nodes/Kosinkadink-ComfyUI-Advanced-ControlNet
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Merge PR #37 from Kosinkadink/comfy_update

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Updated ControlNet code to work with newest ComfyUI changes (probably not backwards compatible)
This commit is contained in:
Jedrzej Kosinski
2023-12-12 14:10:34 -06:00
committed by GitHub
parent 9b0944874e f297890854
commit 296a9ef49c
1 changed files with 13 additions and 10 deletions
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control/control.py
+13 -10
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@@ -559,8 +559,8 @@ class AdvancedControlBase:
class ControlNetAdvanced(ControlNet, AdvancedControlBase):
def __init__(self, control_model, timestep_keyframes: TimestepKeyframeGroup, global_average_pooling=False, device=None):
super().__init__(control_model=control_model, global_average_pooling=global_average_pooling, device=device)
def __init__(self, control_model, timestep_keyframes: TimestepKeyframeGroup, global_average_pooling=False, device=None, load_device=None, manual_cast_dtype=None):
super().__init__(control_model=control_model, global_average_pooling=global_average_pooling, device=device, load_device=load_device, manual_cast_dtype=manual_cast_dtype)
AdvancedControlBase.__init__(self, super(), timestep_keyframes=timestep_keyframes, weights_default=ControlWeights.controlnet())
def get_universal_weights(self) -> ControlWeights:
@@ -583,8 +583,11 @@ class ControlNetAdvanced(ControlNet, AdvancedControlBase):
else:
return None
output_dtype = x_noisy.dtype
dtype = self.control_model.dtype
if self.manual_cast_dtype is not None:
dtype = self.manual_cast_dtype
output_dtype = x_noisy.dtype
# make cond_hint appropriate dimensions
# TODO: change this to not require cond_hint upscaling every step when self.sub_idxs are present
if self.sub_idxs is not None or self.cond_hint is None or x_noisy.shape[2] * 8 != self.cond_hint.shape[2] or x_noisy.shape[3] * 8 != self.cond_hint.shape[3]:
@@ -593,14 +596,14 @@ class ControlNetAdvanced(ControlNet, AdvancedControlBase):
self.cond_hint = None
# if self.cond_hint_original length greater or equal to real latent count, subdivide it before scaling
if self.sub_idxs is not None and self.cond_hint_original.size(0) >= self.full_latent_length:
self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original[self.sub_idxs], x_noisy.shape[3] * 8, x_noisy.shape[2] * 8, 'nearest-exact', "center").to(self.control_model.dtype).to(self.device)
self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original[self.sub_idxs], x_noisy.shape[3] * 8, x_noisy.shape[2] * 8, 'nearest-exact', "center").to(dtype).to(self.device)
else:
self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original, x_noisy.shape[3] * 8, x_noisy.shape[2] * 8, 'nearest-exact', "center").to(self.control_model.dtype).to(self.device)
self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original, x_noisy.shape[3] * 8, x_noisy.shape[2] * 8, 'nearest-exact', "center").to(dtype).to(self.device)
if x_noisy.shape[0] != self.cond_hint.shape[0]:
self.cond_hint = broadcast_image_to(self.cond_hint, x_noisy.shape[0], batched_number)
# prepare mask_cond_hint
self.prepare_mask_cond_hint(x_noisy=x_noisy, t=t, cond=cond, batched_number=batched_number, dtype=self.control_model.dtype)
self.prepare_mask_cond_hint(x_noisy=x_noisy, t=t, cond=cond, batched_number=batched_number, dtype=dtype)
context = cond['c_crossattn']
# uses 'y' in new ComfyUI update
@@ -608,15 +611,15 @@ class ControlNetAdvanced(ControlNet, AdvancedControlBase):
if y is None: # TODO: remove this in the future since no longer used by newest ComfyUI
y = cond.get('c_adm', None)
if y is not None:
y = y.to(self.control_model.dtype)
y = y.to(dtype)
timestep = self.model_sampling_current.timestep(t)
x_noisy = self.model_sampling_current.calculate_input(t, x_noisy)
control = self.control_model(x=x_noisy.to(self.control_model.dtype), hint=self.cond_hint, timesteps=timestep.float(), context=context.to(self.control_model.dtype), y=y)
control = self.control_model(x=x_noisy.to(dtype), hint=self.cond_hint, timesteps=timestep.float(), context=context.to(dtype), y=y)
return self.control_merge(None, control, control_prev, output_dtype)
def copy(self):
c = ControlNetAdvanced(self.control_model, self.timestep_keyframes, global_average_pooling=self.global_average_pooling)
c = ControlNetAdvanced(self.control_model, self.timestep_keyframes, global_average_pooling=self.global_average_pooling, load_device=self.load_device, manual_cast_dtype=self.manual_cast_dtype)
self.copy_to(c)
self.copy_to_advanced(c)
return c
@@ -624,7 +627,7 @@ class ControlNetAdvanced(ControlNet, AdvancedControlBase):
@staticmethod
def from_vanilla(v: ControlNet, timestep_keyframe: TimestepKeyframeGroup=None) -> 'ControlNetAdvanced':
return ControlNetAdvanced(control_model=v.control_model, timestep_keyframes=timestep_keyframe,
global_average_pooling=v.global_average_pooling, device=v.device)
global_average_pooling=v.global_average_pooling, device=v.device, load_device=v.load_device, manual_cast_dtype=v.manual_cast_dtype)
class T2IAdapterAdvanced(T2IAdapter, AdvancedControlBase):