javierdejesusda opened a new pull request, #19773:
URL: https://github.com/apache/tvm/pull/19773
### Root Cause
The ONNX `CumSum` converter in the Relax frontend rejected any node with
`exclusive=1` via a bare
`assert not attr.get("exclusive", False), "Exclusive option not yet
supported."`, so importing a
model that used exclusive cumulative sums failed with `AssertionError:
Exclusive option not yet
supported.`. The underlying op already supports the exclusive form:
`relax.op.cumsum` forwards an
`exclusive` flag to the FFI and `topi/scan.py` implements the exclusive
branch, so the converter
only needed to pass the attribute through.
### Solution
Drop the assert and read the attribute as `exclusive = attr.get("exclusive",
0) != 0` (matching the
existing `attr.get("reverse", 0) != 0` idiom in the same converter), then
pass it to
`relax.op.cumsum(data, axis, exclusive=exclusive)`. The existing reverse
handling
(`flip -> cumsum -> flip`) composes correctly with exclusive, so `reverse=1,
exclusive=1` lowers to
an exclusive scan over the reversed axis.
### Test Plan
Extended `test_cumsum` in `tests/python/relax/test_frontend_onnx.py` to
parametrize `exclusive` over
`[True, False]`, so `check_correctness` now exercises all four `(reverse,
exclusive)` combinations
against ONNX Runtime:
```
python -m pytest tests/python/relax/test_frontend_onnx.py::test_cumsum -v
```
### Issue
Fixes #19692
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