LudovicoYIN opened a new pull request, #19634:
URL: https://github.com/apache/tvm/pull/19634
## Summary
Add three TFLite sequence recurrent operators to the Relax frontend, all with
coupled input-forget gate (FULL kernel) and float32-only support.
- UNIDIRECTIONAL_SEQUENCE_LSTM
- BIDIRECTIONAL_SEQUENCE_RNN
- BIDIRECTIONAL_SEQUENCE_LSTM
Closes #19519.
## Changes
- **UNIDIRECTIONAL_SEQUENCE_LSTM**: same layout as single-step LSTM, unrolls
over
time and stacks per-step hidden states. Supports time_major, cell_clip,
proj_clip,
and fused activation.
- **BIDIRECTIONAL_SEQUENCE_RNN**: separate fw/bw RNN cells, backward scans in
reverse. Supports merge_outputs (concat fw + bw) and split outputs via
Tuple.
- **BIDIRECTIONAL_SEQUENCE_LSTM**: 48-input operator with fw/bw LSTM cells
sharing
the same input tensor. States at indices 35-38.
- All converters propagate final states to exp_tab for multi-step
correctness.
- Peephole, projection, layer norm, and aux input are not supported (raise
OpNotImplemented).
## Testing
- `test_unidirectional_sequence_lstm_none_activation` — output shape [batch,
time, num_units]
- `test_bidirectional_sequence_rnn_none_activation` — merge_outputs=True,
shape [batch, time, 2*num_units]
- `test_bidirectional_sequence_lstm_none_activation` — merge_outputs=True,
shape [batch, time, 2*num_units]
```bash
python -m pytest tests/python/relax/test_frontend_tflite.py -k
"sequence_lstm or sequence_rnn" -v
```
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