nodes/shiimizu-ComfyUI-TiledDiffusion
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Support Stable Diffusion x4 upscaler model.

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shiimizu
2024-01-16 15:30:23 -08:00
parent 820fe86998
commit 99c062d2c6
1 changed files with 20 additions and 14 deletions
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tiled_diffusion.py
+20 -14
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@@ -373,9 +373,10 @@ class MultiDiffusion(AbstractDiffusion):
ts_tile = self.repeat_tensor(t_in, n_rep)
cond_tile = self.repeat_tensor(c_crossattn, n_rep)
c_tile = c_in.copy()
if 'y' in c_tile:
c_tile['y'] = self.repeat_tensor(c_tile['y'], n_rep)
c_tile['c_crossattn'] = cond_tile
for key in ['y', 'c_concat']:
if key in c_tile:
c_tile[key] = self.repeat_tensor(c_tile[key], n_rep)
# controlnet tiling
# self.switch_controlnet_tensors(batch_id, N, len(bboxes))
@@ -466,10 +467,11 @@ class MixtureOfDiffusers(AbstractDiffusion):
# batching
x_tile_list = []
t_tile_list = []
tcond_tile_list = []
icond_tile_list = []
vcond_tile_list = []
control_list = []
icond_map = {}
# tcond_tile_list = []
# icond_tile_list = []
# vcond_tile_list = []
# control_list = []
for bbox in bboxes:
x_tile_list.append(x_in[bbox.slicer])
t_tile_list.append(t_in)
@@ -478,11 +480,14 @@ class MixtureOfDiffusers(AbstractDiffusion):
# tcond_tile = c_crossattn #self.get_tcond(c_in) # cond, [1, 77, 768]
# tcond_tile_list.append(tcond_tile)
# present in sdxl
if 'y' in c_in:
icond=c_in['y'] # self.get_icond(c_in)
if icond.shape[2:] == (self.h, self.w):
icond = icond[bbox.slicer]
icond_tile_list.append(icond)
for key in ['y', 'c_concat']:
if key in c_in:
icond=c_in[key] # self.get_icond(c_in)
if icond.shape[2:] == (self.h, self.w):
icond = icond[bbox.slicer]
if icond_map.get(key, None) is None:
icond_map[key] = []
icond_map[key].append(icond)
# # vcond:
# vcond = self.get_vcond(c_in)
# vcond_tile_list.append(vcond)
@@ -493,10 +498,11 @@ class MixtureOfDiffusers(AbstractDiffusion):
t_tile = self.repeat_tensor(t_in, n_rep) # just repeat
tcond_tile = self.repeat_tensor(c_crossattn, n_rep) # just repeat
c_tile = c_in.copy()
if 'y' in c_in:
icond_tile = torch.cat(icond_tile_list, dim=0) # differs each
c_tile['y'] = icond_tile
c_tile['c_crossattn'] = tcond_tile
for key in ['y', 'c_concat']:
if key in c_in:
icond_tile = torch.cat(icond_map[key], dim=0) # differs each
c_tile[key] = icond_tile
# vcond_tile = torch.cat(vcond_tile_list, dim=0) if None not in vcond_tile_list else None # just repeat
# controlnet