nodes/shiimizu-ComfyUI-TiledDiffusion
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Update ControlNet code.

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* ModelPatcher Overhaul and Hook Support. See https://github.com/comfyanonymous/ComfyUI/commit/0ee322ec5f338791c5836b79830e2f419d6fcc79
* Support official SD3.5 Controlnets. See https://github.com/comfyanonymous/ComfyUI/commit/4c82741b545c6cedcfa397034f56ce1377b3675a
* Resolves #53
This commit is contained in:
shiimizu
2024-12-02 14:41:39 -08:00
parent 18b68bb828
commit 448e961d82
1 changed files with 6 additions and 5 deletions
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tiled_diffusion.py
+6 -5
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@@ -354,10 +354,10 @@ class AbstractDiffusion:
del control.cond_hint
control.cond_hint = None
compression_ratio = control.compression_ratio
if control.vae is not None:
if getattr(control, 'vae', None) is not None:
compression_ratio *= control.vae.downscale_ratio
else:
if control.latent_format is not None:
if getattr(control, 'latent_format', None) is not None:
raise ValueError("This Controlnet needs a VAE but none was provided, please use a ControlNetApply node with a VAE input and connect it.")
PH, PW = self.h * compression_ratio, self.w * compression_ratio
@@ -378,6 +378,7 @@ class AbstractDiffusion:
cns = common_upscale(control.cond_hint_original, PW, PH, control.upscale_algorithm, "center").to(dtype=dtype, device=device)
else:
cns = common_upscale(control.cond_hint_original, PW, PH, control.upscale_algorithm, 'center').to(dtype=dtype, device=device)
cns = control.preprocess_image(cns)
if getattr(control, 'vae', None) is not None:
loaded_models_ = loaded_models(only_currently_used=True)
cns = control.vae.encode(cns.movedim(1, -1))
@@ -521,7 +522,7 @@ class MultiDiffusion(AbstractDiffusion):
# self.switch_controlnet_tensors(batch_id, N, len(bboxes))
if 'control' in c_in:
self.process_controlnet(x_tile, c_in, cond_or_uncond, bboxes, N, batch_id)
c_tile['control'] = c_in['control'].get_control_orig(x_tile, t_tile, c_tile, len(cond_or_uncond))
c_tile['control'] = c_in['control'].get_control_orig(x_tile, t_tile, c_tile, len(cond_or_uncond), c_in['transformer_options'])
# stablesr tiling
# self.switch_stablesr_tensors(batch_id)
@@ -675,7 +676,7 @@ class SpotDiffusion(AbstractDiffusion):
# self.switch_controlnet_tensors(batch_id, N, len(bboxes))
if 'control' in c_in:
self.process_controlnet(x_tile, c_in, cond_or_uncond, bboxes, N, batch_id, (sh_h,sh_w), condition)
c_tile['control'] = c_in['control'].get_control_orig(x_tile, t_tile, c_tile, len(cond_or_uncond))
c_tile['control'] = c_in['control'].get_control_orig(x_tile, t_tile, c_tile, len(cond_or_uncond), c_in['transformer_options'])
# stablesr tiling
# self.switch_stablesr_tensors(batch_id)
@@ -795,7 +796,7 @@ class MixtureOfDiffusers(AbstractDiffusion):
# self.switch_controlnet_tensors(batch_id, N, len(bboxes), is_denoise=True)
if 'control' in c_in:
self.process_controlnet(x_tile, c_in, cond_or_uncond, bboxes, N, batch_id)
c_tile['control'] = c_in['control'].get_control_orig(x_tile, t_tile, c_tile, len(cond_or_uncond))
c_tile['control'] = c_in['control'].get_control_orig(x_tile, t_tile, c_tile, len(cond_or_uncond), c_in['transformer_options'])
# stablesr
# self.switch_stablesr_tensors(batch_id)