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Disable dynamic_vram when using torch compiler (#12612)
* mp: attach re-construction arguments to model patcher
When making a model-patcher from a unet or ckpt, attach a callable
function that can be called to replay the model construction. This
can be used to deep clone model patcher WRT the actual model.
Originally written by Kosinkadink
f4b99bc623
* mp: Add disable_dynamic clone argument
Add a clone argument that lets a caller clone a ModelPatcher but disable
dynamic to demote the clone to regular MP. This is useful for legacy
features where dynamic_vram support is missing or TBD.
* torch_compile: disable dynamic_vram
This is a bigger feature. Disable for the interim to preserve
functionality.
This commit is contained in:
@ -271,6 +271,7 @@ class ModelPatcher:
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self.is_clip = False
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self.hook_mode = comfy.hooks.EnumHookMode.MaxSpeed
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self.cached_patcher_init: tuple[Callable, tuple] | None = None
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if not hasattr(self.model, 'model_loaded_weight_memory'):
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self.model.model_loaded_weight_memory = 0
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@ -307,8 +308,15 @@ class ModelPatcher:
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def get_free_memory(self, device):
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return comfy.model_management.get_free_memory(device)
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def clone(self):
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n = self.__class__(self.model, self.load_device, self.offload_device, self.model_size(), weight_inplace_update=self.weight_inplace_update)
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def clone(self, disable_dynamic=False):
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class_ = self.__class__
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model = self.model
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if self.is_dynamic() and disable_dynamic:
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class_ = ModelPatcher
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temp_model_patcher = self.cached_patcher_init[0](*self.cached_patcher_init[1], disable_dynamic=True)
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model = temp_model_patcher.model
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n = class_(model, self.load_device, self.offload_device, self.model_size(), weight_inplace_update=self.weight_inplace_update)
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n.patches = {}
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for k in self.patches:
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n.patches[k] = self.patches[k][:]
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@ -362,6 +370,8 @@ class ModelPatcher:
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n.is_clip = self.is_clip
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n.hook_mode = self.hook_mode
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n.cached_patcher_init = self.cached_patcher_init
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for callback in self.get_all_callbacks(CallbacksMP.ON_CLONE):
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callback(self, n)
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return n
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