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Switch genmo model to native RMSNorm.

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This commit is contained in:
comfyanonymous 2025-05-03 18:55:49 -04:00
parent 7689917113
commit 923834828a
2 changed files with 4 additions and 16 deletions
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9
comfy/ldm/genmo/joint_model/asymm_models_joint.py
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@ -13,7 +13,6 @@ from comfy.ldm.modules.attention import optimized_attention
from .layers import ( from .layers import (
FeedForward, FeedForward,
PatchEmbed, PatchEmbed,
RMSNorm,
TimestepEmbedder, TimestepEmbedder,
) )
@ -90,10 +89,10 @@ class AsymmetricAttention(nn.Module):
# Query and key normalization for stability. # Query and key normalization for stability.
assert qk_norm assert qk_norm
self.q_norm_x = RMSNorm(self.head_dim, device=device, dtype=dtype) self.q_norm_x = operations.RMSNorm(self.head_dim, eps=1e-5, device=device, dtype=dtype)
self.k_norm_x = RMSNorm(self.head_dim, device=device, dtype=dtype) self.k_norm_x = operations.RMSNorm(self.head_dim, eps=1e-5, device=device, dtype=dtype)
self.q_norm_y = RMSNorm(self.head_dim, device=device, dtype=dtype) self.q_norm_y = operations.RMSNorm(self.head_dim, eps=1e-5, device=device, dtype=dtype)
self.k_norm_y = RMSNorm(self.head_dim, device=device, dtype=dtype) self.k_norm_y = operations.RMSNorm(self.head_dim, eps=1e-5, device=device, dtype=dtype)
# Output layers. y features go back down from dim_x -> dim_y. # Output layers. y features go back down from dim_x -> dim_y.
self.proj_x = operations.Linear(dim_x, dim_x, bias=out_bias, device=device, dtype=dtype) self.proj_x = operations.Linear(dim_x, dim_x, bias=out_bias, device=device, dtype=dtype)

11
comfy/ldm/genmo/joint_model/layers.py
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@ -151,14 +151,3 @@ class PatchEmbed(nn.Module):
x = self.norm(x) x = self.norm(x)
return x return x
class RMSNorm(torch.nn.Module):
def __init__(self, hidden_size, eps=1e-5, device=None, dtype=None):
super().__init__()
self.eps = eps
self.weight = torch.nn.Parameter(torch.empty(hidden_size, device=device, dtype=dtype))
self.register_parameter("bias", None)
def forward(self, x):
return comfy.ldm.common_dit.rms_norm(x, self.weight, self.eps)