LudovicoYIN opened a new pull request, #19633: URL: https://github.com/apache/tvm/pull/19633
## Summary Add LSTM (coupled input-forget) and SVDF single-step converters to the TFLite frontend. Both are float32-only; quantized variants are not supported yet. Closes #19519. ## Changes - **LSTM**: FULL kernel type, coupled input-forget gate only. Peephole, projection, and layer norm are not supported - **SVDF**: Standard SVDF with feature projection + time filtering + bias + fused activation - Both converters validate unsupported modes (quantized, non-coupled LSTM) with clear error messages ## Testing - `test_lstm_none_activation` — verifies LSTM converter produces correct IR shapes (batch, input_size) → (batch, num_units) with 3 params (input, h_state, c_state) - `test_svdf_none_activation` — verifies SVDF converter produces correct IR shapes (batch, input_size) → (batch, num_filters) with 2 params (input, state) ```bash python -m pytest tests/python/relax/test_frontend_tflite.py -k "lstm or svdf" -v ``` ## References - TFLite LSTM spec: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/kernels/lstm.cc - TFLite SVDF spec: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/kernels/svdf.cc -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
