fix(schedulers): guard Helios schedulers against float64 on MPS - #14427
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erensh27 wants to merge 2 commits into
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fix(schedulers): guard Helios schedulers against float64 on MPS#14427erensh27 wants to merge 2 commits into
erensh27 wants to merge 2 commits into
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The labeler LLM is told to pick from a fixed set of labels, but several of those labels do not exist in the repo (e.g. 'compile', 'attention-backends', 'torchao', 'new-pipeline/model'). Applying any of them with 'gh issue edit --add-label' fails the whole job, so most bug reports end up with no labels at all (issue huggingface#14377: 'needs-env-info'). Filter the model output against the repo's actual label list before applying, and emit a warning for any label that does not exist instead of failing the run.
Both Helios schedulers built float64 tensors without the MPS guard used elsewhere in the codebase, raising TypeError on Apple Silicon the moment the pipeline set timesteps (or reached convert_flow_pred_to_x0). - set_timesteps (both schedulers): when the target device is MPS, cast the numpy schedule to float32 before from_numpy, and force the concatenated sigma tensor to float32 (mps does not support float64). - convert_flow_pred_to_x0 (HeliosDMDScheduler): use float64 for calculation on non-MPS devices, fall back to float32 on MPS. Mirrors the existing device guard in scheduling_consistency_models.py and scheduling_cosine_dpmsolver_multistep.py.
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Fixes #14367.
Both Helios schedulers build
float64tensors without the MPS guard used elsewhere in the codebase, so on Apple Silicon the pipeline fails withTypeErrorat the first scheduler call.Changes in
src/diffusers/schedulers/scheduling_helios.pyandscheduling_helios_dmd.py:set_timesteps(both): when the target device is MPS, cast the NumPy schedule tofloat32beforefrom_numpyand force the concatenatedsigmastensor tofloat32— mps does not support float64. Non-MPS behavior unchanged.convert_flow_pred_to_x0(HeliosDMDScheduler): keepfloat64for the high-precision calculation on non-MPS devices; usefloat32on MPS instead ofx.double().to(device).Mirrors the existing guard in
scheduling_consistency_models.py/scheduling_cosine_dpmsolver_multistep.py.