Nanmur opened a new pull request, #20330: URL: https://github.com/apache/tvm/pull/20330
The GPU GEMV schedule assumes that the outer spatial loop produced by its thread-tile split has extent one. It checks this by reading `.extent.value`, which crashes when the extent is a `FloorDiv`; for the convolution shapes in #20047, the extent is also genuinely larger than one, so forcing this GEMV schedule is not valid. This change uses `arith.Analyzer.can_prove_equal` at the three unit-extent guards. When the selected GEMV configuration cannot prove that the outer extent is one, the rule returns `None`, allowing `ApplyDefaultSchedule` to continue to the GPU Fallback rule. The regression test uses the lowered TIR for the reported `1x1x3x10` input and `1x1x1x2` kernel. It verifies that GEMV declines the unsupported configuration and Fallback produces a scheduled PrimFunc instead of raising `AttributeError` or `AssertionError`. Fixes #20047 Tests: - `python -m pytest tests/python/s_tir/dlight/test_gpu_gemv.py -q` (`15 passed`) - Relax CUDA default-pipeline probe for the reported conv2d shape - `python -m ruff check python/tvm/s_tir/dlight/gpu/gemv.py tests/python/s_tir/dlight/test_gpu_gemv.py` - `python -m ruff format --check python/tvm/s_tir/dlight/gpu/gemv.py tests/python/s_tir/dlight/test_gpu_gemv.py` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
