Switch mochi and wan modes to use pytorch RMSNorm. (#7925)
* Switch genmo model to native RMSNorm. * Switch WAN to native RMSNorm.
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@@ -13,7 +13,6 @@ from comfy.ldm.modules.attention import optimized_attention
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from .layers import (
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FeedForward,
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PatchEmbed,
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RMSNorm,
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TimestepEmbedder,
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)
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@@ -90,10 +89,10 @@ class AsymmetricAttention(nn.Module):
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# Query and key normalization for stability.
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assert qk_norm
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self.q_norm_x = RMSNorm(self.head_dim, device=device, dtype=dtype)
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self.k_norm_x = RMSNorm(self.head_dim, device=device, dtype=dtype)
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self.q_norm_y = RMSNorm(self.head_dim, device=device, dtype=dtype)
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self.k_norm_y = RMSNorm(self.head_dim, device=device, dtype=dtype)
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self.q_norm_x = operations.RMSNorm(self.head_dim, eps=1e-5, device=device, dtype=dtype)
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self.k_norm_x = operations.RMSNorm(self.head_dim, eps=1e-5, device=device, dtype=dtype)
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self.q_norm_y = operations.RMSNorm(self.head_dim, eps=1e-5, device=device, dtype=dtype)
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self.k_norm_y = operations.RMSNorm(self.head_dim, eps=1e-5, device=device, dtype=dtype)
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# Output layers. y features go back down from dim_x -> dim_y.
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self.proj_x = operations.Linear(dim_x, dim_x, bias=out_bias, device=device, dtype=dtype)
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