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EXECUTORCH STRIPS MPS, PYTORCH DROPS UNUSED DEPS
By RepoJournal · Filed · About PyTorch
ExecuTorch finally deletes the deprecated MPS backend and PyTorch cuts dead weight in its build, while the rest of the stack quietly hardens.
ExecuTorch removed the MPS backend as promised in its deprecation notice [1], shipping in 1.5.0 after being overdue. Meanwhile, the project fixed a subtle graph copy bug that wasted 68 MB of memory on a four-method model [2], and fixed a Cortex-M kernel miscompilation that produced incorrect results for quantized add with an alpha multiplier [3]. On PyTorch core, the build no longer links the unused cuRAND host library [4] and generate_code.py lost a flag that hadn't done anything since 2021 [5]. The gradcheck fix addresses a long-standing issue where non-differentiable outputs could corrupt projections [6]. Torchtitan's MFU calculation was overcounting FLOPS for sliding window attention models, sometimes exceeding 100% [7]. TensorRT's Windows CI was failing 170 of 300 jobs due to a malformed artifact name [8], and ExecuTorch's packaged runner now registers the device copy kernels it was missing [9].
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Action items
- → Update ExecuTorch to remove MPS backend dependencies pytorch/executorch [plan]
- → Review quantized add alpha handling on Cortex-M pytorch/executorch [monitor]
- → Verify gradcheck behavior with non-differentiable outputs pytorch/pytorch [plan]
References
- [1] Remove the deprecated MPS backend (#22181) pytorch/executorch
- [2] Fix issues in the export recipe framework (#22158) pytorch/executorch
- [3] Cortex-M: lower subtraction, and stop miscompiling add with alpha (#22153) pytorch/executorch
- [4] Stop linking the cuRAND host library (#194850) pytorch/pytorch
- [5] Drop the dead force_schema_registration flag from generate_code.py (#194843) pytorch/pytorch
- [6] Fix fast gradcheck when non-differentiable outputs precede differentiable ones (#194222) pytorch/pytorch
- [7] Fix mfu calculation for muse glimmer and gpt_oss ↗ pytorch/torchtitan
- [8] fix(ci): build the Windows download artifact name in the right order ↗ pytorch/TensorRT
- [9] fix(executorch): register device copy kernels in the packaged runner ↗ pytorch/TensorRT