Aharrypotter opened a new pull request, #19824:
URL: https://github.com/apache/tvm/pull/19824
## Summary
This PR adds explicit Relax TFLite frontend handling for the TFLite builtin
operator markers from #19519 item H:
- `DELEGATE`
- `PLACEHOLDER_FOR_GREATER_OP_CODES`
These builtins are TFLite marker / pseudo operators rather than ordinary
tensor
operators. The frontend now recognizes them and raises a targeted
`OpNotImplemented` diagnostic instead of falling through to a generic
unsupported-operator path.
## Design
`DELEGATE` marks delegated TFLite subgraphs, and
`PLACEHOLDER_FOR_GREATER_OP_CODES` is a schema compatibility placeholder.
They
do not have Relax tensor semantics to lower. This PR therefore keeps the
importer conservative:
- both builtin names are added to the TFLite `convert_map`
- both route to a shared `convert_operator_marker` guard
- the guard reports that the marker is not a Relax tensor operator
This makes the unsupported status intentional and discoverable without
mapping
the markers to synthetic Relax ops.
## Tests
The tests manually build minimal TFLite flatbuffers containing each marker
builtin and assert that import raises the targeted `OpNotImplemented`.
Local validation:
```bash
python -m ruff format \
python/tvm/relax/frontend/tflite/tflite_frontend.py \
tests/python/relax/test_frontend_tflite.py
python -m ruff check \
python/tvm/relax/frontend/tflite/tflite_frontend.py \
tests/python/relax/test_frontend_tflite.py
python -m pytest \
tests/python/relax/test_frontend_tflite.py \
-k operator_marker_unsupported -q
```
Result:
```text
ruff format: 2 files left unchanged
ruff check: All checks passed
operator_marker_unsupported tests: 2 passed, 535 deselected
```
## References
- Issue #19519 item H: TFLite operator markers
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