fix
This commit is contained in:
lllyasviel
2023-10-11 03:33:28 -07:00
committed by GitHub
parent bbdf4bd120
commit 5e6b27a680
3 changed files with 9 additions and 3 deletions
+1 -1
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@@ -1 +1 @@
version = '2.1.48' version = '2.1.49'
+6 -1
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@@ -197,7 +197,9 @@ def get_previewer():
@torch.inference_mode() @torch.inference_mode()
def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sampler_name='dpmpp_fooocus_2m_sde_inpaint_seamless', def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sampler_name='dpmpp_fooocus_2m_sde_inpaint_seamless',
scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None, scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
force_full_denoise=False, callback_function=None, refiner=None, refiner_switch=-1, previewer_start=None, previewer_end=None): force_full_denoise=False, callback_function=None, refiner=None, refiner_switch=-1,
previewer_start=None, previewer_end=None, noise_multiplier=1.0):
latent_image = latent["samples"] latent_image = latent["samples"]
if disable_noise: if disable_noise:
noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu") noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
@@ -205,6 +207,9 @@ def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sa
batch_inds = latent["batch_index"] if "batch_index" in latent else None batch_inds = latent["batch_index"] if "batch_index" in latent else None
noise = comfy.sample.prepare_noise(latent_image, seed, batch_inds) noise = comfy.sample.prepare_noise(latent_image, seed, batch_inds)
if noise_multiplier != 1.0:
noise = noise * noise_multiplier
noise_mask = None noise_mask = None
if "noise_mask" in latent: if "noise_mask" in latent:
noise_mask = latent["noise_mask"] noise_mask = latent["noise_mask"]
+2 -1
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@@ -123,7 +123,7 @@ def refresh_refiner_model(name):
xl_refiner.clip = None xl_refiner.clip = None
xl_refiner.vae = None xl_refiner.vae = None
else: else:
xl_refiner = None # 1.5/2.1 not supported yet. xl_refiner.clip = None
return return
@@ -387,6 +387,7 @@ def process_diffusion(positive_cond, negative_cond, steps, switch, width, height
scheduler=scheduler_name, scheduler=scheduler_name,
previewer_start=switch, previewer_start=switch,
previewer_end=steps, previewer_end=steps,
noise_multiplier=1.2,
) )
target_model = final_refiner_vae target_model = final_refiner_vae