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lvmin 2023-08-10 11:13:10 -07:00
parent c4f798221d
commit 1bfa1db707
2 changed files with 46 additions and 5 deletions
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4
modules/core.py
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@ -190,7 +190,7 @@ def ksampler_with_refiner(model, positive, negative, refiner, refiner_positive,
models = load_additional_models(positive, negative, model.model_dtype())
sampler = KSamplerWithRefiner(model=model.model, refiner_model=refiner.model, steps=steps, device=device,
sampler = KSamplerWithRefiner(model=model, refiner_model=refiner, steps=steps, device=device,
sampler=sampler_name, scheduler=scheduler,
denoise=denoise, model_options=model.model_options)
@ -198,7 +198,7 @@ def ksampler_with_refiner(model, positive, negative, refiner, refiner_positive,
refiner_negative=refiner_negative_copy, refiner_switch_step=refiner_switch_step,
cfg=cfg, latent_image=latent_image,
start_step=start_step, last_step=last_step, force_full_denoise=force_full_denoise,
denoise_mask=noise_mask, sigmas=sigmas, callback=callback, disable_pbar=disable_pbar,
denoise_mask=noise_mask, sigmas=sigmas, callback_function=callback, disable_pbar=disable_pbar,
seed=seed)
samples = samples.cpu()

47
modules/samplers_advanced.py
View File

@ -1,5 +1,7 @@
from comfy.samplers import *
import comfy.model_management
class KSamplerWithRefiner:
SCHEDULERS = ["normal", "karras", "exponential", "simple", "ddim_uniform"]
@ -8,8 +10,11 @@ class KSamplerWithRefiner:
"dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "ddim", "uni_pc", "uni_pc_bh2"]
def __init__(self, model, refiner_model, steps, device, sampler=None, scheduler=None, denoise=None, model_options={}):
self.model = model
self.refiner_model = refiner_model
self.model_patcher = model
self.refiner_model_patcher = refiner_model
self.model = model.model
self.refiner_model = refiner_model.model
self.model_denoise = CFGNoisePredictor(self.model)
self.refiner_model_denoise = CFGNoisePredictor(self.refiner_model)
@ -77,7 +82,7 @@ class KSamplerWithRefiner:
def sample(self, noise, positive, negative, refiner_positive, refiner_negative, cfg, latent_image=None,
start_step=None, last_step=None, refiner_switch_step=None,
force_full_denoise=False, denoise_mask=None, sigmas=None, callback=None, disable_pbar=False, seed=None):
force_full_denoise=False, denoise_mask=None, sigmas=None, callback_function=None, disable_pbar=False, seed=None):
if sigmas is None:
sigmas = self.sigmas
sigma_min = self.sigma_min
@ -125,6 +130,42 @@ class KSamplerWithRefiner:
negative = encode_adm(self.model, negative, noise.shape[0], noise.shape[3], noise.shape[2], self.device,
"negative")
refiner_positive = refiner_positive[:]
refiner_negative = refiner_negative[:]
resolve_cond_masks(refiner_positive, noise.shape[2], noise.shape[3], self.device)
resolve_cond_masks(refiner_negative, noise.shape[2], noise.shape[3], self.device)
calculate_start_end_timesteps(self.refiner_model_wrap, refiner_positive)
calculate_start_end_timesteps(self.refiner_model_wrap, refiner_negative)
# make sure each cond area has an opposite one with the same area
for c in refiner_positive:
create_cond_with_same_area_if_none(refiner_negative, c)
for c in refiner_negative:
create_cond_with_same_area_if_none(refiner_positive, c)
if self.model.is_adm():
refiner_positive = encode_adm(self.refiner_model, refiner_positive, noise.shape[0],
noise.shape[3], noise.shape[2], self.device, "positive")
refiner_negative = encode_adm(self.refiner_model, refiner_negative, noise.shape[0],
noise.shape[3], noise.shape[2], self.device, "negative")
def refiner_switch():
comfy.model_management.load_model_gpu(self.refiner_model_patcher)
self.model_denoise.inner_model = self.refiner_model_denoise.inner_model
for i in range(len(positive)):
positive[i] = refiner_positive[i]
for i in range(len(negative)):
negative[i] = refiner_negative[i]
return
def callback(step, x0, x, total_steps):
if step == refiner_switch_step:
refiner_switch()
if callback_function is not None:
callback_function(step, x0, x, total_steps)
if latent_image is not None:
latent_image = self.model.process_latent_in(latent_image)