Commit Graph

31 Commits

Author SHA1 Message Date
Tung D. Le 7c1e67898d
Fuse convolution and batch normalization (#253)
* Rewriting rule

* Fix formulas

* Reuse op results

* Const propagation for Div and Sqrt

* Explicitly use ONNXConstantOp

* Minor revise

* Const propagation for unsqueeze

* Do const propagationnce all tensors have inferred shapes

* LIT tests for fusion

* Add LIT tests for constant propagation on Div, Sqrt, and Unsqueeze

* Missing dash

Co-authored-by: Tian Jin <tjingrant@gmail.com>
2020-08-18 16:41:40 +08:00
Anh Leu a611c145f4
Add Rewrite rule to eliminate CastOp when input element type is the same as expected output element type (#237)
* move scalerop to decompose

* change clang format

* change clang format

* add shape inference for scaler op

* fixing generated onnxop

* generate onnx.md

* add benefit for scaler decompose and simplify scaler shape inference

* cast rewrite only for float

* add cast op same type rewrite rule

* fix format

Co-authored-by: chentong319 <chentong@us.ibm.com>
2020-07-27 12:49:14 -04:00
Anh Leu c9e3ba2d64
Add shape inference for ScalerOp (#228)
* move scalerop to decompose

* change clang format

* change clang format

* add shape inference for scaler op

* fixing generated onnxop

* generate onnx.md

* Add shape inference for scaler op

* add benefit for scaler decompose and simplify scaler shape inference
2020-07-23 13:05:19 -04:00
Anh Leu 4b33c312d6
Add ONNXScalerOp pattern (#220)
* add ONNXScalerOp pattern

* move ScalerOp rewrite rule to Rewrite.cpp .td

* attempt to fix format issue

* fixing format issue

* fixing format issue2

* add ONNXScalerOp pattern

* move ScalerOp rewrite rule to Rewrite.cpp .td

* attempt to fix format issue

* fixing format issue

* fixing format issue2
2020-07-17 11:01:30 -04:00
chentong319 23bea50404
Implement PadOp based on attribute promotion (#71)
* enable promote attr for pad

* use optional arguments for pad

* shape infereance for pad

* Lowering Pad

* format file

* use DenseTensor for the attribute

* use Pad in ONNXRewrite

* fix the merge conflict

* fix the attr given to constantOp

* handle ONNXConstantOp in attribute promotion

* Fix bug when AttributePromotion is called more than once

* update ONNXOps.td.inc with correct version of onnx

* update onnx.md

* responses to review

* fix the build error

* change the implementation of Pad

* delete commented out code

* clang format

Co-authored-by: Tian Jin <tjingrant@gmail.com>
2020-05-15 13:19:28 +08:00
Tung D. Le eac2297624
Lower MaxPooling and AveragePool to Krnl dialect using AffineMap (#38)
* Create a template for pooling and add support for AveragePool

* Edit MLIR tests for MaxPool according to the new lowering template for pooling

* Dealloc temporary variables

* Support count_include_pad for AveragePool

* Add MLIR tests for AveragePool lowering

* Make changes according to Tian's comments

* Push AffineMap as upper bound for KrnlIterateOp

* Test AffineMap to use in Pooling

* Replace the old implementaion by a new one using AffineMap

* Fix the computation when dilations are non-unit

* Clean up the old code

* Remove AveragePool from Canonicalization pass

* Fix computing the end indices of a filter window

* Refactor the code for pooling

* Revise pushAffineMapBound

* Add MLIR tests

* Remove unused functions

* Fix check-onnx-backend build on x86 Linux. (#91)

* Add the split marker to test files (#90)

Co-authored-by: Tian Jin <tjingrant@gmail.com>

Co-authored-by: gongsu832 <gong_su@hotmail.com>
Co-authored-by: Tian Jin <tjingrant@gmail.com>
2020-04-19 21:39:34 +08:00
Tung D. Le e32f531546
Add the split marker to test files (#90)
Co-authored-by: Tian Jin <tjingrant@gmail.com>
2020-04-16 15:17:27 +08:00
Alexandre Eichenberger 653fa69102
Unify Conv implementation (#54)
* fixed readme for new git repo

* conv with bias as an optional input
2020-03-26 11:03:19 -04:00
Gheorghe-Teodor Bercea 1622b9f161
[NFC] Change ONNF based names to ONNX-MLIR (#32)
* Rename onnf to onnx-mlir.

* Change workspace name.
2020-03-17 09:16:33 -04:00
chentong319 6137fc7c17
Fix issues #15 and #16 (#29)
* fix issue #15 and #16

* fix format

Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-03-13 10:19:27 -04:00
Tung D. Le 162ac1bc32
Pad value for MaxPool must be negative infinity instead of zero (#20)
Co-authored-by: Alexandre Eichenberger <alexe@us.ibm.com>
2020-03-12 09:30:02 -04:00
Tung D. Le 1882059ac9
Support Pads for MaxPoolSingleOut (#14)
* Support Pads for MaxPoolSingleOut

* Regenerate onnx.md to include the new op

* Edit comments

* Undo redundant parts that were unintentionally changed

* Move declarative rewriting rules into canonicalize to avoid creating a new op

* Reformat the rewriting rule pattern of MaxPoolSingleOut

* Put ONNXPadConstantValuePadOp's build method into a .cpp file instead of a tablegen file

* Use the same helper function as the one in inferShape for the ONNXPadConstantValuePadOp's build method

* Change function names and fix padding for the spatial dimensions

* Call shape-inference again after canonicalization to infer shape for newly added ops during canonicalization.

* Fix typos
2020-03-09 20:15:58 -04:00
Tung D. Le e97df0b343
Add a pass to decompose ONNX operations (#9) 2020-03-04 10:53:59 -05:00
Tung D. Le 0c4a010283
Remove rank constraints in gemm fusion (#101)
* Remove rank constraints in gemm fusion

* Add an MLIR test

Co-authored-by: Tian Jin <tjingrant@gmail.com>
Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-02-26 11:40:52 -05:00
Gheorghe-Teodor Bercea d4f8fef947
Merge branch 'master' into shapeinference-pad 2020-02-24 16:13:21 -05:00
Tian Jin 9c398c0121
Support Optional Inputs (#94)
* 1. Combine variadicIn/Out with expectedNumOperands/Results to simplify import function arguments.
2. Generic improvements to code readability in gen_doc.py.

* Update ONNX Dialect doc.

* Remove redundant code in ImportNode.

* Prettify op_build_table.inc.

* 1. Remove irrelevant code in gen_doc.py

* Refactor code to be more readable.

* Further refactoring for readability improvements.

* Allow gemm to have an optional operand (bias term), and include an example of declarative optimization pattern targeting gemm with bias term ommitted.

* Make shape inference/lowering of gemm op compatible with optional operand declaration.

* Apply canonicalization again after lowering from onnx -> std dialects.

* Make hasBias compatible with the situation of GemmNoBias op.

* Update doc.

* Add a canonicalization test.

* Remove special handler for importing Gemm op, as it's redundant now.
2020-02-24 23:46:48 +08:00
chentong c11f97f1b5 fix test case for changes in Op definition 2020-02-17 09:07:58 -05:00
chentong ec43fadc3b Merge remote-tracking branch 'upstream/master' into shapeinference-pad 2020-02-17 08:27:43 -05:00
Gheorghe-Teodor Bercea 3c505ae31d
Split convolution into explicit padding and unpaded convolution. (#82)
* Split convolution into explicit padding and unpaded convolution.

* Refactor code. Add test.
2020-02-14 16:06:38 -05:00
chentong c3041bfb43 shape inference for pad with constant pads 2020-02-13 19:56:05 -05:00
chentong319 49dae74eab
Create constant pad (#75)
* handle pad op which does not have the optional third argment

* rewrite PadConstantValue with constant pad into PadConstantValuePad

* add test for PadConstantValuePad

* update onnx.md
2020-02-11 15:32:01 -05:00
Tung D. Le 0564c0eaef
Add constraints for matmul-add fusion (#67)
Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-02-07 13:51:44 -05:00
Tung D. Le 2b56c09454
Rewrite ReduceL1, ReduceL2, ReduceLogSum, ReduceLogSumExp, ReduceSumSquare in the ONNX dialect (#38)
* Rewrite ReduceSumSquare

* Edit gen_doc.py

* Revise the code

* Do shape inference after canonicalization so that there is no need to implement shape inference of rewritten ops

* Rewrite ReduceL2

* Add onnx_rewrite.cpp for all rewriting for ONNX ops

* Rewrite ReduceL1, ReduceLogSum, ReduceLogSumExp

* Edit comments

* Change the use of -> to .

* Checkout gen_doc.py from the master branch

* Use emplace_back instead of push_back

* Revise the code

* Edit comments

Co-authored-by: Tian Jin <tjingrant@gmail.com>
2020-01-31 19:00:39 +08:00
chentong319 c74f814f64 Add attributes as operation parameters (#45)
* add attributes of Op into parameters

* fix rewrite rule for GemmOp with attributes

* use I64Attr instead of I32Attr and modify test cases for the changes in attributes

* add output name (prefixed with o_) to Op definition

* update shape inference for the new attributes
2020-01-27 10:09:14 -05:00
Doru Bercea a42fdd08f3 Fix Gemm translation to ONNX dialect. 2020-01-15 14:11:32 -05:00
TUNG LEDUC d61cf35471 [MLIR] Add one more test case for MatMul-Add fusion (#380)
* Add one more testcase for matmul-add fusion

* Code format for identity elimination testcase
2019-12-21 00:51:54 -05:00
Tian Jin 004762c13d [MLIR] Remove module from test (#379)
* Remove module from test

* Update onnx_canonicalization.mlir
2019-12-21 00:51:23 -05:00
TUNG LEDUC 53ab014a1d [MLIR] Canonicalization pattern for eliminating identity ops (#377)
* Canonicalization pattern for eliminating identity ops

* Add a test for the identity elimination rule

* Remove frontend from test

* Use CHECK-NEXT instead of CHECK
2019-12-21 00:47:22 -05:00
GHEORGHE-TEOD BERCEA bee32e2041 Fix rebase errors. (#378) 2019-12-21 00:46:29 -05:00
TONG CHEN 3f68c5420d [MLIR] generate op from onnx document (#366)
* generate op from onnx document

* Restore FullGemm

* update the op attribute for shape inference and canonicalizer

* Update onnx_canonicalization.mlir
2019-12-21 00:40:40 -05:00
Tian Jin d01ac7732f [MLIR] compartmentalize build script (#369)
* compartmentalize build script, temporarily remove dependency of onnf_opt on helper.cpp

* fix test includes

* fix op directory include

* compiler -> op

* compiler test depends on boost system

* fix function name

* specify libcompiler dependencies

* let cmake take care of transitive dependencies

* remove unnecessary includes

* use ONNF_SRC_ROOT and ONNF_BIN_ROOT

* allow whole-archive linked libraries to be appended

* [MLIR] Support filecheck (#371)

* support lit+FileCheck

* add lit into build script

* format MLIR.cmake

* format cmake

* [MLIR] Remove input/output ops (#372)

* remove input/output ops

* get output tensor type from symbol table
2019-12-21 00:34:51 -05:00