Public/automatic
1
0
Fork 0
mirror of https://github.com/vladmandic/automatic synced 2026-09-19 17:24:32 +02:00
Code Issues Packages Projects Releases Wiki Activity

Use dtype_unet as specified, propagete types in gaussian

Browse Source
This commit is contained in:
Kubuxu
2023-07-11 22:04:43 +01:00
parent e4a682de2b
commit 5d0c01b9e3
1 changed files with 4 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/sd_hijack.py
+4
View File
@@ -2,6 +2,7 @@ from types import MethodType
import torch
from torch.nn.functional import silu
import ldm.modules.attention
import ldm.modules.distributions.distributions
import ldm.modules.diffusionmodules.model
import ldm.modules.diffusionmodules.openaimodel
import ldm.models.diffusion.ddim
@@ -305,3 +306,6 @@ def register_buffer(self, name, attr):
ldm.models.diffusion.ddim.DDIMSampler.register_buffer = register_buffer
ldm.models.diffusion.plms.PLMSSampler.register_buffer = register_buffer
# Ensure samping from Guassian for DDPM follows types
ldm.modules.distributions.distributions.DiagonalGaussianDistribution.sample = lambda self: self.mean.to(self.parameters.dtype) + self.std.to(self.parameters.dtype) * torch.randn(self.mean.shape, dtype=self.parameters.dtype).to(device=self.parameters.device)