lllyasviel/stable-diffusion-webui-forge
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remove forge_sampler

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layerdiffusion
2024-08-03 15:38:07 -07:00
parent 0b129b7181
commit b8b29a2372
6 changed files with 6 additions and 11 deletions
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2
extensions-builtin/sd_forge_fooocus_inpaint/scripts/forge_fooocus_inpaint.py
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@@ -5,7 +5,7 @@ import backend.patcher.base
from modules_forge.shared import add_supported_control_model
from modules_forge.supported_controlnet import ControlModelPatcher
from modules_forge.forge_sampler import sampling_prepare
from backend.sampling.sampling_function import sampling_prepare
from backend.utils import load_torch_file
from backend.memory_management import cast_to_device, current_loaded_models
from backend.patcher.lora import model_lora_keys_unet

6
modules/sd_samplers_cfg_denoiser.py
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@@ -6,7 +6,7 @@ import modules.shared as shared
from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback
from modules.script_callbacks import CFGDenoisedParams, cfg_denoised_callback
from modules.script_callbacks import AfterCFGCallbackParams, cfg_after_cfg_callback
from modules_forge import forge_sampler
from backend.sampling.sampling_function import sampling_function
def catenate_conds(conds):
@@ -179,8 +179,7 @@ class CFGDenoiser(torch.nn.Module):
denoiser_params = CFGDenoiserParams(x, image_cond, sigma, state.sampling_step, state.sampling_steps, cond, uncond, self)
cfg_denoiser_callback(denoiser_params)
denoised = forge_sampler.forge_sample(self, denoiser_params=denoiser_params,
cond_scale=cond_scale, cond_composition=cond_composition)
denoised = sampling_function(self, denoiser_params=denoiser_params, cond_scale=cond_scale, cond_composition=cond_composition)
if self.mask is not None:
blended_latent = denoised * self.nmask + self.init_latent * self.mask
@@ -207,4 +206,3 @@ class CFGDenoiser(torch.nn.Module):
return eps
return denoised.to(device=original_x_device, dtype=original_x_dtype)

2
modules/sd_samplers_common.py
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@@ -5,7 +5,7 @@ import torch
from PIL import Image
from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared, sd_models
from modules.shared import opts, state
from modules_forge.forge_sampler import sampling_prepare, sampling_cleanup
from backend.sampling.sampling_function import sampling_prepare, sampling_cleanup
from modules import extra_networks
import k_diffusion.sampling

2
modules/sd_samplers_kdiffusion.py
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@@ -7,7 +7,7 @@ from modules.script_callbacks import ExtraNoiseParams, extra_noise_callback
from modules.shared import opts
import modules.shared as shared
from modules_forge.forge_sampler import sampling_prepare, sampling_cleanup
from backend.sampling.sampling_function import sampling_prepare, sampling_cleanup
samplers_k_diffusion = [

2
modules/sd_samplers_timesteps.py
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@@ -7,7 +7,7 @@ from modules.script_callbacks import ExtraNoiseParams, extra_noise_callback
from modules.shared import opts
import modules.shared as shared
from modules_forge.forge_sampler import sampling_prepare, sampling_cleanup
from backend.sampling.sampling_function import sampling_prepare, sampling_cleanup
samplers_timesteps = [

3
modules_forge/forge_sampler.py
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@@ -1,3 +0,0 @@
from backend.sampling.sampling_function import *
forge_sample = sampling_function