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
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onnx_canonicalization.mlir	Support Optional Inputs (#94)	2020-02-24 23:46:48 +08:00
onnx_lowering.mlir	Lower BatchNormalization (test mode) to Krnl dialect (#70)	2020-02-20 11:45:40 -05:00
onnx_lowering_with_dealloc.mlir	Chentong319 attribute with variant (#25)	2020-01-21 19:36:21 -07:00
onnx_shape_inference.mlir	Allow 1-D convolutions. (#86)	2020-02-14 10:54:08 -05:00
onnx_shape_inference_maxpool.mlir	Inference maxpool (#48)	2020-01-30 14:30:28 -05:00