Use the promoted output dtype when lowering clamp - #83
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PyTorch promotes integer inputs when clamp bounds are floating point. The lowering instead built the bounds in the input type, truncating their values and producing a result that disagreed with the exported node's declared type. Use the node output type as the working type, cast the input and tensor bounds when needed, and build scalar bounds in that type. Extend the end-to-end clamp coverage across scalar and tensor float bounds while retaining integer behavior.
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PyTorch promotes integer inputs when clamp bounds are floating point. The lowering instead built bounds in the input dtype, truncating their values and producing a result that disagreed with the exported node's declared type.
This uses the node output type as the working type, casting the input and tensor bounds when needed. The tests cover scalar and tensor float bounds while retaining the existing integer behavior
Tested with
pytest -q tests/ops/test_ops.py::test_clamp