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update dep, sampler (#217)

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lllyasviel
2023-08-19 14:35:25 -07:00
committed by GitHub
parent d2e7d940ce
commit 084f1dfb72
5 changed files with 16 additions and 11 deletions
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modules/core.py
+9 -8
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@@ -9,7 +9,7 @@ import comfy.utils
from comfy.sd import load_checkpoint_guess_config
from nodes import VAEDecode, EmptyLatentImage, CLIPTextEncode
from comfy.sample import prepare_mask, broadcast_cond, load_additional_models, cleanup_additional_models
from comfy.sample import prepare_mask, broadcast_cond, get_additional_models, cleanup_additional_models
from modules.samplers_advanced import KSampler, KSamplerWithRefiner
from modules.patch import patch_all
@@ -92,7 +92,7 @@ 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',
def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sampler_name='uni_pc',
scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
force_full_denoise=False, callback_function=None):
# SCHEDULERS = ["normal", "karras", "exponential", "simple", "ddim_uniform"]
@@ -133,7 +133,6 @@ def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sa
if noise_mask is not None:
noise_mask = prepare_mask(noise_mask, noise.shape, device)
comfy.model_management.load_model_gpu(model)
real_model = model.model
noise = noise.to(device)
@@ -142,7 +141,9 @@ def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sa
positive_copy = broadcast_cond(positive, noise.shape[0], device)
negative_copy = broadcast_cond(negative, noise.shape[0], device)
models = load_additional_models(positive, negative, model.model_dtype())
models = get_additional_models(positive, negative)
comfy.model_management.load_models_gpu([model] + models, comfy.model_management.batch_area_memory(
noise.shape[0] * noise.shape[2] * noise.shape[3]))
sampler = KSampler(real_model, steps=steps, device=device, sampler=sampler_name, scheduler=scheduler,
denoise=denoise, model_options=model.model_options)
@@ -164,7 +165,7 @@ def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sa
@torch.no_grad()
def ksampler_with_refiner(model, positive, negative, refiner, refiner_positive, refiner_negative, latent,
seed=None, steps=30, refiner_switch_step=20, cfg=7.0, sampler_name='dpmpp_2m_sde_gpu',
seed=None, steps=30, refiner_switch_step=20, cfg=7.0, sampler_name='uni_pc',
scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
force_full_denoise=False, callback_function=None):
# SCHEDULERS = ["normal", "karras", "exponential", "simple", "ddim_uniform"]
@@ -205,8 +206,6 @@ def ksampler_with_refiner(model, positive, negative, refiner, refiner_positive,
if noise_mask is not None:
noise_mask = prepare_mask(noise_mask, noise.shape, device)
comfy.model_management.load_model_gpu(model)
noise = noise.to(device)
latent_image = latent_image.to(device)
@@ -216,7 +215,9 @@ def ksampler_with_refiner(model, positive, negative, refiner, refiner_positive,
refiner_positive_copy = broadcast_cond(refiner_positive, noise.shape[0], device)
refiner_negative_copy = broadcast_cond(refiner_negative, noise.shape[0], device)
models = load_additional_models(positive, negative, model.model_dtype())
models = get_additional_models(positive, negative)
comfy.model_management.load_models_gpu([model] + models, comfy.model_management.batch_area_memory(
noise.shape[0] * noise.shape[2] * noise.shape[3]))
sampler = KSamplerWithRefiner(model=model, refiner_model=refiner, steps=steps, device=device,
sampler=sampler_name, scheduler=scheduler,