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Fix SVD lowvram mode.

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This commit is contained in:
comfyanonymous 2023-12-24 07:06:59 -05:00
parent a252963f95
commit d0165d819a
2 changed files with 7 additions and 7 deletions
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6
comfy/ldm/modules/diffusionmodules/util.py
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@ -51,9 +51,9 @@ class AlphaBlender(nn.Module):
if self.merge_strategy == "fixed":
# make shape compatible
# alpha = repeat(self.mix_factor, '1 -> b () t () ()', t=t, b=bs)
alpha = self.mix_factor
alpha = self.mix_factor.to(image_only_indicator.device)
elif self.merge_strategy == "learned":
alpha = torch.sigmoid(self.mix_factor)
alpha = torch.sigmoid(self.mix_factor.to(image_only_indicator.device))
# make shape compatible
# alpha = repeat(alpha, '1 -> s () ()', s = t * bs)
elif self.merge_strategy == "learned_with_images":
@ -61,7 +61,7 @@ class AlphaBlender(nn.Module):
alpha = torch.where(
image_only_indicator.bool(),
torch.ones(1, 1, device=image_only_indicator.device),
rearrange(torch.sigmoid(self.mix_factor), "... -> ... 1"),
rearrange(torch.sigmoid(self.mix_factor.to(image_only_indicator.device)), "... -> ... 1"),
)
alpha = rearrange(alpha, self.rearrange_pattern)
# make shape compatible

8
comfy/ldm/modules/temporal_ae.py
View File

@ -82,14 +82,14 @@ class VideoResBlock(ResnetBlock):
x = self.time_stack(x, temb)
alpha = self.get_alpha(bs=b // timesteps)
alpha = self.get_alpha(bs=b // timesteps).to(x.device)
x = alpha * x + (1.0 - alpha) * x_mix
x = rearrange(x, "b c t h w -> (b t) c h w")
return x
class AE3DConv(torch.nn.Conv2d):
class AE3DConv(ops.Conv2d):
def __init__(self, in_channels, out_channels, video_kernel_size=3, *args, **kwargs):
super().__init__(in_channels, out_channels, *args, **kwargs)
if isinstance(video_kernel_size, Iterable):
@ -97,7 +97,7 @@ class AE3DConv(torch.nn.Conv2d):
else:
padding = int(video_kernel_size // 2)
self.time_mix_conv = torch.nn.Conv3d(
self.time_mix_conv = ops.Conv3d(
in_channels=out_channels,
out_channels=out_channels,
kernel_size=video_kernel_size,
@ -167,7 +167,7 @@ class AttnVideoBlock(AttnBlock):
emb = emb[:, None, :]
x_mix = x_mix + emb
alpha = self.get_alpha()
alpha = self.get_alpha().to(x.device)
x_mix = self.time_mix_block(x_mix, timesteps=timesteps)
x = alpha * x + (1.0 - alpha) * x_mix # alpha merge