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Skip ReplacePowWithMulPass when pow promotes the input dtype (#24177) - #24177
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/24177
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…#24177) Summary: `pow.Tensor_Scalar(int32, 2.0)` returns float32, but the `mul.Tensor(x, x)` chain that `ReplacePowWithMulPass` emits stays int32. The pass copied the float32 `meta` onto the int32 `mul` nodes, so the lowered program's output dtype no longer matched the eager reference. The pass now gives up when the input dtype differs from the `pow` output dtype. Found by the Jarvis nightly operator tests: `test_pow_Tensor_Scalar_out` cases 14 and 23 (int32 input, exponent 2.0) fail on nxp, DLA, Artemis v3/v4 and CPU with `The label tensor ... dtype shall be torch.int32, but now is torch.float32`. Differential Revision: D127746754
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…#24177) Summary: `pow.Tensor_Scalar(int32, 2.0)` returns float32, but the `mul.Tensor(x, x)` chain that `ReplacePowWithMulPass` emits stays int32. The pass copied the float32 `meta` onto the int32 `mul` nodes, so the lowered program's output dtype no longer matched the eager reference. The pass now gives up when the input dtype differs from the `pow` output dtype. Found by the Jarvis nightly operator tests: `test_pow_Tensor_Scalar_out` cases 14 and 23 (int32 input, exponent 2.0) fail on nxp, DLA, Artemis v3/v4 and CPU with `The label tensor ... dtype shall be torch.int32, but now is torch.float32`. Differential Revision: D127746754
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…#24177) Summary: `pow.Tensor_Scalar(int32, 2.0)` returns float32, but the `mul.Tensor(x, x)` chain that `ReplacePowWithMulPass` emits stays int32. The pass copied the float32 `meta` onto the int32 `mul` nodes, so the lowered program's output dtype no longer matched the eager reference. The pass now gives up when the input dtype differs from the `pow` output dtype. Found by the Jarvis nightly operator tests: `test_pow_Tensor_Scalar_out` cases 14 and 23 (int32 input, exponent 2.0) fail on nxp, DLA, Artemis v3/v4 and CPU with `The label tensor ... dtype shall be torch.int32, but now is torch.float32`. Differential Revision: D127746754
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…#24177) Summary: `pow.Tensor_Scalar(int32, 2.0)` returns float32, but the `mul.Tensor(x, x)` chain that `ReplacePowWithMulPass` emits stays int32. The pass copied the float32 `meta` onto the int32 `mul` nodes, so the lowered program's output dtype no longer matched the eager reference. The pass now gives up when the input dtype differs from the `pow` output dtype. Authored with Claude Code. Reviewed By: DrJessop Differential Revision: D127746754
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…#24177) Summary: `pow.Tensor_Scalar(int32, 2.0)` returns float32, but the `mul.Tensor(x, x)` chain that `ReplacePowWithMulPass` emits stays int32. The pass copied the float32 `meta` onto the int32 `mul` nodes, so the lowered program's output dtype no longer matched the eager reference. The pass now gives up when the input dtype differs from the `pow` output dtype. Authored with Claude Code. Reviewed By: DrJessop Differential Revision: D127746754
…torch#24176) Summary: `add.Scalar(Tensor self, Scalar other, Scalar alpha=1)` takes `alpha` positionally, but `add.Tensor(Tensor self, Tensor other, *, Scalar alpha=1)` takes it as keyword-only, and the same holds for `sub`. When `alpha` was the third positional argument, `get_replacement` passed it through `*args[2:]`, and building the `.Tensor` node raised `RuntimeError: aten::add() takes 2 positional argument(s) but 3 was/were given`. The 3-argument path now binds the call by name with `torch.fx.operator_schemas.normalize_function` (the part of `get_arg` that doesn't need a `Node`; `call_operator` gets no node), passes `self` (`input` after normalization) and `other` positionally, and `alpha` as a kwarg. `get_replacement` always gets 2 args and no longer forwards extra ones. The Arm `ReplaceScalarWithTensorByProfilePass` subclass routes through the same base `call_operator`, so it gets the fix too for edge `add/sub.Scalar`. `torch.ops.aten.add/sub.Scalar` with a positional `alpha` still pass through unreplaced, as before. The changed path previously always raised, so no graph that worked before is affected. Authored with Claude Code. Reviewed By: DrJessop Differential Revision: D127746753
…#24177) Summary: `pow.Tensor_Scalar(int32, 2.0)` returns float32, but the `mul.Tensor(x, x)` chain that `ReplacePowWithMulPass` emits stays int32. The pass copied the float32 `meta` onto the int32 `mul` nodes, so the lowered program's output dtype no longer matched the eager reference. The pass now gives up when the input dtype differs from the `pow` output dtype. Authored with Claude Code. Reviewed By: DrJessop Differential Revision: D127746754
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Summary:
pow.Tensor_Scalar(int32, 2.0)returns float32, but themul.Tensor(x, x)chain thatReplacePowWithMulPassemits stays int32. The pass copied the float32metaonto the int32mulnodes, so the lowered program's output dtype no longer matched the eager reference. The pass now gives up when the input dtype differs from thepowoutput dtype.Authored with Claude Code.
Reviewed By: DrJessop
Differential Revision: D127746754