fix: add MPS (Apple Silicon) support for PyTorch backend#415
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- Auto-detect MPS device in TimesFM_2p5_200M_torch_module.__init__ - Fix tensor dtype conversion order: cast to float32/bool before moving to device, avoiding MPS float64 incompatibility - Explicitly set dtype=np.float32 on padding arrays to prevent NumPy's implicit float64 promotion from propagating to MPS tensors
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LGTM |
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Summary
TimesFM_2p5_200M_torch_module.__init__: adds anelif torch.backends.mps.is_available()branch so Apple Silicon GPUs are used automatically, without requiring any manual workaround from callers.timesfm_2p5_torch.py: convert tofloat32/boolbefore moving to device (was.to(device).to(float32)). MPS does not supportfloat64, so the previous order raisedCannot convert a MPS Tensor to float64when NumPy's defaultfloat64arrays were moved to MPS first.timesfm_2p5_base.py: explicitly passdtype=np.float32when creating padding arrays, preventing NumPy's implicitfloat64promotion from propagating into the model.Test plan
torch.backends.mps.is_available() == True) and confirm nofloat64errors🤖 Generated with Claude Code