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Run each partitioner’s edge transforms after caller-supplied passes so backends can use the standard lowering entry point. QNN contributes its existing transforms through the new hook.
Reserve names for constant tensors already present in the exported program before lifting new constants, so methods with folded tables retain distinct constants.
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/24567
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Avoid constant-name collisions when lifting tensors
A program with a buffer already named
_lifted_tensor_constant1could lift a new scalar into the same name. The resulting signature has duplicate buffer names and can lose a folded constant. Reserve existing names before assigning names to newly lifted tensors.Review order: the name allocation in
lift_constant_tensor_pass, thentest_lift_constant_tensor_pass_avoids_buffer_name_collision. This is PR 2 of the Stack 2 series. Its local parent isstack2/pr01-partitioner-transforms; the GitHub base ismain, so it includes PR 1's commits followed by this constant-name fix.Test Plan
On this PR's branch:
Against unmodified main, the collision regression fails with
AssertionError: 2 != 1(duplicate buffer names). After the fix, buffer names are unique and the original[2,2,2,2]buffer is unchanged.No external memory-planning changes are carried in this PR. The reachable base is
5f72739cf26ed53df21a746fb5b022fb8e4266d9; GitHub main fetch returned proxy 403.Stack (review in order)
Each PR includes the commits of the ones above it; review only its own top commits.