onnx-mlir/src
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
..
builder Support Optional Inputs (#94) 2020-02-24 23:46:48 +08:00
conversion/onnx_to_krnl Support Optional Inputs (#94) 2020-02-24 23:46:48 +08:00
dialect Support Optional Inputs (#94) 2020-02-24 23:46:48 +08:00
pass Support Optional Inputs (#94) 2020-02-24 23:46:48 +08:00
runtime Lower BatchNormalization (test mode) to Krnl dialect (#70) 2020-02-20 11:45:40 -05:00
tool Fix building ONNF with latest LLVM/MLIR (#89) 2020-02-19 18:15:02 -05:00
transform Fix building ONNF with latest LLVM/MLIR (#89) 2020-02-19 18:15:02 -05:00
CMakeLists.txt Add result type inference to op definition (#87) 2020-02-21 22:28:24 +08:00
main.cpp Support Optional Inputs (#94) 2020-02-24 23:46:48 +08:00