The GitHub Actions job "Teams" on tvm.git/main has succeeded. Run started by GitHub user tlopex (triggered by tlopex).
Head commit for run: 9d6e1cf07fc3fe3a793a034ab41bd1aa661a8f36 / Felix Hirwa Nshuti <[email protected]> [Relax][Frontend][TFLite] Add support for FFT/complex operators: REAL, IMAG, COMPLEX_ABS (#19763) Part of https://github.com/apache/tvm/issues/19519 This PR adds support for the FFT and complex operator family in the Relax TFLite frontend. **Key implementations:** - Registered `REAL`, `IMAG`, `COMPLEX_ABS`to the TFLite op map. - Implemented `convert_real` and `convert_imag` which extract the real and imaginary parts of a complex tensor via `strided_slice` + `squeeze` along the last axis. - Implemented `convert_complex_abs` which computes `sqrt(re^2 + im^2)` using elementwise Relax ops. - All three ops adopt a unified representation convention: TFLite `complex64` tensors (which have no native Relax dtype equivalent) are represented as `float32[..., 2]`, where the last axis holds `(real, imaginary)` interleaved.. **Out of scope:** - `RFFT2D` is not registered in this PR. An O(N²) matmul decomposition is feasible using existing Relax ops and will be contributed separately with benchmarks showing the performance gap versus a native FFT op. A native `relax.op.signal.rfft2d` is tracked in https://github.com/apache/tvm/issues/19764 **Testing:** - Added structural equality tests for `REAL`, `IMAG`, and `COMPLEX_ABS` in `test_frontend_tflite.py` following the `verify(TestClass, Expected)` pattern. ```bash python3 -m pytest tests/python/relax/test_frontend_tflite.py -k "test_real or test_imag or test_complex_abs" ``` Report URL: https://github.com/apache/tvm/actions/runs/27645628727 With regards, GitHub Actions via GitBox --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
