3 Commits (d49eabb3fce6e24fa19b344096b7c5d61e367115)

Author	SHA1	Message	Date
Phaneesh Barwaria	7830c00ca2	onnx.LSTM - bidirectional, layout attr (#3771) ... - Support Bidirectional LSTM (utilising the forward LSTM layer with flipped Inputs and Outputs) - Support layout 1 - Support default cases for attr `clip` and `input_forget` - Support returning partial outputs (1-3) - fixes for alt_e2e_tests lstm tests (1,2,3)	2024-10-08 11:29:49 -07:00
Xida Ren (Cedar)	33eef15e42	Support onnx.If (#2825) ... This is probably a decent PR for learning about blocks and regions. If you're here to learn about that, consider also looking at lib/Conversion/TorchToSCF/TorchToSCF.cpp While this doesn't include an e2e test, it is tested downstream in https://github.com/nod-ai/SHARK-TestSuite/blob/main/e2eshark/onnx/operators/If/model.py --------- Co-authored-by: Xida Ren <xida.ren.dev@gmail.com>	2024-04-30 18:36:40 +00:00
Xida Ren (Cedar)	dd967eb199	[ONNX] Support onnx.LSTM (#2969) ... This PR only performs a lit test. In lieu of an e2e test, https://github.com/nod-ai/SHARK-TestSuite/pull/142 makede sure that the lowering works & the numbers check out. Co-authored-by: Xida Ren <xida.ren.dev@gmail.com>	2024-04-08 12:23:33 -07:00