Apply hijacks in ddpm_edit for upcast sampling
To avoid import errors, ddpm_edit hijacks are done after an instruct pix2pix model is loaded.
This commit is contained in:
parent
4738486d8f
commit
2016733814
@ -104,6 +104,9 @@ class StableDiffusionModelHijack:
|
||||
m.cond_stage_model.model.token_embedding = EmbeddingsWithFixes(m.cond_stage_model.model.token_embedding, self)
|
||||
m.cond_stage_model = sd_hijack_open_clip.FrozenOpenCLIPEmbedderWithCustomWords(m.cond_stage_model, self)
|
||||
|
||||
if m.cond_stage_key == "edit":
|
||||
sd_hijack_unet.hijack_ddpm_edit()
|
||||
|
||||
self.optimization_method = apply_optimizations()
|
||||
|
||||
self.clip = m.cond_stage_model
|
||||
|
@ -44,6 +44,7 @@ def apply_model(orig_func, self, x_noisy, t, cond, **kwargs):
|
||||
with devices.autocast():
|
||||
return orig_func(self, x_noisy.to(devices.dtype_unet), t.to(devices.dtype_unet), cond, **kwargs).float()
|
||||
|
||||
|
||||
class GELUHijack(torch.nn.GELU, torch.nn.Module):
|
||||
def __init__(self, *args, **kwargs):
|
||||
torch.nn.GELU.__init__(self, *args, **kwargs)
|
||||
@ -53,6 +54,16 @@ class GELUHijack(torch.nn.GELU, torch.nn.Module):
|
||||
else:
|
||||
return torch.nn.GELU.forward(self, x)
|
||||
|
||||
|
||||
ddpm_edit_hijack = None
|
||||
def hijack_ddpm_edit():
|
||||
global ddpm_edit_hijack
|
||||
if not ddpm_edit_hijack:
|
||||
CondFunc('modules.models.diffusion.ddpm_edit.LatentDiffusion.decode_first_stage', first_stage_sub, first_stage_cond)
|
||||
CondFunc('modules.models.diffusion.ddpm_edit.LatentDiffusion.encode_first_stage', first_stage_sub, first_stage_cond)
|
||||
ddpm_edit_hijack = CondFunc('modules.models.diffusion.ddpm_edit.LatentDiffusion.apply_model', apply_model, unet_needs_upcast)
|
||||
|
||||
|
||||
unet_needs_upcast = lambda *args, **kwargs: devices.unet_needs_upcast
|
||||
CondFunc('ldm.models.diffusion.ddpm.LatentDiffusion.apply_model', apply_model, unet_needs_upcast)
|
||||
CondFunc('ldm.modules.diffusionmodules.openaimodel.timestep_embedding', lambda orig_func, timesteps, *args, **kwargs: orig_func(timesteps, *args, **kwargs).to(torch.float32 if timesteps.dtype == torch.int64 else devices.dtype_unet), unet_needs_upcast)
|
||||
|
Loading…
Reference in New Issue
Block a user