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Add a way to set a different compute dtype for the model at runtime.

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Currently only works for diffusion models.
This commit is contained in:
comfyanonymous 2025-02-13 20:34:03 -05:00
parent 8773ccf74d
commit 019c7029ea
1 changed files with 18 additions and 2 deletions
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20
comfy/model_patcher.py
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@ -218,6 +218,7 @@ class ModelPatcher:
self.load_device = load_device self.load_device = load_device
self.offload_device = offload_device self.offload_device = offload_device
self.weight_inplace_update = weight_inplace_update self.weight_inplace_update = weight_inplace_update
self.force_cast_weights = False
self.patches_uuid = uuid.uuid4() self.patches_uuid = uuid.uuid4()
self.parent = None self.parent = None
@ -277,6 +278,8 @@ class ModelPatcher:
n.object_patches_backup = self.object_patches_backup n.object_patches_backup = self.object_patches_backup
n.parent = self n.parent = self
n.force_cast_weights = self.force_cast_weights
# attachments # attachments
n.attachments = {} n.attachments = {}
for k in self.attachments: for k in self.attachments:
@ -424,6 +427,12 @@ class ModelPatcher:
def add_object_patch(self, name, obj): def add_object_patch(self, name, obj):
self.object_patches[name] = obj self.object_patches[name] = obj
def set_model_compute_dtype(self, dtype):
self.add_object_patch("manual_cast_dtype", dtype)
if dtype is not None:
self.force_cast_weights = True
self.patches_uuid = uuid.uuid4() #TODO: optimize by preventing a full model reload for this
def add_weight_wrapper(self, name, function): def add_weight_wrapper(self, name, function):
self.weight_wrapper_patches[name] = self.weight_wrapper_patches.get(name, []) + [function] self.weight_wrapper_patches[name] = self.weight_wrapper_patches.get(name, []) + [function]
self.patches_uuid = uuid.uuid4() self.patches_uuid = uuid.uuid4()
@ -602,6 +611,7 @@ class ModelPatcher:
if hasattr(m, "prev_comfy_cast_weights"): #Already lowvramed if hasattr(m, "prev_comfy_cast_weights"): #Already lowvramed
continue continue
cast_weight = self.force_cast_weights
if lowvram_weight: if lowvram_weight:
if hasattr(m, "comfy_cast_weights"): if hasattr(m, "comfy_cast_weights"):
m.weight_function = [] m.weight_function = []
@ -620,8 +630,7 @@ class ModelPatcher:
m.bias_function = [LowVramPatch(bias_key, self.patches)] m.bias_function = [LowVramPatch(bias_key, self.patches)]
patch_counter += 1 patch_counter += 1
m.prev_comfy_cast_weights = m.comfy_cast_weights cast_weight = True
m.comfy_cast_weights = True
else: else:
if hasattr(m, "comfy_cast_weights"): if hasattr(m, "comfy_cast_weights"):
wipe_lowvram_weight(m) wipe_lowvram_weight(m)
@ -630,6 +639,10 @@ class ModelPatcher:
mem_counter += module_mem mem_counter += module_mem
load_completely.append((module_mem, n, m, params)) load_completely.append((module_mem, n, m, params))
if cast_weight:
m.prev_comfy_cast_weights = m.comfy_cast_weights
m.comfy_cast_weights = True
if weight_key in self.weight_wrapper_patches: if weight_key in self.weight_wrapper_patches:
m.weight_function.extend(self.weight_wrapper_patches[weight_key]) m.weight_function.extend(self.weight_wrapper_patches[weight_key])
@ -766,6 +779,7 @@ class ModelPatcher:
weight_key = "{}.weight".format(n) weight_key = "{}.weight".format(n)
bias_key = "{}.bias".format(n) bias_key = "{}.bias".format(n)
if move_weight: if move_weight:
cast_weight = self.force_cast_weights
m.to(device_to) m.to(device_to)
module_mem += move_weight_functions(m, device_to) module_mem += move_weight_functions(m, device_to)
if lowvram_possible: if lowvram_possible:
@ -775,7 +789,9 @@ class ModelPatcher:
if bias_key in self.patches: if bias_key in self.patches:
m.bias_function.append(LowVramPatch(bias_key, self.patches)) m.bias_function.append(LowVramPatch(bias_key, self.patches))
patch_counter += 1 patch_counter += 1
cast_weight = True
if cast_weight:
m.prev_comfy_cast_weights = m.comfy_cast_weights m.prev_comfy_cast_weights = m.comfy_cast_weights
m.comfy_cast_weights = True m.comfy_cast_weights = True
m.comfy_patched_weights = False m.comfy_patched_weights = False