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Merge branch 'comfyanonymous:master' into master

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patientx 2025-11-10 14:05:53 +03:00 committed by GitHub
commit 3662d0a2ce
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3 changed files with 25 additions and 11 deletions
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11
comfy/model_management.py
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@ -504,7 +504,11 @@ class LoadedModel:
use_more_vram = lowvram_model_memory
if use_more_vram == 0:
use_more_vram = 1e32
self.model_use_more_vram(use_more_vram, force_patch_weights=force_patch_weights)
if use_more_vram > 0:
self.model_use_more_vram(use_more_vram, force_patch_weights=force_patch_weights)
else:
self.model.partially_unload(self.model.offload_device, -use_more_vram, force_patch_weights=force_patch_weights)
real_model = self.model.model
if is_intel_xpu() and not args.disable_ipex_optimize and 'ipex' in globals() and real_model is not None:
@ -690,7 +694,10 @@ def load_models_gpu(models, memory_required=0, force_patch_weights=False, minimu
current_free_mem = get_free_memory(torch_dev) + loaded_memory
lowvram_model_memory = max(128 * 1024 * 1024, (current_free_mem - minimum_memory_required), min(current_free_mem * MIN_WEIGHT_MEMORY_RATIO, current_free_mem - minimum_inference_memory()))
lowvram_model_memory = max(0.1, lowvram_model_memory - loaded_memory)
lowvram_model_memory = lowvram_model_memory - loaded_memory
if lowvram_model_memory == 0:
lowvram_model_memory = 0.1
if vram_set_state == VRAMState.NO_VRAM:
lowvram_model_memory = 0.1

21
comfy/model_patcher.py
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@ -843,7 +843,7 @@ class ModelPatcher:
self.object_patches_backup.clear()
def partially_unload(self, device_to, memory_to_free=0):
def partially_unload(self, device_to, memory_to_free=0, force_patch_weights=False):
with self.use_ejected():
hooks_unpatched = False
memory_freed = 0
@ -887,13 +887,19 @@ class ModelPatcher:
module_mem += move_weight_functions(m, device_to)
if lowvram_possible:
if weight_key in self.patches:
_, set_func, convert_func = get_key_weight(self.model, weight_key)
m.weight_function.append(LowVramPatch(weight_key, self.patches, convert_func, set_func))
patch_counter += 1
if force_patch_weights:
self.patch_weight_to_device(weight_key)
else:
_, set_func, convert_func = get_key_weight(self.model, weight_key)
m.weight_function.append(LowVramPatch(weight_key, self.patches, convert_func, set_func))
patch_counter += 1
if bias_key in self.patches:
_, set_func, convert_func = get_key_weight(self.model, bias_key)
m.bias_function.append(LowVramPatch(bias_key, self.patches, convert_func, set_func))
patch_counter += 1
if force_patch_weights:
self.patch_weight_to_device(bias_key)
else:
_, set_func, convert_func = get_key_weight(self.model, bias_key)
m.bias_function.append(LowVramPatch(bias_key, self.patches, convert_func, set_func))
patch_counter += 1
cast_weight = True
if cast_weight:
@ -909,6 +915,7 @@ class ModelPatcher:
self.model.model_lowvram = True
self.model.lowvram_patch_counter += patch_counter
self.model.model_loaded_weight_memory -= memory_freed
logging.info("loaded partially: {:.2f} MB loaded, lowvram patches: {}".format(self.model.model_loaded_weight_memory / (1024 * 1024), self.model.lowvram_patch_counter))
return memory_freed
def partially_load(self, device_to, extra_memory=0, force_patch_weights=False):

4
comfy/ops.py
View File

@ -110,9 +110,9 @@ def cast_bias_weight(s, input=None, dtype=None, device=None, bias_dtype=None, of
for f in s.bias_function:
bias = f(bias)
weight = weight.to(dtype=dtype)
if weight_has_function:
if weight_has_function or weight.dtype != dtype:
with wf_context:
weight = weight.to(dtype=dtype)
for f in s.weight_function:
weight = f(weight)