mirror of https://github.com/llvm/torch-mlir
facbe5d96b
… AtenBernoulli_FloatOp It fixing case like: `%2110 = torch.aten.arange.start_out %int1, %int1517, %int1, %2109 : !torch.int, !torch.int, !torch.int, !torch.tensor -> !torch.tensor`. `aten.arange.start_out` doesn't have value semantics also, means`%2110` is an alias for %2109. So I decompose it to `aten.arange.start` + `torch.contents.overwrite`. The complex decomposition logic is target to handle cases like view and dtype cast which I add in e2e tests. |
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main.py | ||
xfail_sets.py |