Add use_real parameter to Z-Image for platform compatibility#13824
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st7109 wants to merge 1 commit into
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Add use_real parameter to Z-Image for platform compatibility#13824st7109 wants to merge 1 commit into
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Add optional real-number RoPE implementation to Z-Image transformer and controlnet. When use_real=True, the rotary position embeddings use (cos, sin) tuples instead of complex numbers, enabling the model to run on platforms that don't support complex arithmetic (e.g., MLU). Changes: - Add apply_rotary_emb() with use_real parameter supporting both complex and real computation - Propagate use_real through ZSingleStreamAttnProcessor, ZImageTransformerBlock, RopeEmbedder, ZImageTransformer2DModel, and controlnet variants - Update _prepare_sequence and _build_unified_sequence to handle (cos, sin) tuples - Default use_real=False maintains backward compatibility - Replace hardcoded cuda autocast with device-aware torch.autocast for Z-Image Tested on MLU: successfully generates 1024x1024 images with numerical equivalence (max diff < 1e-6) compared to complex mode.
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@sayakpaul hello, Sir, Please help review this commit, any suggests, let me know. thanks. |
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Fixes # (issue)
Add optional real-number RoPE implementation to Z-Image transformer and controlnet. When use_real=True,
the rotary position embeddings use (cos, sin) tuples instead of complex numbers, enabling the model to run on platforms that don't support complex arithmetic (e.g., Cambricon MLU, etc).
Changes:
Tested on Cambricon MLU and nvidia A100: successfully generates 1024x1024 images with numerical equivalence (max diff < 1e-6) compared to complex mode.
The test case is from https://huggingface.co/Tongyi-MAI/Z-Image-Turbo, if tests with Cambricon MLU platform, should set use_real=True, then generate the below:
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@sayakpaul
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