nodes/kijai-ComfyUI-WanVideoWrapper
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Support T2V with Fun InP models

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kijai
2025-03-26 22:00:18 +02:00
parent 921e577ad9
commit 94ede80e57
1 changed files with 16 additions and 4 deletions
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nodes.py
+16 -4
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@@ -1807,17 +1807,29 @@ class WanVideoSampler:
control_latents = control_embeds["control_images"].to(device)
if control_lora:
image_cond = control_latents.to(device)
if not patcher.model.is_patched:
log.info("Re-loading control LoRA...")
patcher = apply_lora(patcher, device, device, low_mem_load=False)
patcher.model.is_patched = True
else:
image_cond = torch.zeros_like(control_latents).to(device)
clip_fea = None
control_start_percent = control_embeds.get("start_percent", 0.0)
control_end_percent = control_embeds.get("end_percent", 1.0)
else:
if transformer.in_dim == 36: #fun inp
mask_latents = torch.tile(
torch.zeros_like(noise[:1]), [4, 1, 1, 1]
)
print(mask_latents.shape)
masked_video_latents_input = torch.zeros_like(noise)
print(masked_video_latents_input.shape)
image_cond = torch.cat([mask_latents, masked_video_latents_input], dim=0).to(device)
print(image_cond.shape)
if not patcher.model.is_patched:
log.info("Re-loading control LoRA...")
patcher = apply_lora(patcher, device, device, low_mem_load=False)
patcher.model.is_patched = True
latent_video_length = noise.shape[1]