tlopex opened a new pull request, #19732:
URL: https://github.com/apache/tvm/pull/19732
Fixes the failures in
tests/python/nightly/test_nnapi/test_from_exported_to_cuda.py (PyTorch export
-> Relax -> CUDA), which despite the directory name are plain CUDA
exported-program tests.
1. test_index_tensor: aten.index.Tensor with multiple index tensors and no
None entries was lowered through a sequential-take fast path, which computes an
outer product over the index tensors. PyTorch/NumPy advanced indexing
broadcasts the index tensors together and applies them jointly, so e.g. x[[0,
1], [0, 1]] on a (5, 5, 5, 5) tensor produced shape (2, 2, 5, 5) instead of (2,
5, 5). Route the no-None case directly to relax.op.index_tensor
(topi.adv_index), which implements the correct broadcast-and-zip semantics. The
sequential-take path is kept for the sliced (None-containing)
decomposed-interpolate pattern, whose orthogonal index shapes make the outer
product equivalent.
2. test_copy_ (and any in-place op on a buffer/user input):
functionalization in torch.export prepends mutation outputs (BUFFER_MUTATION /
USER_INPUT_MUTATION) to the graph outputs, and the importer returned them as
part of the Relax function's output tuple. Callers indexing outputs
positionally then read the mutated-buffer value instead of the model output.
Filter the outputs through the graph signature's output_specs and keep only
user-facing outputs (USER_OUTPUT / LOSS_OUTPUT). Frontend test expectations
that asserted the extra mutation outputs are updated.
3. test_cross_entropy_module:
- aten.sum over a bool tensor was emitted as relax.op.sum on the bool
input, which keeps dtype bool, so the non-ignored-target count in the
decomposed cross-entropy collapsed to 1.0 and the mean reduction degenerated to
a sum. Match PyTorch type promotion by casting bool and sub-64-bit integer
inputs to int64 (or the explicit dtype argument) before summing.
- The dlight GPU Fallback rule skipped blocks with zero loops entirely,
so rank-0 kernels (the scalar divide) were marked tirx.is_scheduled without any
thread binding and failed VerifyMemory. Bind such blocks through the existing
add-unit-loop path, and only skip zero-loop blocks that already launch threads
internally (e.g. opaque sort kernels), detected via thread_extent attrs /
thread-bound loops in the block body.
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