Commit Graph

7 Commits

Author SHA1 Message Date
TUNG LEDUC 5ed79083d5 [MLIR] Add support for Max, Min, Sum, Elu, Selu, LeakyRelu, HardSigmoid (#395)
* Lower ONNXSumOp

* Add inferShapes() and test cases

* Load the first operand to the result

* Update SharingWork.md

* Update SharingWork.md

* Update SharingWork.md

* Add support for Max, Min

* Pass operation instead of location to mapToLowerScalarOp

* Add support for Elu, Selu, LeakyRelu, HardSigmoid

* Add test cases

* Update SharingWork.md

* Rewrite the part of lowering variadic ops and use it for binary ops

* Use two diffenrent templates for Unary and Variadic Ops

* Revise the code
2019-12-21 02:02:09 -05:00
TUNG LEDUC 45608282e0 [MLIR] Add support for Relu (#392)
* Add support for Relu

* Add comments
2019-12-21 01:38:16 -05:00
TUNG LEDUC 1c3176bf9f [MLIR] Lower ONNX element-wise unary ops: Exp, Tanh, Sinh, Cosh, Sigmoid (#389)
* Lower ExpOp

* Lower ONNXTanhOp

* Lower Exp Tanh, Sinh, and Cosh

* Lower ONNX Sigmoid op

* Merge

* Specialize template lowerScalarOp

* Unify ONNXEWUnaryOpLowering and ONNXEWBinaryOpLowering

* Support multiple types

* Reformat the code

* Add test cases

* Reformat the code

* Change names

* Apply clang-format

* Update variable names
2019-12-21 01:37:29 -05:00
TUNG LEDUC c3ef1d93ae [MLIR] Lower ONNX element-wise binary ops: Mul, Div, Sub, And, Or, Xor (#388)
* Lower ONNX element-wise binary ops: Mul, Div, Sub, And, Or, Xor

* Edit gen_doc.py to avoid changes about AnyTypeOf<[AnyMemRef, AnyTensor]>

* Miss a space

* Add tests

* Shorten ONNXElementWiseBinaryOpLowering into ONNXEWBinaryOpLowering

* Move lowering patterns into runOnModule()

* Redundant space
2019-12-21 01:35:31 -05:00
GHEORGHE-TEOD BERCEA b02652dd76 [MLIR] Lowering of frontend dialect to KRNL dialect (#382)
* Partial support for lowering operations to KRNL dialect.

* Attempt to lower to KRNL IR.

* Update file.

* Add lowering.

* Address comments. Fix alloc dynamic dimensions. Correctly link StandardOps.

* Temporarily remove deallocation of locally allocated tensors.
2019-12-21 01:11:14 -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
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