The GitHub Actions job "Teams" on tvm.git/main has succeeded.
Run started by GitHub user tlopex (triggered by tlopex).

Head commit for run:
576e60e9744a1baea921ce054829925e192d3817 / YinHanke <[email protected]>
[Relax][Frontend][TFLite] Add LSTM and SVDF converter (#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.

>From #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

Report URL: https://github.com/apache/tvm/actions/runs/26655271825

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