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fix colab

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lvmin
2023-08-19 17:23:55 -07:00
parent 4bc5b0e50f
commit 63545b224e
3 changed files with 9 additions and 10 deletions
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modules/core.py
+7 -7
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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, get_additional_models, cleanup_additional_models
from comfy.sample import prepare_mask, broadcast_cond, load_additional_models, cleanup_additional_models
from modules.samplers_advanced import KSampler, KSamplerWithRefiner
from modules.patch import patch_all
@@ -133,6 +133,8 @@ 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)
@@ -141,9 +143,7 @@ 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 = 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]))
models = load_additional_models(positive, negative, model.model_dtype())
sampler = KSampler(real_model, steps=steps, device=device, sampler=sampler_name, scheduler=scheduler,
denoise=denoise, model_options=model.model_options)
@@ -206,6 +206,8 @@ 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)
@@ -215,9 +217,7 @@ 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 = 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]))
models = load_additional_models(positive, negative, model.model_dtype())
sampler = KSamplerWithRefiner(model=model, refiner_model=refiner, steps=steps, device=device,
sampler=sampler_name, scheduler=scheduler,