Refactored 'registered' to be HookGroup instead of a list of Hooks, made AddModelsHook operational and compliant with should_register result, moved TransformerOptionsHook handling out of ModelPatcher.register_all_hook_patches, support patches in TransformerOptionsHook properly by casting any patches/wrappers/hooks to proper device at sample time
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@@ -819,9 +819,58 @@ def get_total_hook_groups_in_conds(conds: dict[str, list[dict[str]]]):
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return len(hooks_set)
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def cast_to_load_options(model_options: dict[str], device=None, dtype=None):
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'''
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If any patches from hooks, wrappers, or callbacks have .to to be called, call it.
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'''
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if model_options is None:
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return
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to_load_options = model_options.get("to_load_options", None)
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if to_load_options is None:
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return
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casts = []
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if device is not None:
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casts.append(device)
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if dtype is not None:
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casts.append(dtype)
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# if nothing to apply, do nothing
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if len(casts) == 0:
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return
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# Try to call .to on patches
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if "patches" in to_load_options:
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patches = to_load_options["patches"]
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for name in patches:
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patch_list = patches[name]
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for i in range(len(patch_list)):
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if hasattr(patch_list[i], "to"):
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for cast in casts:
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patch_list[i] = patch_list[i].to(cast)
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if "patches_replace" in to_load_options:
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patches = to_load_options["patches_replace"]
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for name in patches:
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patch_list = patches[name]
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for k in patch_list:
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if hasattr(patch_list[k], "to"):
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for cast in casts:
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patch_list[k] = patch_list[k].to(cast)
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# Try to call .to on any wrappers/callbacks
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wrappers_and_callbacks = ["wrappers", "callbacks"]
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for wc_name in wrappers_and_callbacks:
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if wc_name in to_load_options:
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wc: dict[str, list] = to_load_options[wc_name]
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for wc_dict in wc.values():
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for wc_list in wc_dict.values():
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for i in range(len(wc_list)):
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if hasattr(wc_list[i], "to"):
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for cast in casts:
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wc_list[i] = wc_list[i].to(cast)
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class CFGGuider:
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def __init__(self, model_patcher):
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self.model_patcher: 'ModelPatcher' = model_patcher
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def __init__(self, model_patcher: ModelPatcher):
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self.model_patcher = model_patcher
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self.model_options = model_patcher.model_options
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self.original_conds = {}
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self.cfg = 1.0
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@@ -861,7 +910,7 @@ class CFGGuider:
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return self.inner_model.process_latent_out(samples.to(torch.float32))
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def outer_sample(self, noise, latent_image, sampler, sigmas, denoise_mask=None, callback=None, disable_pbar=False, seed=None):
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self.inner_model, self.conds, self.loaded_models = comfy.sampler_helpers.prepare_sampling(self.model_patcher, noise.shape, self.conds)
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self.inner_model, self.conds, self.loaded_models = comfy.sampler_helpers.prepare_sampling(self.model_patcher, noise.shape, self.conds, self.model_options)
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device = self.model_patcher.load_device
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if denoise_mask is not None:
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@@ -870,6 +919,7 @@ class CFGGuider:
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noise = noise.to(device)
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latent_image = latent_image.to(device)
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sigmas = sigmas.to(device)
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cast_to_load_options(self.model_options, device=device, dtype=self.model_patcher.model_dtype())
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try:
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self.model_patcher.pre_run()
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@@ -906,6 +956,7 @@ class CFGGuider:
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)
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output = executor.execute(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
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finally:
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cast_to_load_options(self.model_options, device=self.model_patcher.offload_device)
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self.model_options = orig_model_options
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self.model_patcher.hook_mode = orig_hook_mode
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self.model_patcher.restore_hook_patches()
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