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1.0.19 (#33)

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Unlock to allow changing model.
This commit is contained in:
lllyasviel
2023-08-12 17:43:39 -07:00
committed by GitHub
parent 1ff382c8ef
commit 158afe088d
7 changed files with 217 additions and 41 deletions
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modules/core.py
+13 -3
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@@ -29,6 +29,14 @@ class StableDiffusionModel:
self.clip = clip
self.clip_vision = clip_vision
def to_meta(self):
if self.unet is not None:
self.unet.model.to('meta')
if self.clip is not None:
self.clip.cond_stage_model.to('meta')
if self.vae is not None:
self.vae.first_stage_model.to('meta')
@torch.no_grad()
def load_model(ckpt_filename):
@@ -42,8 +50,8 @@ def load_lora(model, lora_filename, strength_model=1.0, strength_clip=1.0):
return model
lora = comfy.utils.load_torch_file(lora_filename, safe_load=True)
model.unet, model.clip = comfy.sd.load_lora_for_models(model.unet, model.clip, lora, strength_model, strength_clip)
return model
unet, clip = comfy.sd.load_lora_for_models(model.unet, model.clip, lora, strength_model, strength_clip)
return StableDiffusionModel(unet=unet, clip=clip, vae=model.vae, clip_vision=model.clip_vision)
@torch.no_grad()
@@ -92,7 +100,7 @@ def get_previewer(device, latent_format):
@torch.no_grad()
def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sampler_name='dpmpp_2m_sde_gpu',
scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
force_full_denoise=False):
force_full_denoise=False, callback_function=None):
# SCHEDULERS = ["normal", "karras", "exponential", "simple", "ddim_uniform"]
# SAMPLERS = ["euler", "euler_ancestral", "heun", "dpm_2", "dpm_2_ancestral",
# "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu",
@@ -118,6 +126,8 @@ def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sa
pbar = comfy.utils.ProgressBar(steps)
def callback(step, x0, x, total_steps):
if callback_function is not None:
callback_function(step, x0, x, total_steps)
if previewer and step % 3 == 0:
previewer.preview(x0, step, total_steps)
pbar.update_absolute(step + 1, total_steps, None)