Skip to content

[pull] master from comfyanonymous:master #36

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
May 4, 2025
+7 −20
Merged

[pull] master from comfyanonymous:master #36

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 4 additions & 5 deletions comfy/ldm/genmo/joint_model/asymm_models_joint.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,6 @@
from .layers import (
FeedForward,
PatchEmbed,
RMSNorm,
TimestepEmbedder,
)

Expand Down Expand Up @@ -90,10 +89,10 @@ def __init__(

# Query and key normalization for stability.
assert qk_norm
self.q_norm_x = RMSNorm(self.head_dim, device=device, dtype=dtype)
self.k_norm_x = RMSNorm(self.head_dim, device=device, dtype=dtype)
self.q_norm_y = RMSNorm(self.head_dim, device=device, dtype=dtype)
self.k_norm_y = 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 = operations.RMSNorm(self.head_dim, eps=1e-5, device=device, dtype=dtype)
self.q_norm_y = operations.RMSNorm(self.head_dim, eps=1e-5, 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.
self.proj_x = operations.Linear(dim_x, dim_x, bias=out_bias, device=device, dtype=dtype)
Expand Down
11 changes: 0 additions & 11 deletions comfy/ldm/genmo/joint_model/layers.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -151,14 +151,3 @@ def forward(self, x):

x = self.norm(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)
7 changes: 3 additions & 4 deletions comfy/ldm/wan/model.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,6 @@
from comfy.ldm.modules.attention import optimized_attention
from comfy.ldm.flux.layers import EmbedND
from comfy.ldm.flux.math import apply_rope
from comfy.ldm.modules.diffusionmodules.mmdit import RMSNorm
import comfy.ldm.common_dit
import comfy.model_management

Expand Down Expand Up @@ -49,8 +48,8 @@ def __init__(self,
self.k = operation_settings.get("operations").Linear(dim, dim, device=operation_settings.get("device"), dtype=operation_settings.get("dtype"))
self.v = operation_settings.get("operations").Linear(dim, dim, device=operation_settings.get("device"), dtype=operation_settings.get("dtype"))
self.o = operation_settings.get("operations").Linear(dim, dim, device=operation_settings.get("device"), dtype=operation_settings.get("dtype"))
self.norm_q = RMSNorm(dim, eps=eps, elementwise_affine=True, device=operation_settings.get("device"), dtype=operation_settings.get("dtype")) if qk_norm else nn.Identity()
self.norm_k = RMSNorm(dim, eps=eps, elementwise_affine=True, device=operation_settings.get("device"), dtype=operation_settings.get("dtype")) if qk_norm else nn.Identity()
self.norm_q = operation_settings.get("operations").RMSNorm(dim, eps=eps, elementwise_affine=True, device=operation_settings.get("device"), dtype=operation_settings.get("dtype")) if qk_norm else nn.Identity()
self.norm_k = operation_settings.get("operations").RMSNorm(dim, eps=eps, elementwise_affine=True, device=operation_settings.get("device"), dtype=operation_settings.get("dtype")) if qk_norm else nn.Identity()

def forward(self, x, freqs):
r"""
Expand Down Expand Up @@ -114,7 +113,7 @@ def __init__(self,
self.k_img = operation_settings.get("operations").Linear(dim, dim, device=operation_settings.get("device"), dtype=operation_settings.get("dtype"))
self.v_img = operation_settings.get("operations").Linear(dim, dim, device=operation_settings.get("device"), dtype=operation_settings.get("dtype"))
# self.alpha = nn.Parameter(torch.zeros((1, )))
self.norm_k_img = RMSNorm(dim, eps=eps, elementwise_affine=True, device=operation_settings.get("device"), dtype=operation_settings.get("dtype")) if qk_norm else nn.Identity()
self.norm_k_img = operation_settings.get("operations").RMSNorm(dim, eps=eps, elementwise_affine=True, device=operation_settings.get("device"), dtype=operation_settings.get("dtype")) if qk_norm else nn.Identity()

def forward(self, x, context, context_img_len):
r"""
Expand Down