield <jeff.fifield@xilinx.com>
2020-08-12 19:28:04 -07:00
Stella Laurenzo 9e4a62fc71 Allow JITModule passes to be built separately.
* Re-introduces frontent/backend split.
* Adds a (very) trivial shape refinement pass.
2020-07-10 22:57:26 -07:00
Stella Laurenzo efbcf0aa44 Add NumpyPublicFunctionsToTensor pass.
* Rewrites public function signatures to operate on tensors (vs ndarray).
* Most of our backends presume immutable tensors at public function boundaries.
2020-07-08 22:51:54 -07:00
Stella Laurenzo 5ceb37c19b Add NumpyToTCF conversion.
* Just for numpy.add right now.
2020-07-08 21:03:57 -07:00
Sean Silva b4f0cea8fa Rework e2e flow to use new "npcomprt"
This ~totally reworks the existing "runtime" stuff to be more
principled and usable, such as from Python. It's still not fully
production-quality, mainly in the department of memory management (e.g.
it currently leaks memory; we need to figure out "who frees memrefs" +
the analysis and transformation needed to do that (maybe use upstream
buffer allocation pass?)).

The user API is in include/npcomp/runtime/UserAPI.h, though
include/npcomp/JITRuntime/JITModule.h is a friendlier wrapper.

The stuff under {include,lib}/runtime is totally firewalled from the
compiler and tiny (<6kB, though no attention has gone into optimizing
that size). For example, we don't link in libSupport into the runtime,
instead having our own bare bones replacements for basics like ArrayRef
(the JITRuntime helps with bridging that gap, since it *can* depend on
all common LLVM utilities).

The overall features of npcomprt is that it exposes a module that
with multiple function entry points. Each function has arguments and
results that are tensor-valued, and npcomprt::Tensor is the runtime type
that is used to interact with that (and a npcomprt::Ref<T>
reference-counting wrapper is provided to wrap npcomprt::Tensor in the
common case).

From an implementation perspective, an npcomprt module at the
LLVM/object/binary level exposes a single module descriptor struct that
has pointers to other metadata (currently just a list of function
metadata descriptors). All interactions with the npcomp runtime are
keyed off of that module descriptor, including function lookups and
dispatching. This is done to dodge platform ABI issues and also allow
enough reflection to e.g. verify provided arguments.

Most of the compiler-side work here was in LowerToNpcomprtABI and
LowerToLLVM.

Also,
- Rename npcomp_rt/NpcompRt to npcomprt/Npcomprt; it was getting
annoying to type the underscores/caps.
- misc improvements to bash_helpers.sh
2020-07-08 19:36:19 -07:00
Stella Laurenzo 48a0b0ec7f NFC: Move CPATypeInference to Typing directory. 2020-07-04 16:56:09 -07:00
Stella Laurenzo b21b5322f6 Basicpy conversion to IREE+std skeleton and first conversions.
* Conversions to std for numeric binary expressions, numeric to_boolean, and numeric comparisons.
* Added folders to constant ops to comply with requirements of the pass system.
* Extended the frontend with parameter/result annotation processing for primitives (can specify types for function arguments).
* Added (empty) directory/sources for IREEVM conversions. These are only enabled if IREE is enabled.
2020-06-13 23:45:43 -07:00
Stella Laurenzo 2bc7a77f98 Add conditional registration of IREE passes. 2020-06-11 17:57:10 -07:00
Stella Laurenzo 19196f23e1 Make a real library for InitAll and extend it to conditionally initialize dependencies.
* Conditioned on the top level CMake option to enable IREE.
* There is still some warning flags and such that need triage, but it does build/work.
2020-06-11 17:47:14 -07:00