Commit Graph

49 Commits (d849cbad14730c2af35ced046df03be2fe9a87eb)

Author SHA1 Message Date
Jae Hoon (Antonio) Kim 1d695239ff
Unrevert #1724 (#1737)
* Unrevert #1724

* Update pytorch requirements.txt
2022-12-20 11:17:21 -05:00
Ashay Rane dd1cf578a6
build: fix LTC code after upstream PyTorch change (#1727)
pytorch/pytorch@140a3139 reverted a change from yesterday, causing the
RollPyTorch action to break.  This patch reverts the corresponding
change in the torch-mlir LTC code.

This patch also re-enables tests that were previously marked as XFAIL.
2022-12-16 13:07:38 -06:00
Jae Hoon (Antonio) Kim a2a93891ea
Replace asIntArrayRefSlow with macro (#1724)
* Replace asIntArrayRefSlow with macro

* Update pytorch requirements.txt
2022-12-15 11:52:41 -05:00
Gleb Kazantaev 804f9f1f8f
Extended TorchMLIRLoweringContext with virtual CreateComputation method (#1699)
* Extended TorchMLIRLoweringContext with virtual CreateComputation method

* Fix device_data_cast return value
2022-12-08 15:57:07 -05:00
Vivek Khandelwal d9cbf01d1e Revert "build: update llvm tag to 147fe9de"
This reverts commit e45ad313d4.
2022-11-25 12:41:56 +05:30
Vivek Khandelwal e45ad313d4 build: update llvm tag to 147fe9de
Summary of changes:
- Update call to `hasNoEffect` utility
- `KDynamicSize` value changed to
  `std::numeric_limits<int64_t>::min()` from `-1`
- Update tags
  llvm: 147fe9de29dc13c14835127b35280c4d95c8e8ba
  mhlo: 1944b5fa6062ec4c065d726c9c5d64f1487ee8c5

Signed-Off By: Vivek Khandelwal<vivek@nod-labs.com>
2022-11-24 12:44:43 +05:30
Gleb Kazantaev 6909eaf7fc
Update TorchMlirBackendImpl Methods (#1580)
* Fix LTC build

* Remove passing test from xfail set
2022-11-14 00:37:49 -05:00
Jae Hoon (Antonio) Kim 2ec4b06bbb
Remove MakeView from IR Builder (#1552)
* Remove MakeView from IR Builder

* Update PyTorch requirements
2022-11-09 13:46:34 -05:00
Jae Hoon (Antonio) Kim 0701464c47
Remove view ops from IR builder (#1534)
* Remove view ops from IR builder

* Update PyTorch requirements
2022-10-30 21:42:44 -04:00
Jae Hoon (Antonio) Kim 2f300935bf
Reference lazy graph executor (#1507)
* Add LazyGraphExecutor registration

* Update PyTorch version to 1.14.0.dev20221024

Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
2022-10-24 17:15:11 -04:00
Gleb Kazantaev bdb5083d33
New ops support & enhancements (#1494)
* New ops support & enhancements

* Enabled xfail ltc tests
2022-10-14 10:28:21 -04:00
Jae Hoon (Antonio) Kim 3e08f5a779
Fix `fromIntArrayRef` call (#1479)
* Fix fromSymint call

* Update PyTorch requirement

* Re-enable LTC
2022-10-11 13:29:07 -04:00
Jae Hoon (Antonio) Kim c57d801260
Fix functionalize_aten_op calls for symint ops (#1459)
* Fix functionalize_aten_op calls for symint ops

* Update PyTorch version
2022-10-05 10:23:48 -04:00
Jae Hoon (Antonio) Kim fa5a8e21a3
Propagate parameter names to TorchMlirComputation (#1420)
* Propagate parameter name to MLIR

* Add TorchMlirNode Constructor Hook

* Make func_op mutable

- Purpose of this is to allow modification of func_op by subclass
  backend

* Clean up unnecessary changes

* Remove unnecessary attribute case

* Address PR comments
2022-09-29 11:43:39 -04:00
Jae Hoon (Antonio) Kim 3e27aa2be3
Fix as_strided/slice symint (#1401)
* Fix as_strided symint

* Re-enable LTC tests

* Re-enable LTC

* Add hardtanh shape inference function

* Fix slice symint
2022-09-26 12:16:49 -04:00
Jae Hoon (Antonio) Kim 8967463980
Fix symint ops and blacklist `lift_fresh_copy` (#1373)
* Add symint to native functions yaml

* Re-enable LTC

* Fix new_empty_strided and narrow_copy
2022-09-20 10:16:04 -04:00
Jae Hoon (Antonio) Kim 8e880a2d00
Fix symint related functionalization ops (#1289)
* Fix symint related functionalization ops

* Remove zeros xfail from LTC tests
2022-08-26 16:13:28 -04:00
Henry Tu e869e68559
Fix LTC lib_torch_mlir_ltc.so import error (#1283)
* Build LTC to _mlir_libs directory

* Update CMakeLists.txt
2022-08-25 18:25:01 -04:00
Henry Tu a1ace0657d
Revert updating mlir_native_functions.cpp signature (#1281)
* Revert updating mlir_native_functions.cpp signature, due to a7edf71360

* Restored NewZeros to LTC XFAIL set
2022-08-25 13:00:33 -04:00
Henry Tu e2f862cb85
Fix LTC build warnings (#1272)
* Resolved Wunused-variable

* Fix Wunneeded-internal-declaration

* Address review comment

* Update autogen_ltc_backend.py

* Update mlir_native_functions.cpp to work with updated PyTorch

* Remove NewZeros from LTC XFAIL set
2022-08-24 15:04:28 -04:00
Henry Tu ba17a4d6c0
Reenable LTC in out-of-tree build (for real this time) (#1205)
* Fix OOT LTC CI build failure

* Disable LTC during macOS package gen

* Add more details about static TorchMLIRJITIRImporter library
2022-08-19 15:25:00 -04:00
Jae Hoon (Antonio) Kim 0af55781ae
Propagate device data names (#1157)
* Propagate device data names

* Address PR comment

* Add example usage

* Add test for device data names

* Make TorchMlirComputation fields protected

* Add lazy backend device data name unit tests

* Disable lazy backend tests if LTC is disabled

* Add comments
2022-08-16 09:30:22 -04:00
Sambhav Jain 41aa562fb4
s/external/externals/g (#1222)
Fix remaining instances of `external/llvm-project`.
2022-08-13 07:13:56 -07:00
Henry Tu 2c3b3606d0 Resolve remaining LTC CI failures (#1110)
* Replace CHECK_EQ with TORCH_CHECK_EQ

* Check value of TORCH_MLIR_USE_INSTALLED_PYTORCH during LTC build

* Update LTC XFAIL with NewZerosModule ops

* Explicitly blacklist _like ops

* Automatically blacklist new_/_like ops

* Prune away unused Python dependencies from LTC

* Add flag to disable LTC

* Autogen dummy _REFERENCE_LAZY_BACKEND library when LTC is disabled

* Implement compute_shape_var

* Removed Var tests from XFAIL Set

* XFAIL tests using _local_scalar_dense or index.Tensor

* Add StdDim tests to XFAIL set

* Autogen aten::cat
2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim 368963243e Export LTC Headers (#1108) 2022-07-30 09:40:02 -04:00
Henry Tu 70395de197 Resolve CI testing failure for Lazy Tensor Core (#1088)
* Xfail unsupported ops

* Register FuncDialect

* Include dynamic_ir in build

* Code reformat

* Enable LTC tests for macOS and Source Build
2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim 0d16a91656 Add support for lift_fresh op (#1101) 2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim e37891b997 Default Device Ordinal API (#1079)
* Add default device ordinal API

* Fix reference backend
2022-07-30 09:40:02 -04:00
Antonio Kim de6c135dc3 Fix LTC autogen for CI with nightly PyTorch
- Update llvm-project pin to match main
2022-07-30 09:40:02 -04:00
Henry Tu 47bb38d180 Reference Lazy Backend (#1045)
* Changed Example MLIR backend to Reference MLIR backend

* Moved reference_ltc_backend into csrc

* Merged sys_utils.h

* Renamed reference_ltc_backend to reference_lazy_backend

* Addressed review comments

* Update docs with new library name

* Removed _REFERENCE_LAZY_BACKEND from .gitignore

* Added reference_lazy_backend to the TorchMLIRPythonModules dependency list

Fixed typo in `ltc_examples.md`

Missed instance where `ltc_backend` was used instead of `lazy_backend`.
2022-07-30 09:40:02 -04:00
Henry Tu 9de06f3ebd Update Torch MLIR readme 2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim fb21c9e6cb Integrate Functionalization Pass (#998)
* Fix autogen build dir issue

* Got functionalization pass to compile

* Add slice/diagonal backwards functionalization

* Fix codegen invocation in CMakeLists.txt

* Add functionalization view ops

* Fix logsumexp out functionalization

* Fix ComputationPtr

* Blacklist new_empty op

* Add op comparison

* Remove unnecessary ops

Co-authored-by: Henry Tu <henry.tu@cerebras.net>
2022-07-30 09:40:02 -04:00
Henry Tu 1510eae75d Upstream native_batch_norm and native_batch_norm_backward shape inference functions (#978)
* Removed compute_shape_native_batch_norm

* Removed compute_shape_native_batch_norm_backward
2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim a62d60829c Refactor autogen (#925) 2022-07-30 09:40:02 -04:00
Henry Tu dfcc26556a Added e2e LTC tests (#916)
* Added e2e LTC Torch MLIR tests

* Fix seed for reproducability

* Check if computation is None before getting debug string

* Updated unit tests, and added numeric tests

* Print name of the model layer that fails numeric validation

* Run LTC e2e test with CI/CD

* Set seed in main function, instead of beginning of execution

* Add comment to specify number of digits of precision

* Fixed typo

* Remove tests for LTC example models

* Added LTC option to torchscript e2e

* Implement compile and run for LTC e2e test

* xfail all tests that use ops that aren't currently supported
2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim 8312fa535b Refactor Node Lowering (#914) 2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim d9aee0d7a7 E2E HuggingFace Bert using LTC Backend (#912)
* Update native function definitions

* Add ops to support bert lowering

- Add empty_strided and as_strided

- Restore zeros_like to op blacklist (Without this, tensors will be unintentionally created with a CPU device rather than lazy)

- Check for composite implicit ops and add device data IR

- Also fix codegen for functionalization

* Add autogen to CMakeList

* Remove PyTorch submodule

* Reduced BERT model size

* Print Mark Step status in Torch MLIR LTC debug string

* Apply fixes to work with latest upstream/main

- Pass importOptions into getMlirTypeFromTorchType during NodeImporter::importNode

  Without this, the tensor type created may have a mismatched type as ImportOptions may cause vtensor to be used instead of tensor

* Update shape inference functions

- Fixed compute_shape_native_batch_norm when mean and var are uninitialized

  Previously, the number of shapes returned would be <3 if either mean or val was didn't exist. Instead, we now initialize them with a vector matching the number of channels.

- Implemented compute_shape_mul

- Fixed bug in reshape shape inference error message

* Get MLIR backend more consistent with TS backend

- Remove LazyNativeFunctions::_unsafe_view from autogen

- Blacklist ops to make JIT graph more like output of TS backend

- Print graph when SSA value has mismatch of types and results

- Remove normalize_index from LazyShapeInference

- Fix seeds for LTC example models

* Update and clean up shape inference functions

- Prune shape inference functions

- Add shape inference function for GenerateSlice

- Add shape inference function for GenerateCopy

Co-authored-by: Henry Tu <henry.tu@cerebras.net>
2022-07-30 09:40:02 -04:00
Henry Tu 0c35e607b3 Add static shape for scalar tensors (#833)
* Assume zero rank tensors are scalar

* Run RefineTypes pass on JIT Graph

* Rollback assumption that zero rank tensors are scalar

* Set numSizes to -1 for non-ranked tensors

* Rename RefineTypes to RefineTupleTypes
2022-07-30 09:40:02 -04:00
Henry Tu de5b380143 Bert example and relevant shape inference functions (#831) 2022-07-30 09:40:02 -04:00
Henry Tu 406d1e7538 Use JIT GraphExecutor for execution in example backend (#830)
* Update LazyShapeInference header

* Use JIT GraphExecutor for execution in example backend
2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim 1bde00c73d Fix LTC Decoupling (#815)
* Initial changes

* Fix up native functions

* Further fix decoupling

* Remove unnecessary ops

* Formatting and copyright banners:

* Add pytorch submodule
2022-07-30 09:40:02 -04:00
Henry Tu cca9fe126e Enable support for LTC Input/Output Mapping (#764)
* Save InputOutputAliases to TorchMlirComputation

* Implement GetResultShape for TorchMlirLoweringContext

* Use optional return type for GetResultShape

* Remove support for aten::detach

With this op enabled, tensors were being copied, which resulted in incorrect aliasing.

* Add newline before printing I/O alias mapping

* Changed printout to use "Input param" as label instead of "Input"

* Remote shape inference function for aten::detach

* Moved implementation of SetUpAlias to MlirLoweringContext

As part of this change, TorchMlirComputation has been moved to the end of mlir_lowering_context.h so that it can access some new structs in TorchMlirLoweringContext

* Use updated PyTorch API

* Remove GetResultShape

Complements this upstream PyTorch PR: pytorch/pytorch#75828

This PR adds support for mapping input and output tensors which alias each other. (e.g. maps input weight tensor in parameter to the same tensor in output after a training iteration)

MLIR: 
func @graph(%arg0: !torch.vtensor<[1,5],f32>, %arg1: !torch.vtensor<[1],si64>, ..., %arg6: !torch.vtensor<[10,5],f32>, %arg7: !torch.vtensor<[10],f32>, ...) {
  ...
  return %arg0, %arg1, %17, %23, ... : !torch.vtensor<[1,5],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[10,5],f32>, !torch.vtensor<[10],f32>, ...
}

Input/Output Alias Mapping: 
Output: 0 -> Input: 0
Output: 1 -> Input: 1
Output: 2 -> Input: 6
Output: 3 -> Input: 7
The aten::detach op has also been disabled in this PR to fix the issue of tensors not aliasing properly due to copying.
2022-07-30 09:40:02 -04:00
Antonio Kim 615ff1d31c Generate MLIR with shape information via LTC frontend (#742) 2022-07-30 09:40:02 -04:00
Henry Tu a605fe279c Add example Torch MLIR LTC Backend (#725) 2022-07-30 09:40:02 -04:00
Henry Tu 3e9b1cbd36 Added JIT to MLIR lowering (#724)
* Added JIT to MLIR lowering

Lowering to JIT is performed in a way similar to how it's done in the TS LTC backend. After a jit::Graph is constructed, it gets converted to a jit::Function, which is fed into the existing utility to generate an MlirModule in torch-mlir.

* Renamed `csrc/backend` to `csrc/base_lazy_backend`
2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim 65cf1465ef Fix Torch-MLIR LTC Backend based off latest PyTorch master (#723)
* Changes as a result of the LTC TS backend decoupling

* Fix bugs in BackendImpl and codegen

* Fix based on latest PyTorch master
2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim c3b20e444c Got LTC working until compile (#689) 2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim 58338f79a1 Torch-MLIR LTC Backend Lowering Codegen (#621)
* Codegen and build LTC lowering

* Add LazyShapeInference header
2022-07-30 09:40:02 -04:00
Jae Hoon (Antonio) Kim 2f22e2ef40 Add initial LTC backend (#610)
* Add initial LTC backend skeleton

* Disable CI build and move TorchMLIRPyTorch.cmake
2022-07-30 09:40:02 -04:00