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axis_weights() in diffusion_vae_tiling built its float64 weights directly on the target device, so a tiled encode on Apple Silicon raised before the first step (MPS has no float64). Build them on CPU and move only the fp32 result, matching video_ltx2_vae_tiles.axis_weights. Fixes unslothai#12935 Signed-off-by: GokayAI <[email protected]>
…ks float64 The tile blend weights were moved to an unconditional CPU build to keep float64 off MPS. Gate that on the device's float64 capability instead, the way the RoPE demotion already is: a device with float64 builds them in place exactly as before, and only MPS builds on CPU and receives the fp32 result. The regression test now watches every tensor the build produces rather than the constructor arguments, so a float64 tensor reaching the device through a later move or cast is caught too.
…E tiles The LTX-2 axis_weights was a copy of the image one that differed only in its default margin and ramp, and the image copy missed the MPS float64 handling the LTX-2 copy had. Delegate to the image implementation with the LTX-2 defaults so the float64 capability is decided in one place.
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Staging run for unslothai#12937 (same head) for CI and review. The base is the upstream main the head was merged with, so the diff is the PR's own changes.