[AMD] diffusion refactor: move ROCM VAE optimization to Platform abstraction (#20496)
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@@ -380,6 +380,11 @@ class Platform:
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"""Whether to enable DIT layerwise offload by default on the current platform."""
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return True
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@classmethod
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def optimize_vae(cls, vae: torch.nn.Module) -> torch.nn.Module:
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"""Apply platform-specific optimizations to VAE after loading."""
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return vae
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def get_attn_backend(self, *args, **kwargs) -> AttentionImpl:
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attention_cls_str = self.get_attn_backend_cls_str(*args, **kwargs)
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return resolve_obj_by_qualname(attention_cls_str)
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@@ -182,6 +182,48 @@ class RocmPlatform(Platform):
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def get_device_communicator_cls(cls) -> str:
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return "sglang.multimodal_gen.runtime.distributed.device_communicators.cuda_communicator.CudaCommunicator" # works for ROCm too
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@classmethod
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def optimize_vae(cls, vae: torch.nn.Module) -> torch.nn.Module:
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"""Replace nn.GroupNorm with AITer GroupNorm for improved ROCm VAE performance."""
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if not envs.SGLANG_USE_ROCM_VAE:
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return vae
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try:
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from aiter.ops.groupnorm import GroupNorm as AiterGroupNorm
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count = cls._replace_groupnorm(vae, AiterGroupNorm)
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if count > 0:
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logger.info(
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"Replaced %d nn.GroupNorm modules with AITer GroupNorm in VAE",
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count,
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)
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except Exception:
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logger.warning(
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"Failed to apply AITer GroupNorm to VAE.",
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exc_info=True,
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)
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return vae
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@staticmethod
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def _replace_groupnorm(module: torch.nn.Module, aiter_gn_cls: type) -> int:
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count = 0
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for name, child in module.named_children():
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if isinstance(child, torch.nn.GroupNorm) and child.affine:
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replacement = aiter_gn_cls(
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num_groups=child.num_groups,
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num_channels=child.num_channels,
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eps=child.eps,
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affine=True,
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device=child.weight.device,
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dtype=child.weight.dtype,
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)
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replacement.weight = child.weight
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replacement.bias = child.bias
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setattr(module, name, replacement)
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count += 1
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else:
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count += RocmPlatform._replace_groupnorm(child, aiter_gn_cls)
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return count
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@classmethod
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def enable_dit_layerwise_offload_for_wan_by_default(cls) -> bool:
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"""ROCm performs better without DIT layerwise offload on Wan."""
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