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from backend import utils |
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class ForgeObjects: |
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def __init__(self, unet, clip, vae, clipvision): |
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self.unet = unet |
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self.clip = clip |
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self.vae = vae |
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self.clipvision = clipvision |
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def shallow_copy(self): |
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return ForgeObjects(self.unet, self.clip, self.vae, self.clipvision) |
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class ForgeDiffusionEngine: |
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matched_guesses = [] |
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def __init__(self, estimated_config, huggingface_components): |
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self.model_config = estimated_config |
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self.is_inpaint = estimated_config.inpaint_model() |
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self.forge_objects = None |
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self.forge_objects_original = None |
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self.forge_objects_after_applying_lora = None |
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self.current_lora_hash = str([]) |
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self.fix_for_webui_backward_compatibility() |
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def set_clip_skip(self, clip_skip): |
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pass |
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def get_first_stage_encoding(self, x): |
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return x |
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def get_learned_conditioning(self, prompt: list[str]): |
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raise NotImplementedError |
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def encode_first_stage(self, x): |
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raise NotImplementedError |
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def decode_first_stage(self, x): |
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raise NotImplementedError |
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def get_prompt_lengths_on_ui(self, prompt): |
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return 0, 75 |
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def is_webui_legacy_model(self): |
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return self.is_sd1 or self.is_sdxl |
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def fix_for_webui_backward_compatibility(self): |
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self.tiling_enabled = False |
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self.first_stage_model = None |
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self.cond_stage_model = None |
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self.use_distilled_cfg_scale = False |
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self.use_shift = False |
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self.is_sd1 = False |
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self.is_sdxl = False |
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self.is_flux = False |
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self.is_wan = False |
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def save_unet(self, filename): |
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import safetensors.torch as sf |
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sd = utils.get_state_dict_after_quant(self.forge_objects.unet.model.diffusion_model) |
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sf.save_file(sd, filename) |
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return filename |
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def save_checkpoint(self, filename): |
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import safetensors.torch as sf |
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sd = {} |
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sd.update(utils.get_state_dict_after_quant(self.forge_objects.unet.model.diffusion_model, prefix="model.diffusion_model.")) |
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sd.update(utils.get_state_dict_after_quant(self.forge_objects.clip.cond_stage_model, prefix="text_encoders.")) |
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sd.update(utils.get_state_dict_after_quant(self.forge_objects.vae.first_stage_model, prefix="vae.")) |
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sf.save_file(sd, filename) |
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return filename |
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