mirror of
https://github.com/lllyasviel/stable-diffusion-webui-forge.git
synced 2026-07-21 21:01:24 +08:00
107 lines
3.2 KiB
Python
107 lines
3.2 KiB
Python
from typing import TYPE_CHECKING
|
|
|
|
if TYPE_CHECKING:
|
|
import torch
|
|
|
|
from backend.patcher.clip import CLIP
|
|
from backend.patcher.unet import UnetPatcher
|
|
from backend.patcher.vae import VAE
|
|
|
|
from backend import memory_management, utils
|
|
|
|
|
|
class ForgeObjects:
|
|
def __init__(self, unet, clip, vae, clipvision):
|
|
self.unet: "UnetPatcher" = unet
|
|
self.clip: "CLIP" = clip
|
|
self.vae: "VAE" = vae
|
|
self.clipvision = clipvision
|
|
|
|
def shallow_copy(self):
|
|
return ForgeObjects(self.unet, self.clip, self.vae, self.clipvision)
|
|
|
|
|
|
class ForgeDiffusionEngine:
|
|
matched_guesses = []
|
|
|
|
def __init__(self, estimated_config, huggingface_components):
|
|
self.model_config = estimated_config
|
|
self.is_inpaint = estimated_config.inpaint_model()
|
|
|
|
self.forge_objects: "ForgeObjects" = None
|
|
self.forge_objects_original: "ForgeObjects" = None
|
|
self.forge_objects_after_applying_lora: "ForgeObjects" = None
|
|
|
|
self.current_lora_hash = str([])
|
|
|
|
self.fix_for_webui_backward_compatibility()
|
|
|
|
self.ini_latent: "torch.Tensor" = None # image from img2img input
|
|
self.ref_latents: list["torch.Tensor"] = [] # images from ImageStitch
|
|
|
|
def set_clip_skip(self, clip_skip):
|
|
pass
|
|
|
|
def get_first_stage_encoding(self, x):
|
|
return x
|
|
|
|
def get_learned_conditioning(self, prompt: list[str]):
|
|
raise NotImplementedError
|
|
|
|
def encode_first_stage(self, x):
|
|
raise NotImplementedError
|
|
|
|
def decode_first_stage(self, x):
|
|
raise NotImplementedError
|
|
|
|
def get_prompt_lengths_on_ui(self, prompt):
|
|
return 0, 75
|
|
|
|
def is_webui_legacy_model(self):
|
|
return self.is_sd1 or self.is_sdxl
|
|
|
|
def fix_for_webui_backward_compatibility(self):
|
|
self.tiling_enabled = False
|
|
self.use_distilled_cfg_scale = False
|
|
self.use_shift = False
|
|
self.is_sd1 = False
|
|
self.is_sdxl = False
|
|
self.is_flux = False # affects the usage of TAESD
|
|
self.is_wan = False # affects the usage of WanVAE (B, C, T, H, W)
|
|
|
|
@property
|
|
def first_stage_model(self):
|
|
try:
|
|
return self.forge_objects.vae.first_stage_model
|
|
except Exception:
|
|
return None
|
|
|
|
@property
|
|
def cond_stage_model(self):
|
|
try:
|
|
return self.forge_objects.clip.cond_stage_model
|
|
except Exception:
|
|
return None
|
|
|
|
def clear_references(self):
|
|
# called by ImageStitch
|
|
self.ref_latents.clear()
|
|
memory_management.soft_empty_cache()
|
|
|
|
def save_unet(self, filename):
|
|
import safetensors.torch as sf
|
|
|
|
sd = utils.get_state_dict_after_quant(self.forge_objects.unet.model.diffusion_model)
|
|
sf.save_file(sd, filename)
|
|
return filename
|
|
|
|
def save_checkpoint(self, filename):
|
|
import safetensors.torch as sf
|
|
|
|
sd = {}
|
|
sd.update(utils.get_state_dict_after_quant(self.forge_objects.unet.model.diffusion_model, prefix="model.diffusion_model."))
|
|
sd.update(utils.get_state_dict_after_quant(self.forge_objects.clip.cond_stage_model, prefix="text_encoders."))
|
|
sd.update(utils.get_state_dict_after_quant(self.forge_objects.vae.first_stage_model, prefix="vae."))
|
|
sf.save_file(sd, filename)
|
|
return filename
|