+2707
-319
lines changedFilter options
+2707
-319
lines changed Original file line number Diff line number Diff line change
@@ -36,6 +36,10 @@
36 36
import comfy.ldm.hydit.controlnet
37 37
import comfy.ldm.flux.controlnet
38 38
import comfy.cldm.dit_embedder
39 +
from typing import TYPE_CHECKING
40 +
if TYPE_CHECKING:
41 +
from comfy.hooks import HookGroup
42 + 39 43 40 44
def broadcast_image_to(tensor, target_batch_size, batched_number):
41 45
current_batch_size = tensor.shape[0]
@@ -78,6 +82,7 @@ def __init__(self):
78 82
self.concat_mask = False
79 83
self.extra_concat_orig = []
80 84
self.extra_concat = None
85 +
self.extra_hooks: HookGroup = None
81 86
self.preprocess_image = lambda a: a
82 87 83 88
def set_cond_hint(self, cond_hint, strength=1.0, timestep_percent_range=(0.0, 1.0), vae=None, extra_concat=[]):
@@ -115,6 +120,14 @@ def get_models(self):
115 120
if self.previous_controlnet is not None:
116 121
out += self.previous_controlnet.get_models()
117 122
return out
123 + 124 +
def get_extra_hooks(self):
125 +
out = []
126 +
if self.extra_hooks is not None:
127 +
out.append(self.extra_hooks)
128 +
if self.previous_controlnet is not None:
129 +
out += self.previous_controlnet.get_extra_hooks()
130 +
return out
118 131 119 132
def copy_to(self, c):
120 133
c.cond_hint_original = self.cond_hint_original
@@ -130,6 +143,7 @@ def copy_to(self, c):
130 143
c.strength_type = self.strength_type
131 144
c.concat_mask = self.concat_mask
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c.extra_concat_orig = self.extra_concat_orig.copy()
146 +
c.extra_hooks = self.extra_hooks.clone() if self.extra_hooks else None
133 147
c.preprocess_image = self.preprocess_image
134 148 135 149
def inference_memory_requirements(self, dtype):
@@ -200,10 +214,10 @@ def __init__(self, control_model=None, global_average_pooling=False, compression
200 214
self.concat_mask = concat_mask
201 215
self.preprocess_image = preprocess_image
202 216 203 -
def get_control(self, x_noisy, t, cond, batched_number):
217 +
def get_control(self, x_noisy, t, cond, batched_number, transformer_options):
204 218
control_prev = None
205 219
if self.previous_controlnet is not None:
206 -
control_prev = self.previous_controlnet.get_control(x_noisy, t, cond, batched_number)
220 +
control_prev = self.previous_controlnet.get_control(x_noisy, t, cond, batched_number, transformer_options)
207 221 208 222
if self.timestep_range is not None:
209 223
if t[0] > self.timestep_range[0] or t[0] < self.timestep_range[1]:
@@ -758,10 +772,10 @@ def scale_image_to(self, width, height):
758 772
height = math.ceil(height / unshuffle_amount) * unshuffle_amount
759 773
return width, height
760 774 761 -
def get_control(self, x_noisy, t, cond, batched_number):
775 +
def get_control(self, x_noisy, t, cond, batched_number, transformer_options):
762 776
control_prev = None
763 777
if self.previous_controlnet is not None:
764 -
control_prev = self.previous_controlnet.get_control(x_noisy, t, cond, batched_number)
778 +
control_prev = self.previous_controlnet.get_control(x_noisy, t, cond, batched_number, transformer_options)
765 779 766 780
if self.timestep_range is not None:
767 781
if t[0] > self.timestep_range[0] or t[0] < self.timestep_range[1]:
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