Commit Graph

2881 Commits (c2c1c2cfa40e89d3acb79c7ccf720ad539e16c56)
 

Author SHA1 Message Date
Sean Silva 6351474382 Bump llvm-project to bc556e5685c0f97e79fb7b3c6f15cc5062db8e36
- `let typeDesription` -> `let description`
- LLVMIntegerType -> IntegerType
2021-01-08 14:18:09 -08:00
Stella Laurenzo 52240e0569 Disable RTTI in the LLVM build.
* It was only required with the old python APIs.
2021-01-08 10:56:57 -08:00
Stella Laurenzo 3f706473fd NFC: Delete npcomp python API and switch to upstream.
* Most updates are mechanical except:
  * python/npcomp/__init__.py and python/NpcompModule.cpp: New init/registration bits to replace some automatic things being done in the old bindings. Also an annoying linkage hack that I'll need to triage next.
  * NpcompModule.cpp: New python helpers for custom types and other hard to reach items (for the new bindings).
  * PybindUtils.h: Extended type casting so that the local extension can directly exchange Mlir* C types.
  * python/npcomp/dialects/*: Build support and ODS bindings for local dialects.
  * mlir_utils.py: Defines an ImportContext to replace the old/bad "Helper" class that tracked locations, and insertion points. This has a number of methods on it that would be good candidates to think about better ways to do them upstream.
* Also hoisted a few stand-alone samples to dedicated unit tests as they covered important things.
* More cleanup can be done, but keeping this patch as mechanical as possible to stay in NFC land (this is big enough).
2021-01-08 10:46:24 -08:00
Stella Laurenzo 951d7ff42c NFC: Add .code-workspace to gitignore. 2021-01-08 10:34:49 -08:00
Sean Silva 97d6d04d41 Bump llvm-project to 16c6e9c58e9ae50a775945e6b407f1891f353d2f
Changes:
- linalg init tensor change (outs+init -> just outs)
- IntegerType::get and other builtin types now take the context as the
  first arg
- LLVMType::* is gone. Now LLVM Types are just regular Type's.
2021-01-05 16:12:11 -08:00
Sean Silva d8261a06d5 Fix scripts to handle the case of nonexistent directory.
Also, touch up the docs.
2021-01-05 14:17:08 -08:00
Brennan Saeta 46d3dd9ddd Update links in features.md
Point to correct files instead of 404's.
2021-01-05 13:52:57 -08:00
powderluv d35724ad0d
Use portable realpath. Its unavailable in !GNU (#145)
realpath is a GNUUtils package that is not available on recent OSX

TEST=Build on OSX systems without GNUutils + zsh

Change-Id: I573855b93a08e1746e0bb214be28b4a3ea8264ca
2020-12-29 13:03:15 -08:00
powderluv 4237172bbf
Fix OSX builds. (#143)
--version_script doesn't work on OSX.
Shared libs are .dylibs on OSX.

TEST=Build on iMac Pro. M1 has other issues will be fixed later

Change-Id: I2bda46349a878b8265e273c05d8db6b46c0df633
2020-12-28 01:30:45 -08:00
Aaron Arthurs 85898aaf10
Add TCF convolutional op with bias addition (#137) 2020-12-15 12:53:12 -08:00
Sean Silva d818043986 Bump llvm-project to d50d7c37a159802c89454a6c53c0ec2e7949d84a
Fixes:
- use `op->(method on Operation)`
- update for MlirIdentifier in signature of mlirNamedAttributeGet
2020-12-14 14:30:51 -08:00
Stella Laurenzo f6d7ee06ef Make torch_mlir compatible with binary PyTorch installations.
* This has been anticipated for a long time in that it is quite hard to keep C++ binary compatibility across a system landscape as diverse as PyTorch, LLVM, and this project. This is why we based the PyTorch extension on the MLIR and NPCOMP C APIs only: that is the only sane linkage story for the entire matrix.
* Removes the few LLVM'isms in torch_mlir that had snuck in, using either STL or PyTorch support utilities. The new rule here is that LLVM C++ includes are forbidden at this level and (as stated in the design), torch_mlir should use the PyTorch runtime and support libraries (not introduce an incidental C++ dependency on LLVM).
* Also deletes mnist-playground as it was proving impossible to keep the grid of PyTorch vs system ABI divisions functioning. I am open to a less drastic course here (optional/disabled by default?)
* This gets us pretty close to just using PyTorch's extension builder API, which will be nice for distribution (i.e. it integrates well with the PyTorch ecosystem for deployment). I ended up just simplifying the in-tree CMake support for now.
* Fixes #138
2020-12-14 09:51:00 -08:00
Sean Silva b2077738ca Bump llvm-project to 444822d77a7fea28aa49edf24533c987efa1b2ee
Fixes:
- renames StandardTypes -> BuiltinTypes
- std.extract_element -> tensor.extract
2020-12-11 14:43:38 -08:00
Sean Silva 251aa6e435 Bump llvm-project to 774f1d3ffd458d6cb82d5039758ef1cf6370957f
Date:   Mon Nov 30 15:20:30 2020 -0800

Changes:
- finalizing-bufferize is stricter now, and we need to pull in a DimOp
  bufferization which was previously working by happenstance. The
  offending DimOp's are actually created by the linalg bufferization
  (which creates dim ops on the original tensor values, not the
  converted memrefs), so the fix is moving std-bufferize after
  linalg-bufferize.
2020-11-30 18:40:13 -08:00
Sean Silva f9b32a99fc Bump llvm-project to 164410324d8bf3b5a99e39f7dfe3c6d6972dab30
Date:   Mon Nov 30 12:44:35 2020 -0800

Fixes:
- func-bufferize is no longer finalizing, so we need to add
  finalizing-bufferize.
2020-11-30 13:58:13 -08:00
Sean Silva 955fd3eeda Add some much-needed comments around refbackrt::invoke.
This code is really tricky, and was not commented.
2020-11-25 15:39:41 -08:00
Sean Silva 46aa6d0a24 [RefBackend] Fix leaks related to ABI boundaries.
Best as I can tell (e.g. from LeakSanitizer), this fixes all the leaks
except for those due to buffers created internally to the codegenned
code itself (up next I'll add the buffer deallocation pass to fix
those).

The main change is that instead of attempting to pass `refbackrt::Tensor`
to the codegenned function directly, we make all the ABI types be
UnrankedMemRef which gets passed awkwardly (but workably) as a
`{size_t rank, void *ptrToDescriptor}` on the ABI. The reason why
refbackrt::Tensor wasn't workable is that is that MLIR doesn't really
have a way to deal with the lifetime of unranked memref descriptors that
happen inside the function, which is inevitably what would happen in the
old code that would emit runtime calls to
`refbackrt.to_memref/refbackrt.from_memref` to convert back and forth to
`refbackrt::Tensor` inside the codegenned code.

So, instead of the `refbackrt.to_memref/refbackrt.from_memref` with no
real sound basis for valid lifetime management, we now have a lovely
piece of code in `refbackrt::invoke` in `Runtime.cpp` that just barely
seems to be sound. We rely on the codegenned code having these
properties, which it seems to have:

- it won't free memref descriptors or their backing buffer for arguments
  of UnrankedMemRef type.

- it will allocate a separate memref descriptor for each result
  UnrankedMemRef (which is ensured by having a separate memref_cast for
  each)

- we can sniff the `allocatedPtr`'s (i.e. the backing buffer pointers)
  to avoid double-freeing in the case of aliasing of the backing buffer
  (including backing buffers for arguments feeding into results)

- to catch the case of statically allocated data (which we need to avoid
  passing to `free`) , check if the `allocatedPtr` is (no joke) equal to
  `0xDEADBEEF`, because there is otherwise no way to distinguish
  statically allocated from malloc'ed data...  (std.global_memref lowering
  to LLVM by happenstance sets the allocatedPtr equal to `0xDEADBEEF`,
  presumably mainly as a debugging thing)

Even with all this, we *still* need to (internally to refbackrt::invoke)
make copies of all inputs/outputs! And the details of how the LLVM-level
ABI gets laid out for e.g. function arguments/returns is still super
tricky.

This really highlights how deficient memref is as the general runtime
type for our use case. It's stewing in my mind how best to improve the
situation. My general gut feeling is that IREE's abstractions for this
are "right", but I need to think more how to distill those aspects of
IREE's design in a "reference" way for RefBackend.

Some implementation notes:

- In terms of how this is implemented, this did catch a bug in our ABI
  wrapper functions in LowerToLLVM.cpp, which I had to fix (it happened to
  work before through some combination of npcomprt::Tensor being passed as
  a single pointer + probably me infinite-monkey-ing it until it worked)

- This actually removes 2 out of the 3 compiler runtime functions (the
  only one left is "abort_if". (most of the memref descriptor code moved
  from CopmilerRuntime.cpp to Runtime.cpp)

  - this also means deleting `refbackrt.from_memref` and
  `refbackrt.to_memref`
2020-11-25 13:09:58 -08:00
Phoenix Meadowlark 699bf5df45
Add cos_e2e.py, test_utils and support for tensor inputs (#134) 2020-11-24 19:02:50 -08:00
Stella Laurenzo e2405e3ca8 Add design sketch for aten fallback. 2020-11-24 18:13:35 -08:00
Stella Laurenzo 3937dd14cb Add basicpy.numeric_constant op.
* Going through TODOs on the PyTorch side, this is a big cause of them (not being able to have constants for signed/unsigned).
* Added complex while in here since we're at the phase where it is better to just have things complete than partially done.
2020-11-24 16:44:40 -08:00
Stella Laurenzo bea0af419d NFC: Prefactor some basicpy ops in advance of more type work.
* Organizes the BasicPyOps.td file by function.
* Renamed `to_boolean` -> `as_predicate_value` (trying to consistently use "predicate" to refer to i1/low-level types and Bool/Boolean to refer to Python bool types).
2020-11-24 15:49:37 -08:00
Stella Laurenzo b0623b7793 Bump LLVM version to 4f5355ee73626f8b8fe6bf0dd6d167fea7628a2c.
* Incorporates changes around LLVM StringRef.
* Ports fix in upstream pybind11 detection.
* Disables CI hack due to broken pybind detection.
2020-11-24 13:12:04 -08:00
meadowlark@google.com 959c0a79cb Expand pytype coverage for torch_signature_ods_gen.py 2020-11-24 12:42:32 -08:00
Sean Silva 0b7c443256 [RefBackend] Properly initialize refbackrt::Tensor refcount.
Although `refCount` is initialized as `std::atomic<int> refCount{0};` in
the definition of Tensor, our tail-allocating malloc would ignore it,
resulting in bogus values that led to leaks.

Caught with LeakSanitizer, but I added an assertion that the refcount is
non-negative to begin with, which should catch this bug in the future
fairly consistently (assuming the garbage refcount is negative half the
time).
2020-11-24 12:01:35 -08:00
Stella Laurenzo f13994fdf7 NFC: Remove TODO about creating an mlirOperationStateDestroy (unnecessary). 2020-11-23 15:01:51 -08:00
Stella Laurenzo 9ffd2556ab Add TorchScript import tests missed in previous change. 2020-11-23 14:43:42 -08:00
Stella Laurenzo 78a3c90758 Add TorchScript graph importer.
* Does not handle all features yet but should conservatively fail on unsupported things.
* Location tracking is still somewhat mismatched between what TorchScript and MLIR do. Likely need a better heuristic for tracking locations from defs for nodes that do not carry location.
* Sets the ground-work for a specialized/generic split but only implements the generic side.
* Had some evidence that this requires a recent bump of PT nightly (within the last month) to pick up pybind11 2.6, which includes some cross-module symbol fixes (vs the previously sync'd version). No source changes, but older versions fail to cast function types at runtime.
2020-11-23 14:20:09 -08:00
Stella Laurenzo 2021d3609e
Make CMAKE_PREFIX_PATH explicit for now (#125)
* Installs numpy as well.
2020-11-22 16:23:36 -08:00
Stella Laurenzo 31d80064a9 Update CI to be verbose about pybind11 detection logic. 2020-11-22 13:42:44 -08:00
Stella Laurenzo f03225b1f1 Bump llvm-project to f4f8a67aaf13bc66a2b7d55561b14a3724a5e0de.
* Incorporates source fixes.
* Uses upstream pybind11 detection logic.
* Patches CI.
* This may break the CI, which will need to be fixed manually in a followup.
2020-11-22 13:14:44 -08:00
Sean Silva 45ca371129 cmake_configure.sh: Add mlir native modules to PYTHONPATH
Also, update README.md to use the canonical .env file written by
`cmake_configure.sh`.
2020-11-20 17:29:57 -08:00
Sean Silva 1dfcfa9cd1 Add aten.mm op and "test" it e2e.
Note that unlike aten.matmul which has dynamic behavior
depending on the argument ranks (can do matrix-matrix, matrix-vector,
batch matmul, etc.), aten.mm is just a vanilla matrix
multiply, which can be lowered precisely to tcf.matmul.

The "test" is really just an example that I stared at while getting my
feet wet with this. We probably want something that actually tests this
as part of `ninja check-npcomp`.
2020-11-20 17:21:24 -08:00
Sean Silva ec1336a8a3 Make pytorch/backend/refjit.py a bit tidier
- Print out initial PyTorch IR.
- Rename ambiguous "frontend IR" to "TCF IR".
- Add newlines to prints
- Rename FRONTEND_PASSES to TORCH_TO_TCF_PASSES
2020-11-20 17:21:24 -08:00
Sean Silva 32b2dc6ce7 Revert "Bump llvm-project to 369c51a74b5327464e27e0749ca7ac59ac1349ce"
This reverts commit c60d7b4aae.

It seems to have tickled some sort of pybind version issue:
https://github.com/llvm/mlir-npcomp/runs/1433414550?check_suite_focus=true
2020-11-20 15:09:18 -08:00
Sean Silva c60d7b4aae Bump llvm-project to 369c51a74b5327464e27e0749ca7ac59ac1349ce 2020-11-20 13:03:24 -08:00
harsh-nod 67d6694fdc
Update PYTHON cmake variables to Python3 (#121)
After the recent change of cmake variables
from PYTHON_INCLUDE_DIRS to Python3_INCLUDE_DIRS
and PYTHON_LIBRARIES to Python3_LIBRARIES, there were
a few files that still had references to the old
variables. This patch fixes that.
2020-11-17 16:04:14 -08:00
Sean Silva 64a7e83184 [RefBackend] Add refback-tcf-to-tcp-pipeline
This allows invoking TCF to TCP-level conversion more easily, and starts
us towards a path of factoring it out of the RefBackend.
2020-11-17 12:33:37 -08:00
Sean Silva 358159a6eb [RefBackend] Open-code shape.get_extent as extract_element
It was annoying that we were creating shape.get_extent in the middle of
the bufferization pipeline, as it required running convert-shape-to-std
at an awkward place. To make that cleaner, just open-code the
extract_element ops that shape.get_extent expands into.

This is a little gross, but it helps with the macroscopic pipeline
ordering issues. Anyway, the train is long-gone of trying to treat
shapes as some special data type that should only be operated on with
shape ops.

Also,
- reorder tensor constant bufferize (which is a module pass) to bracket
all the bufferization function passes, to make the parallelism
opportunities there clearer. Now we have a very clean little
bufferization segment of our pipeline construction.
2020-11-17 11:00:38 -08:00
Stella Laurenzo 4f9c9ecda0 Fix optional Torch package lookup.
* Days since CMake-is-not-a-language failure: 0
2020-11-16 21:41:59 -08:00
Stella Laurenzo a7ff87a922 Sever C++ level depend on IREE and rebase on exe and python interface.
* IREE doesn't have proper install support, so there is some temporary hoaky hacking in our CMakeLists.txt to shuttle some symlinks around.
* Reworked the original numpy e2e with IREE test to pipe through iree-translate.
* Removed all of the C++-level dependencies.
* Will generalize and apply to the PyTorch backend in a followup.
2020-11-16 21:32:56 -08:00
Sean Silva 5227d52c26 [RefBackend] Use std.global_memref instead of homegrown thing
This vastly simplifies our code, allowing deleting multiple ops,
simplifying multiple passes, and removing a whole pass.

Now `refback` dialect is down to one op (refback.alloc_memref, which
simplifies allocations to just take a shape instead of individual
extents).
2020-11-13 18:43:50 -08:00
Stella Laurenzo 6850295ec5 Teach cmake how to find the installed PyTorch.
* In most situations, this eliminates the need to explicitly set a path to the Torch cmake files.
* Also upgrades to new Python3 find package. (should eliminate 2.x mismatches)
* Since PyTorch is located by asking Python where it is, this eliminates a lot of causes of mismatch. (one source of truth)
2020-11-13 17:19:25 -08:00
Sean Silva 32388d938b Make some passes run on FuncOp so they can run in parallel. 2020-11-13 16:12:18 -08:00
Sean Silva 482791fa4a Bump llvm-project to 703ef17e7a0a0f51e1d000bb1f71ad437a9933e4
Date:   Fri Nov 13 15:27:29 2020 -0800
2020-11-13 16:12:18 -08:00
Stella Laurenzo 47ac80491c Delete old PyTorch 1.3 type dispatch oriented code paths.
* We aren't quite at e2e parity, but we aren't going back and the old path is bit-rotted.
2020-11-12 22:27:05 -08:00
Stella Laurenzo e359167562 Fix dispatch of arange.
* Fixes #107
* I wouldn't say I love what had to be done here. Worth a conversation with the PT devs (probably as part of a rollup of a bunch of this stuff).
2020-11-12 22:07:23 -08:00
Stella Laurenzo b4c7ae1e0c Repurpose numpy-compiler compiler/runtime flow for PyTorch.
* A bit gross because I took the chance to upgrade all of the backend bits to the new MLIR Python bindings and we still co-mingle the old and new for now.
* Since the Python created PassManagers are configured for explicit nesting, I had to upgrade some of the pass pipelines to be explicit.
* The demo in mul_maximum_e2e.py now compiles, runs through PyTorch and through the JIT, prints and asserts the same results.
* I am not claiming that this is the prettiest API in this patch: consider that this is just directly using low-level APIs and there should be an intervening high level API.
2020-11-11 10:38:13 -08:00
Stella Laurenzo d1488c8572 Move existing npcomp.compiler -> npcomp.compiler.numpy.
* Makes room for the pytorch compiler.
* Some common things can be hoisted from the numpy side but some more consolidation needs to happen first.
2020-11-10 19:26:40 -08:00
Sean Silva 1c7c362e29 [TCP] Replace tcp.matmul with linalg.matmul.
This involved adding a `tcp.splatted` op to splat a dynamically sized
init tensor. See rationale in TCPOps.td docs.

One interesting observation is that when lowering tcf.matmul to
linalg.matmul, we need to both 1) create the error checks and 2)
calculate a shape transfer function to create the init tensors.
Previously, 2) was deferred to bufferizing tcp.matmul later. I'm not
sure if this is a conflation of concerns or not. For now, it's not a big
burden.
2020-11-10 18:58:28 -08:00
Sean Silva 0427aacb0b [TCP] Replace elementwise ops with std elementwise ops. 2020-11-10 18:58:28 -08:00