torch-mlir

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
Kyle Wang	f0b7ca72f5	Fixed GRU quality issues exposed by e2e tests (#3753 ) Issue: https://github.com/nod-ai/SHARK-ModelDev/issues/856 Related tests: ![Screenshot 2024-10-01 175305](https://github.com/user-attachments/assets/0dc0901b-058f-427c-a596-9e806fd38836)	2024-10-02 17:00:19 -04:00
Rob Suderman	78deb175b3	[onnx] Fix shortcircuit path (#3633 ) The implementation was short circuiting the second result. Updated to guarantee we do not short circuit.	2024-08-16 09:23:47 -07:00
Rob Suderman	2511cf46b4	[onnx] Fix `onnx.RNN` for layout attribute (#3620 ) The `layout` attribute was not considered for the `onnx.RNN` operation. Added support for the attribute to transpose the inputs / outputs of the RNN when valid.	2024-08-13 14:34:25 -07:00
Xida Ren (Cedar)	5342aa70cf	Support onnx.GRU and onnx.RNN (#3447 )	2024-07-10 14:04:17 -04:00